U.S. patent application number 14/745329 was filed with the patent office on 2015-12-24 for estimating impact of property on individual health - property score.
The applicant listed for this patent is William E. Hayward. Invention is credited to William E. Hayward.
Application Number | 20150370986 14/745329 |
Document ID | / |
Family ID | 54869900 |
Filed Date | 2015-12-24 |
United States Patent
Application |
20150370986 |
Kind Code |
A1 |
Hayward; William E. |
December 24, 2015 |
ESTIMATING IMPACT OF PROPERTY ON INDIVIDUAL HEALTH - PROPERTY
SCORE
Abstract
Embodiment of the invention provide a method for determining a
health index of a property area. The method comprises acquiring
property data associated with a property area from a data source,
and extracting a first property attribute data from the property
data acquired. The first property attribute data extracted is used
to determine presence or movement of a first pollutant data within
the property area. The method further comprises determining a first
potential impact data the first pollutant data may have on
individual health based in part on the first property attribute
data extracted, and computing a property score representing a
health index of the property area based in part on the first
potential impact data determined.
Inventors: |
Hayward; William E.;
(Carmel, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Hayward; William E. |
Carmel |
CA |
US |
|
|
Family ID: |
54869900 |
Appl. No.: |
14/745329 |
Filed: |
June 19, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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62015322 |
Jun 20, 2014 |
|
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Current U.S.
Class: |
705/2 |
Current CPC
Class: |
G16H 10/20 20180101;
G06Q 10/00 20130101; G16H 50/30 20180101; G06K 9/46 20130101; Y02A
90/10 20180101; G06Q 50/16 20130101; G16H 10/60 20180101; G06F
3/04842 20130101; G06T 2207/10004 20130101; G06Q 50/163
20130101 |
International
Class: |
G06F 19/00 20060101
G06F019/00 |
Claims
1. A method for determining a health index of a property area, the
method comprising: acquiring property data associated with a
property area from a data source; extracting a first property
attribute data from the property data acquired, wherein the first
property attribute data extracted is used to determine presence or
movement of a first pollutant data within the property area;
determining a first potential impact data the first pollutant data
may have on individual health based in part on the first property
attribute data extracted; and computing a property score
representing a health index of the property area based in part on
the first potential impact data determined.
2. The method of claim 1, wherein: the property score predicts
presence of at least one pollutant within the property area; and
the at least one pollutant contributes to an illness or disease and
negatively impacts individual health.
3. The method of claim 1, wherein: the property data comprises at
least one of the following: climate data relating to an environment
around the property area, data relating to the property area and
construction of the property area, and image data relating to the
property area.
4. The method of claim 1, wherein: the data source is at least one
of the following: a third-party data source, and user input.
5. The method of claim 1, further comprising: maintaining a
collection of multiple questions; selecting a question from the
collection; generating a graphical user interface (GUI) for
display, wherein the GUI includes the selected question; and
receiving user input including a user response to the selected
question.
6. The method of claim 5, wherein selecting a question from the
collection comprises adaptively selecting a question from the
collection based in part on at least one of the following: the
property data acquired, and prior user input received.
7. The method of claim 5, further comprising: extracting a second
property attribute data from the user input received, wherein the
second property attribute data extracted is used to determine
presence or movement of the first pollutant data within the
property area; adjusting the first potential impact data determined
based in part on the second property attribute data extracted; and
adjusting the property score computed based in part on the adjusted
first potential impact data determined.
8. The method of claim 5, further comprising: extracting a second
property attribute from the input received, wherein the second
property attribute extracted is used to determine presence or
movement of a second pollutant within the property area;
determining a second potential impact the second pollutant may have
on individual health based in part on the second property attribute
extracted; and adjusting the property score computed based in part
on the second potential impact determined.
9. The method of claim 1, wherein: the first property attribute
data has a corresponding amplification factor; and the first
potential impact data determined is based in part on the
corresponding amplification factor.
10. The method of claim 1, further comprising: generating a report
including the property score and a recommendation for improving the
health index of the property.
11. The method of claim 10, wherein the recommendation comprises a
remediation action or intervention.
12. The method of claim 1, further comprising: collecting user
feedback collected relating to use of different building materials
or different building assemblies in construction projects for
different property areas; and based in part on the user feedback
collected, generating a recommendation for proposed construction in
a particular property area, wherein the recommendation is
customized to best address local pollutants and sensitivities of a
local population of the particular property area.
13. The method of claim 1, further comprising: tracking and
assessing health index of one or more property areas.
14. The method of claim 1, further comprising: determining
potential health issues associated with a particular property
area.
15. The method of claim 1, further comprising: generating a
recommendation for a retailer for a particular property area,
wherein the recommendation is customized to suggest what building
materials to sell, when to sell the building materials, and who to
sell the building materials to, based on regional population health
and health risks of the particular property area.
16. The method of claim 1, further comprising: generating property
scores for multiple property areas; for each property area,
determining an estimated cost of improvements for the property
area; and providing a comparison tool that allows a user to compare
purchase costs for the property areas, the property scores, and the
estimated costs of improvements.
17. The method of claim 1, further comprising: crowdsourcing
information associated with a particular property area from a
community of users, wherein the information crowdsourced relates to
indoor air quality of the particular property area; computing a
property score representing a health index of the particular
property area based in part on the information crowdsourced; and
generating a recommendation for improving the health index of the
particular property area.
18. The method of claim 17, further comprising: providing a
collaboration tool that facilitates collaboration among the
community in improving the indoor air quality of the property area;
and providing a resource tool that assists the community in
improving the indoor air quality of the property area.
19. A system comprising a computer processor, a computer-readable
hardware storage medium, and program code embodied with the
computer-readable hardware storage medium for execution by the
computer processor to implement a method for determining a health
index of a property area, the method comprising: acquiring property
data associated with a property area from a data source; extracting
a first property attribute data from the property data acquired,
wherein the first property attribute data extracted is used to
determine presence or movement of a first pollutant data within the
property area; determining a first potential impact data the first
pollutant data may have on individual health based in part on the
first property attribute data extracted; and computing a property
score representing a health index of the property area based in
part on the first potential impact data determined.
20. A computer program product comprising a computer-readable
hardware storage medium having program code embodied therewith, the
program code being executable by a computer to implement a method
for determining a method for determining a health index of a
property area, the method comprising: acquiring property data
associated with a property area from a data source; extracting a
first property attribute data from the property data acquired,
wherein the first property attribute data extracted is used to
determine presence or movement of a first pollutant data within the
property area; determining a first potential impact data the first
pollutant data may have on individual health based in part on the
first property attribute data extracted; and computing a property
score representing a health index of the property area based in
part on the first potential impact data determined.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority from U.S. Provisional
Patent Application Ser. No. 62/015,322, filed on Jun. 20, 2014,
incorporated herein by reference.
BACKGROUND
[0002] The present invention generally relates to estimating impact
of a property on health of an individual, and more particularly, to
a system, method and computer program product for correlating
health and sensitivities of an individual (e.g., an occupant of the
property) with physical design and attributes of a property, local
weather and air quality so as to provide the individual an ongoing
assessment of degree of health risk the property may have on the
health of the individual.
[0003] Conventionally, a property is physically inspected to
determine the structural integrity of the property. Current
inspection protocols, however, do not factor in personal health
sensitivities or impacts of a current/prospective owner/occupant of
the property and data particular to the building of the property
(e.g., building practices, building materials, design of the
property, geographical location, ventilation system, etc.) to
determine the potential impact the property may have on the health
of the owner/occupant. A current/prospective owner/occupant of a
property may need to retain the additional services of a qualified
property inspector to physically inspect the property and assess
potential health-related issues that may arise as a result of
occupying the property. The assessment provided by the property
inspector, however, may be biased, limited due to lack of
sufficient data, and susceptible to human error. Further, retaining
the services of the property inspector may be costly.
BRIEF SUMMARY
[0004] One embodiment of the invention provides a method for
determining a health index of a property area. The method comprises
acquiring property data associated with a property area from a data
source, and extracting a first property attribute data from the
property data acquired. The first property attribute data extracted
is used to determine presence or movement of a first pollutant data
within the property area. The method further comprises determining
a first potential impact data the first pollutant data may have on
individual health based in part on the first property attribute
data extracted, and computing a property score representing a
health index of the property area based in part on the first
potential impact data determined.
[0005] These and other features, aspects and advantages of the
present invention will become understood with reference to the
following description, appended claims and accompanying
figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The subject matter which is regarded as the invention is
particularly pointed out and distinctly claimed in the claims at
the conclusion of the specification. The foregoing and other
objects, features, and advantages of the invention are apparent
from the following detailed description taken in conjunction with
the accompanying drawings in which:
[0007] FIG. 1 illustrates an example system 100, in accordance with
an embodiment of the invention;
[0008] FIG. 2 illustrates the centralized computing environment 200
in detail, in accordance with an embodiment of the invention;
[0009] FIG. 3 illustrates an example of different question banks
265 maintained by the computing environment 200, in accordance with
an embodiment of the invention;
[0010] FIG. 4 illustrates another example of different question
banks 265 maintained by the computing environment 200, in
accordance with an embodiment of the invention;
[0011] FIG. 5 illustrates an example property score application
420, in accordance with an embodiment of the invention;
[0012] FIG. 6 illustrates an example process 600 for obtaining
information used in determining a property score for a property, in
accordance with an embodiment of the invention;
[0013] FIG. 7 illustrates an example algorithm 425 applied by the
score calculator unit 421 to determine a property score for a
property, in accordance with an embodiment of the invention;
[0014] FIG. 8 illustrates an example webpage 710, in accordance
with an embodiment of the invention;
[0015] FIG. 9 illustrates an example webpage 700 generated in
response to receiving a property address, in accordance with an
embodiment of the invention;
[0016] FIG. 10 illustrates an example personal profile application
430, in accordance with an embodiment of the invention;
[0017] FIG. 11 illustrates an example process 610 for obtaining
information used in creating a personal profile for a user, in
accordance with an embodiment of the invention;
[0018] FIG. 12 illustrates an example property match application
440, in accordance with an embodiment of the invention;
[0019] FIG. 13 illustrates an example process 620 for obtaining
information used in determining a property match score, in
accordance with an embodiment of the invention;
[0020] FIG. 14 illustrates an example algorithm 443 applied by the
property match calculator unit 441 to determine a property match
score, in accordance with an embodiment of the invention;
[0021] FIG. 15 illustrates an example property health advice
application 450, in accordance with an embodiment of the
invention;
[0022] FIG. 16 illustrates an example health insurance correlation
application 460, in accordance with an embodiment of the
invention;
[0023] FIG. 17 illustrates an example algorithm 465 applied by the
correlation unit 461 to determine health insurance correlations, in
accordance with an embodiment of the invention;
[0024] FIG. 18 illustrates an example crowdsourcing application
470, in accordance with an embodiment of the invention;
[0025] FIG. 19 illustrates an example contractor recommendation
application 480, in accordance with an embodiment of the
invention;
[0026] FIG. 20 illustrates an example virtual inspection
application 490, in accordance with an embodiment of the
invention;
[0027] FIG. 21 illustrates an example investment risk application
800, in accordance with an embodiment of the invention;
[0028] FIG. 22 illustrates an example investment risk comparison
report, in accordance with an embodiment of the invention; and
[0029] FIG. 23 is a high level block diagram showing an information
processing system useful for implementing an embodiment of the
present invention.
[0030] The detailed description explains the preferred embodiments
of the invention together with advantages and features, by way of
example with reference to the drawings.
DETAILED DESCRIPTION
[0031] The present invention generally relates to estimating impact
of a property on health of an individual, and more particularly, to
a system, method and computer program product for correlating
health and sensitivities of an individual (e.g., an occupant of the
property) with physical design and attributes of a property, local
weather and air quality so as to provide the individual an ongoing
assessment of degree of health risk the property may have on the
health of the individual.
[0032] One embodiment of the invention provides a method for
determining a health index of a property area. The method comprises
acquiring property data associated with a property area from a data
source, and extracting a first property attribute data from the
property data acquired. The first property attribute data extracted
is used to determine presence or movement of a first pollutant data
within the property area. The method further comprises determining
a first potential impact data the first pollutant data may have on
individual health based in part on the first property attribute
data extracted, and computing a property score representing a
health index of the property area based in part on the first
potential impact data determined.
[0033] In this specification, the terms "property" and "property
area" are generally used to reference all synonyms of different
types of spaces, areas and dwellings intended for occupancy,
whether commercial or residential, single or multi-family,
individual structures or tract developments governed by homeowners
association (HOA) covenance, currently existing, under construction
or proposed. Examples of properties/property areas may include, but
are not limited to, the following: a house, a dwelling, a mobile
home, a set of houses, a housing development, a suburb, a town, a
city, a state, a country, an apartment building composed of
multiple units, an estate, housing stock, a set of houses within an
enclosed geographic area, a set of houses that are separated by
significant space, a city block, a building, a property approved
for inhabitation, a set of houses that share a common
characteristic, such as a peaked roof, a site of a future house,
sites of future houses, a construction site for a house or multiple
houses, track houses, custom homes, all houses within a given
region, a houseboat, a physical space that currently contains one
or more houses, covenance controlled groupings or developments
(e.g., groupings or developments governed by HOA covenance), and
housing stock owned, controlled and/or managed by a government, a
property management group, a developer or a builder. The terms
"property" and "property area" are used interchangeably in this
specification.
[0034] In this specification, the term "user" is generally used to
reference an individual or an entity. Examples of users include,
but are not limited to, the following: may be a current owner of a
property, a prospective owner of a property, an occupant of a
property (e.g., a tenant), an individual who is present on a
property for work/educational purposes (e.g., an employee of a
business operating on a property, a student of a school operating
on a property), a patron of a business operating on a property
(e.g., a hotel guest, a restaurant guest), etc. The terms
"individual" and "user" are used interchangeably in this
specification.
[0035] In this specification, the term "pollutants" is generally
used to reference materials that may negatively impact/harm an
environment and health of an individual. Pollutants may originate
in an indoor environment or an outdoor environment. There may be
different types of pollutants, such as chemical pollutants,
biological pollutants, and toxic pollutants. Examples of different
chemical pollutants, biological pollutants and toxic pollutants may
include, but are not limited to, the following: pathogens (e.g.,
infectious agents such as bacteria, virus, fungi, etc.), irritants
(e.g., chemicals that are not corrosive to human tissue and whose
effects are reversible), poison (e.g., substances with an inherent
property that may destroy human life or impair human health), toxin
(e.g., a poison produced by an organism), allergens, gases,
chemicals, pollen, jet fuel, freeway emissions, dust mites, dust
mite by products, dampness, molds, mycotoxins, chemicals, bacteria,
yeast, micro biome imbalances, excess particulate, ozone
imbalances, Volatile Organic Compounds, Microbial Volatile Organic
Compounds, Semi-volatile Organic Compounds, lead paint, asbestos,
microfibers, etc.
[0036] In this specification, the term "indoor air" is generally
used to reference interior air of a property that is inhalable or
in contact with skin of an individual.
[0037] In this specification, the term "indoor air quality" is
generally used to reference total presence and interaction of
components of indoor air. Examples of components that may impact
indoor air quality may include, but are not limited to, the
following: indoor pollution, fresh air supply, temperature, and
humidity that influences a human body's ability to establish and
maintain homeostasis.
[0038] In this specification, the term "homeostasis" is generally
used to reference ability or tendency of an individual to maintain
internal stability and functioning to compensate for environmental
changes. An example of homeostasis is a human body maintaining an
average temperature of 98.6 degrees F. in extreme heat or cold.
Another example of homeostasis is a human body rebalancing
functioning when exposed to pollutants.
[0039] In this specification, the term "health" is generally used
to reference comparative effects and ability to function resulting
from a human body's ability to establish and maintain homeostasis
within extremes of illness and thriving.
[0040] In this specification, the terms "illness" and "disease" are
generally used to reference when a human body fails to achieve a
reasonably functional state of homeostasis.
[0041] In this specification, the term "individual health and
sensitivities" is generally used to reference specific attributes
experienced by an individual, such as individual susceptibilities
and impacts to different potential illness and disease outcomes
that may affect the health of the individual.
[0042] In this specification, the terms "health risk" and "risk
assessment of health" is generally used to reference
estimated/predicted negative impact on health of an individual.
[0043] In this specification, the term "health index" is generally
used to reference an assessment of degree of health risk on health
of the individual.
[0044] Embodiments of the invention correlate symptomology and
sensitivities of a user with physical design and attributes of a
property, local weather and air quality so as to provide the user
an ongoing assessment of degree of health risk the property may
have on the health of the user. Embodiments of the invention allow
for expression of the idea that presence and/or combination of
physical design and attributes of a property is analogous to DNA.
Further, physical design and attributes of a property when combined
with environmental context information relating to the property
(e.g., local weather and air quality) may be used to provide an
ongoing assessment of degree of health risk the property may have
on the health of the user.
[0045] Embodiments of the invention provide a comparatively
low-cost solution for objectively and digitally determining
potential impact a property may have on health of an individual
(e.g., current/prospective occupant of the property).
[0046] In this specification, the term "property attributes" is
generally used to reference different physical and geographical
characteristics of a property (e.g., physical design and
attributes, local weather, air quality, etc.).
[0047] Embodiments of the invention correlate different property
attributes with different individual susceptibilities and impacts
to different potential illness and disease outcomes that may affect
the health of an individual.
[0048] FIG. 1 illustrates an example system 100, in accordance with
an embodiment of the invention. The system 100 comprises a
centralized computing environment 200 including one or more server
devices 210, and one or more storage devices 220. The storage
devices 220 may maintain one or more databases 260. One or more
applications 410 (FIG. 2) may execute/operate on the server devices
210 to provide one or more online, virtual tools relating to a
property area.
[0049] A user may access an online, virtual tool provided by the
computing environment 200 using an electronic user client device
299, such as a personal computer, or a mobile device (e.g., a
laptop computer, a tablet, a mobile phone, etc.). In one
embodiment, each user client device 299 exchanges data with the
computing environment 200 over a connection (e.g., a wireless
connection, a wired connection, or a combination of the two).
[0050] As described in detail later herein, the computing
environment 200 is configured to acquire property data for a
property from one or more data sources, such as third-party data
sources 120 or a user. Property data for a property may include,
but is not limited to, the following: climate data about
environment around the property, public data about the property and
its construction (e.g., age of property, average precipitation in
the environment around the property, whether the property is
located in an urban area, last major construction of the property,
age of roof of the property), image data 110 (FIG. 2) for the
property, and user input 111 (e.g., user responses to questions
relating to the property, user feedback).
[0051] FIG. 2 illustrates the centralized computing environment 200
in detail, in accordance with an embodiment of the invention. The
centralized computing environment further comprises a data
acquisition unit 245 configured to acquire property data for a
property from different types of third-party data sources 120 (FIG.
1), such as a property listings data source 121 (e.g., a property
listing database (MLS, Redfin, Zillow), a climate data source 122
providing climate data about environment around the property (e.g.,
climate data from American Society of Heating, Refrigerating, and
Air-Conditioning Engineers (ASHRAE), climate zone maps from
Department of Energy (DOE), etc.), and a location data source 123.
Other types of third-party data sources 120 may include data
sources providing data about the property and its construction,
geophysical data, proximity data, proxy data, contractor data,
disclosure data, and model data for modeling/projecting factors
used by one or more applications 410 executing/operating on the
server devices 210. Property data for a property may include raw
actual data and/or statistical data.
[0052] In one embodiment, the data acquisition unit 245 is
configured to interface with web service interfaces of third-party
data sources 120 (e.g., Google Maps via Google Maps API, Bing and
other similar web services) to acquire/download data from the
third-party data sources 120.
[0053] In one embodiment, the storage devices 220 (FIG. 1)
maintains at least one database 260 including a collection 261 of
datasets 262 of property attributes for different property
addresses located across different geographical locations (e.g.,
nationwide). As described in detail later herein, the computing
environment 200 is configured to acquire property data for
different properties located across different geographical
locations (e.g., nationwide) from multiple data sources, such as
third-party data sources 120. Relevant data used in determining
property attributes may be extracted from the property data
acquired. Any relevant data extracted may be processed and/or
transformed for determining property attributes, and may be
maintained in the storage devices 220, in compliance with third
party agreements, if any.
[0054] In one embodiment, the data acquisition unit 245 is
configured to determine property attributes based on property data
acquired from one or more data sources, such as third-party data
sources 120 or a user. For example, for a particular property, the
data acquisition unit 245 may acquire raw actual data associated
with the property from one or more third-party data sources 120.
The data acquisition unit 245 may also acquire statistical data
associated with the property and/or geographical location of the
property from one or more third-party data sources 120. The data
acquisition unit 245 may also acquire other types of data
associated with the property from other types of data sources. The
data acquisition unit 245 may extract disparate heterogeneous
property attributes from the raw actual data and/or the statistical
data acquired, and maintain a dataset 262 of property attributes
for the property in at least one database 260.
[0055] In one embodiment, a dataset 262 of property attributes for
a property may include the following physical and geographical
characteristics: a corresponding property address (i.e., physical
address), corresponding latitude and longitude of the property, age
of the property, climate data from its nearest point source (e.g.,
temperature ranges, precipitation data, and relative humidity data
from climate data corresponding to a city in which the property is
located), number of bedrooms, internal wall type, external wall
type, air conditioning/cooling type, heating type, roof type,
basement type, floor type covering, pollen data, etc.
[0056] In one embodiment, the computing environment 200 further
comprises an image processing unit 411 configured to process image
data 110 acquired by the data acquisition unit 245 from a
third-party data source 120 (e.g., Google Maps, Redfin, Zillow or
other similar web services) or a user (e.g., images/photos uploaded
by a user and captured via an image capture device). The image
processing unit 411 may comprise a machine learning classifier that
is trained to recognize specific property attributes for a property
based on image data 110 for the property. Image data 110 for a
property may include one or more images and/or one or more videos
capturing one or more areas of the property and/or environment
around the property.
[0057] In one embodiment, the image processing unit 411 may utilize
specialized detection techniques on image data 110 for a property
for determining presence of a peaked roof on the property, presence
of a basement on the property, external wall type of the property,
and volume of the property.
[0058] In one embodiment, the image processing unit 411 may utilize
specialized detection techniques on image data 110 for a property
for evaluating topography to determine if water flows away from or
towards the property.
[0059] In one embodiment, the image processing unit 411 computes an
approximate volume of a property based on a plan map view and a
street map view included in image data 110 for the property. The
image processing unit 411 may utilize specialized detection
techniques on the image data 110 for determining a length, a width
and a height of the property. The image data analysis/processing
unit 411 then computes the approximate volume of the property as
the product of the length, the width and the height of the
property.
[0060] In one embodiment, the computing environment 200 maintains a
collection 270 of different climate groups 275. A climate group 275
may represent a particular climate zone (e.g., hot-humid, hot-dry,
cold, frigid, moderate, mixed, etc.). As described in detail later
herein, a property address associated with a property may be
classified in a particular climate group 275 of the collection 270
based on property attributes for the property.
[0061] In one embodiment, utilizing the data acquisition unit 245
and the image processing unit 411, the computing environment 200 is
configured to acquire property data, determine property attributes
based on the property data, and correlate the property attributes
on a per property address basis nationwide. For example, the
computing environment 200 may operate in accordance with Steps 1-15
provided below:
[0062] Step 1: For each city, for each street (in alphabetical
order), extract a property address in numerical sequence.
[0063] Step 2: Using the property address, acquire raw actual data
for a property associated with the property address from a third
party data source 120, such as a property listings database 121.
Determine property attributes based on the raw actual data
acquired. The property attributes determined may include latitude
and longitude of the property, age of the property, number of
bedrooms within the property, internal wall type of the property,
air conditioning/cooling type of the property, heating type of the
property, and floor covering type of the property.
[0064] Step 3: If raw actual data for the property is not available
from a third party data source 120, determine property attributes
for the property based on statistical data acquired from a third
party data source 120.
[0065] Step 4: Acquire a plan map view of the property from a
third-party data source 120 (e.g., Google Maps, Redfin, Zillow or
other similar web services).
[0066] Step 5: Determine a length and a width of the property based
on the plan map view.
[0067] Step 6: Acquire a street map view of the property from a
third-party data source 120 (e.g., Google Maps, Redfin, Zillow or
other similar web services).
[0068] Step 7: Identify the property in the street view using
specialized detection techniques.
[0069] Step 8: Determine a height of the property using specialized
detection techniques.
[0070] Step 9: Compute an approximate volume of the property based
on the length, the width and the height of the property.
[0071] Step 10: Use specialized detection techniques to determine
whether the property has a peaked roof or a flat roof.
[0072] Step 11: Use specialized detection techniques to determine
whether the property has a basement. In the event that the
specialized detection techniques used are unsuccessful, use brute
force pixel sequence evaluation to detect pattern variations.
[0073] Step 12: Use specialized detection techniques to determine
external wall type of the property. In the event that the
specialized detection techniques are unsuccessful, use brute force
pixel sequence evaluation to detect pattern variations.
[0074] Step 13: Acquire climate data for a geographical
location/area in which the property address is located from a
third-party data source 120 (e.g., a climate data source 122).
Extract temperature ranges, precipitation data, and relative
humidity data from the climate data.
[0075] Step 14: Determine which climate group 275 the property
address should be classified in based on the temperature ranges,
the precipitation data, and the relative humidity data.
[0076] Step 15: Store all the different property attributes
computed/determined for the property address in the database
260.
[0077] In one embodiment, a property attribute maintained in the
database 260 may be assigned a default value or a range of default
values if data specific to that property attribute is
unavailable.
[0078] As stated above, one or more applications 410 may
execute/operate on the server devices 210 (FIG. 1) to provide one
or more online, virtual tools relating a property area. In one
embodiment, the computing environment 200 further comprises a
website generator 290 configured to generate one or more websites
295 for the online, virtual tools. A user may access a website 295
via a user client device 299.
[0079] In one embodiment, the computing environment 200 further
comprises a collection 264 of different question banks 265. Each
question bank 265 maintains a specific set of questions for
obtaining, from a user, additional data that is not available from
a third-party data source 120. As described in detail later herein,
an application 410 may select which questions from the questions
banks 265 to query a user with. The selected questions may be
presented/displayed to the user on a website 295. All user input
111 entered by the user via the website 295 in response to the
questions presented may be collected and maintained in at least one
database 260. As described in detail later herein, one or more
applications 410 operating on the server devices 210 may analyze
user input 111 for purposes of customization or refinement.
[0080] In one embodiment, the computing environment 200 may receive
different user inputs 111 comprising different user feedback
relating to use of different building materials and/or different
building assemblies in construction projects for different property
areas. A user (e.g., a builder, a developer, an architect, etc.)
may enter user feedback via a website 295. User feedback may
indicate success or failure of using particular building materials
and/or particular building assemblies in particular property areas.
All user feedback is collected and maintained in a building
assemblies feedback database 900. The database 900 represents a
vast data source on different building materials and/or different
building assemblies. As described in detail later herein, one or
more applications 410 operating on the server devices 210 may use
the database 900 in determining which building materials and/or
building assemblies are unsuitable for specific climates that are
susceptible to moisture and/or pollutant accumulation. As another
example, one or more applications 410 operating on the server
devices 210 may also use the database 900 in determining which
building materials and/or building assemblies are suitable for
specific climates that are susceptible to moisture and/or pollutant
accumulation.
[0081] FIG. 3 illustrates an example of different question banks
265 maintained by the computing environment 200, in accordance with
an embodiment of the invention. The question banks 265 may include,
but are not limited to, the following: a question bank 265A
comprising one or more questions inquiring about property
attributes of a property ("property attributes questions"; see
examples of property attributes questions shown in FIG. 3), a
question bank 265B comprising one or more questions inquiring about
surroundings around a property ("proximity questions"; see examples
of proximity questions shown in FIG. 3), a question bank 265C
comprising one or more questions inquiring about pets located at a
property ("pet questions"; see examples of pet questions shown in
FIG. 3), and a question bank 265D comprising one or more questions
inquiring about particular user behaviors specific to a property
("user behavioral questions"; see examples of user behavioral
questions shown in FIG. 3).
[0082] FIG. 4 illustrates another example of different question
banks 265 maintained by the computing environment 200, in
accordance with an embodiment of the invention. The question banks
265 may include, but are not limited to, the following: a question
bank 265E comprising one or more questions for querying a user
about his/her personal motivations and goals ("personal motivations
and goals questions"; see examples of personal motivations and
goals questions shown in FIG. 4), a question bank 265F comprising
one or more questions for querying a user about his/her general
sensitivities to certain triggers ("initial screening questions";
see examples of initial screening questions shown in FIG. 4), a
question bank 265G comprising one or more threshold questions for
querying a user about his/her threshold limits with regards to
exposure to certain triggers ("threshold questions"; see examples
of threshold questions shown in FIG. 4), a question bank 265H
comprising one or more questions for querying a user about his/her
sensitivities to certain triggers ("sensitivity questions"; see
examples of sensitivity questions shown in FIG. 4), a question bank
265I comprising one or more questions for querying a user about
symptoms experienced by the user ("symptoms questions"; see
examples of symptoms questions shown in FIG. 4), a question bank
265J comprising one or more questions for querying a user about
potential masking effects (i.e., impact lifestyle and previous
exposures the user has experienced) ("masking questions"; see
examples of masking questions shown in FIG. 4), a question bank
265K comprising one or more questions for querying a user about
impact a property has had on the user ("personal impact questions";
see examples of personal impact questions shown in FIG. 4), and a
question bank 265L comprising one or more questions for querying
user feedback and assessment with respect to any recommendations
generated by the computing environment 200 ("feedback and
assessment questions"; see examples of feedback and assessment
questions shown in FIG. 4).
[0083] In one embodiment, some questions maintained in one question
bank 265 may overlap with some questions maintained in another
question bank 265.
[0084] A response to a question may be provided in different
manners. For example, in response to a question requiring a "yes"
or "no" answer, a user may respond to the question by indicating
either "yes" or "no". As another example, in response to a question
requiring a user to select one or more checkboxes representing
suggested answers, a user may respond to the question by selecting
one or more of the checkboxes. As another example, in response to a
question where the answer may fall within a range of values, a user
may respond to the question by positioning a slider along a sliding
scale to a particular value in the range. As another example, a
user may respond to a question by entering free form text (e.g.,
entering text in an input comment box).
[0085] Property Score Application
[0086] In this specification, the term "property score" represents
a health index for the property, its immediate environments, and
physical and geographical characteristics associated with the
property. A property score for a property may be used to predict
presence of factors (e.g., presence of bacteria, virus, mold,
pollen, dust mites, pet dander, chemicals and other pollutants) at
the property that may contribute to illnesses and diseases, and
that may negatively impact health of an individual. A property
score may be represented using a number grade, a percentage grade,
a letter grade, etc. In one embodiment, the property score may be a
numerical grade that ranges anywhere between a minimum of 1 and a
maximum of 100.
[0087] FIG. 5 illustrates an example property score application
420, in accordance with an embodiment of the invention. In one
embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
property score application 420. The property score application 420
comprises a property score calculator unit 421 configured to
determine a property score for a property based on property
attributes for the property. The property score may be stored in
the database 260 together with a dataset 262 including the property
attributes for the property.
[0088] In one embodiment, a property score for a property may
represent ability for pollutants to develop and move within the
property. For each possible type of pollutant, the property score
calculator unit 421 is configured to identify certain physical
and/or geographical characteristics of the property that may
increase or decrease presence and/or movement of the pollutant. The
property score calculator unit 421 utilizes an algorithm to
determine potential impact (i.e., severity) a combination of
pollutants may have upon health of an individual.
[0089] The property score calculator unit 421 is configured to
analyze input data acquired from different data sources such as,
but not limited to, public data from third-party data sources 120,
data from crowdsourcing, user input from users, sensor data from
property sensors, and internal databases. As described in detail
later herein, based on input data, the property score calculator
unit 421 computes initial, dynamically inter-related
factors/indexes used in determining a property score.
[0090] In one embodiment, the property score application 420
comprises a property score report unit 423 for generating a
property score report that includes a property score for a
property. A property score report including a property score for a
property provides an indication of when an imbalance in the
property exists. The property score report may also include one or
more recommendations, such as remediation actions and/or
interventions for a user (e.g., occupant of the property) to take
to improve the property score. Information contained in the various
factors/indexes contributing to the property score can provide
guidance as to what actions and/or interventions are most
appropriate. A new property score for the property may be
determined after the user performs the remediation actions and/or
improvements recommended to provide verification of effective and
sufficient improvement.
[0091] A property score report may be presented to a user via a
website 295.
[0092] The property score report may also suggest one or more
remediation actions and/or interventions for a user to take.
[0093] In this specification, the term "prevalence" is used to
denote frequency of a particular attribute, factor or index. For
example, if the prevalence of refrigeration-type air conditioners
is ten times more than the prevalence of evaporative-type air
coolers, the influence of evaporative-type air coolers on a
property score will be less than the influence of
refrigeration-type air conditioners on the property score.
[0094] In this specification, the term "weighting" is used to
denote a comparative contribution of a particular attribute, factor
or index. For example, if the impact of evaporative-type air
coolers, when present, on an indoor environment is ten times more
than the impact of refrigeration-type air conditioners, the
influence of evaporative-type air coolers on a property score will
be more than the influence of refrigeration-type air conditioners
on the property score.
[0095] In one embodiment, the property score application 420
comprises a weightings unit 422. The weightings units 422
comprises, but is not limited to, the following: (a) different
weighting values for different attributes, factors or indexes, (b)
different prevalence values for different attributes, factors or
indexes, and (c) data representing interrelationships between
different attributes, factors or indexes. For example, a property
attribute may have a corresponding weighting value and a
corresponding prevalence value, wherein the combination of the
weighting value and the prevalence value represents how much the
property attribute is likely to influence a property score for a
property.
[0096] In one embodiment, a weighting value and/or a prevalence
value may be pre-defined or determined based on data correlations.
The data correlations may be learned through application of a
machine learning algorithm, survey data and/or analysis of
experts/professionals. The data correlations may be determined
based on different data sets, such as property attributes for the
property, factors/indexes used in determining the property score
for the property, personal profiles, health insurance
recommendations, health records, virtual inspections of the
property, personal action plans, expert judgment, survey results,
user responses to questions, user actions, user feedback indicating
results of performing recommended remediation actions and/or
interventions, etc. These different datasets may also be used to
refine/adjust one or more of the weighting values and/or a
prevalence values maintained.
[0097] An amplification factor for a particular
attribute/factor/index represents a combination of prevalence and
weighting for the particular attribute/factor/index. Amplification
factors are determined based on combinations of data correlations
determined from machine learning algorithms, large dataset surveys,
and expert judgment. An amplification factor for a particular
attribute/factor/index modifies the particular
attribute/factor/index to more accurately reflect a true influence
of the particular attribute/factor/index on a property score,
thereby improving accuracy and utility of the property score. For
example, if the prevalence of refrigeration-type air conditioners
is ten times more than the prevalence of evaporative-type air
coolers, but the impact of evaporative-type air coolers, when
present, on indoor environment is ten times more than the impact of
refrigeration-type air conditioners, evaporative-type air coolers
have low prevalence and high weighting values. As such, the
influence of evaporative-type air coolers on a property score will
only be significant if evaporative-type air coolers are
present.
[0098] In one embodiment, the property score application 420 may
acquire property data for a property from a user by presenting one
or more questions via a website 295. Specifically, the property
score application 420 comprises an adaptive question selection unit
424 for adaptively selecting questions from the collection 264
based on property data for a property (e.g., climate data about the
environment around the property, public data about the property and
its construction, and user input, if any). If, at any point during
the presentation of the selected questions, user responses seem
contradictory or mis-entered, the adaptive question selection unit
424 runs a related education module and then repeats or rephrases
the selected questions. Questions selected and presented to a user
are dynamically selected based on prior user interactions (e.g.,
prior user responses). Even if user input is not available, the
property score calculator unit 421 may still determine a property
score for the property based on property data acquired from other
data sources, such as a third-party data source 120.
[0099] In one embodiment, a property score for a property
maintained in the database 260 is updated when updated/additional
property attributes for the property are determined. For example,
property attributes maintained in the database 260 may be refreshed
on a cyclic basis to ensure that the most current property
attributes are available when determining a property score. The
frequency/cycle at which a particular property attribute within the
database 260 is refreshed is based on the nature of the property
attribute. For example, climate-related property attributes may be
refreshed annually, whereas property attributes representing
physical characteristics may be refreshed every five years. In the
instance where a particular property attribute used in calculating
a factor/index corresponding to a pollutant is generated by a
third-party data source 120, the property attribute will be updated
upon notification from the third-party data source 120 of
significant changes to the attribute. The refresh of property
attributes will utilize the same methods of data acquisition as
performed by the data acquisition unit 245. When property
attributes for a property are refreshed, a new property score for
the property is determined and stored in the database 260.
[0100] In one embodiment, the property score application 420
extracts/determines a property attribute data (e.g., pattern
relating to a property attribute) from property data associated
with a property area. The property score application 420 combines
the property attribute data with at least one other property
attribute data to determine presence or movement of a pollutant
data (e.g., pattern relating to a pollutant) within the property
area. The property score application 420 determines a potential
impact data (e.g., pattern relating to personal impact) that the
pollutant data may have on individual health based in part on the
combination, and computes a property score representing a health
index of the property area based in part on the potential impact
data.
[0101] In one embodiment, the property score calculator unit 421
determines a property score for a property based on the following
factors/indexes: a home structural attributes index for the
property, an indoor chemical index for the property, an indoor
particle index for the property, an indoor pet index for the
property, an indoor dampness index for the property, an indoor
cavity index for the property, an outdoor pollutant index for the
property, an outdoor environmental index for the property, an air
movement index for the property, an indoor biological activity
index for the property, an indoor mold index for the property, and
amplification factors for the indexes.
[0102] In this specification, the term "total burden" represents a
weighted calculation of total exposure an individual can be exposed
to before moving to a higher level of sensitivity. This is largely
determined by the individual's overall sensitivity levels.
Sensitivity levels, when appearing in certain combination, are
correlated to significantly lower thresholds and higher impacts for
various specific trigger items. When a burden that an individual is
exposed to is too high, the individual's overall sensitivities
rise. The property score application 420 adjusts by lowering
thresholds and raising impact scores accordingly based on data and
prior data correlations determined.
[0103] For example, if property attributes for a property and/or
user responses to questions indicate presence data points relating
to an indoor pet index, a property score for the property will be
nominally impacted by the indoor pet index. However, if the
property attributes and/or the user responses also indicate
simultaneous presence of data points relating to a significant/high
outdoor pollutant index, indoor chemical index, biological activity
index, and air movement index, this combination of indexes may
substantially enhance the impact of the indoor pet index on the
property score, as well as severity of the outdoor pollutant index,
indoor chemical index, indoor biological activity index and air
movement index on the property score.
[0104] The higher a total burden, the more frequently and the more
strongly an individual will react to particular triggers of the
property that impacts the individual. A property score report
generated for a property may suggest one or more remediation
actions and/or interventions for reducing a total burden to reduce
any impact the property may have on an individual.
[0105] In one embodiment, there may be different total burdens for
different factors/indexes. A total burden for a particular
factor/index may be used to amplify the factor/index, where
necessary.
[0106] As described in detail later herein, a factor/index may
contribute as an amplification factor for another factor/index.
[0107] In one embodiment, for each factor/index, the property score
calculator unit 421 determines a projected accuracy rating based on
number of data points used in computing the factor/index and
amplification factors for the factor/index.
[0108] Table 1 provided below comprises a listing identifying
different parameters referenced in this specification.
TABLE-US-00001 TABLE 1 Abbreviation Definition Property_Score
Property score for a property IMI Indoor mold index (IMI) IMI_Raw
Raw IMI IMI_Amplification Amplification factors for IMI
IMI_TotalBurden Total burden for IMI OPI Outdoor pollutant index
(OPI) OPI_Raw Raw OPI OPI_Amplification Amplification factors for
OPI OPI_TotalBurden Total burden for OPI ICI Indoor chemical index
(ICI) ICI_Raw Raw ICI ICI_Amplification Amplification factors for
ICI ICI_TotalBurden Total burden for ICI IBAI Indoor biological
activity index (IBAI) IBAI_Raw Raw IBAI IBAI_Amplification
Amplification factors for IBAI IBAI_TotalBurden Total burden for
IBAI IPETI Indoor pet index (IPETI) IPETI_Raw Raw IPETI
IPETI_Amplification Amplification factors for IPETI
IPETI_TotalBurden Total burden for IPETI HSAI Home structural
attributes index (HSAI) HSAI_Raw Raw HSAI HSAI_Amplification
Amplification factors for HSAI HSAI_TotalBurden Total burden for
HSAI IPI Indoor particle index (IPI) IPI_Raw Raw IPI
IPI_Amplification Amplification factors for IPI IPI_TotalBurden
Total burden for IPI IDI Indoor dampness index (IDI) IDI_Raw Raw
IDI IDI_Amplification Amplification factors for IDI IDI_TotalBurden
Total burden for IDI ICAVI Indoor cavity index (ICAVI) ICAVI_Raw
Raw ICAVI ICAVI_Amplification Amplification factors for ICAVI
ICAVI_TotalBurden Total burden for ICAVI OEI Outdoor environmental
index (OEI) OEI_Raw Raw OEI OEI_Amplification Amplification factors
for OEI OEI_TotalBurden Total burden for OEI AMI Air movement index
(AMI) AMI_Raw Raw AMI AMI_Amplification Amplification factors for
AMI AMI_TotalBurden Total burden for AMI
[0109] In one embodiment, the property score calculator unit 421
computes a property score for a property in accordance with the
equation (1) provided below:
Property_Score=HSAI+ICI+IPI+IPETI+IDI+ICAVI+OPI+OEI+AMI+IBAI+IMI
(1).
[0110] Indoor Mold Index
[0111] In one embodiment, the property score calculator unit 421
determines an indoor mold index for a property by analyzing
property data for the property (e.g., a dataset 262 comprising
property attributes for the property, user responses to questions
relating to the property, etc.) to identify data points that
indicate potential mold presence in the property. Examples of data
points that indicate potential mold presence in the property may
include, but are not limited to, the following: (a) water-related
events, such as recent events affecting the property (e.g., leaks
or floods), high dampness, and high number of wet dry cycles per
year in geographical area of the property, and (b) conditions
signaling poor maintenance of the property, such as old roofing,
broken downspouts, unkempt gutters, and old ducting. Examples of
data points that indicate potential amplifications factors for the
indoor mold index for the property may include, but are not limited
to, the following: high dampness, high number of wet dry cycles per
year in geographical area of the property, and presence of numerous
cavities in the property.
[0112] In one embodiment, the property score calculator unit 421
computes an indoor mold index (IMI) for a property in accordance
with equation (2) provided below:
IMI=IMI_Raw.times.IMI_Amplification.times.IMI_TotalBurden (2).
[0113] In one embodiment, the property score calculator unit 421
computes IMI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an indoor mold index. The property score calculator unit 421
computes IMI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an indoor mold index. The
property score calculator unit 421 computes the product of IMI_Raw,
IMI_Amplification and IMI_TotalBurden to obtain IMI.
[0114] Indoor Pet Index
[0115] In one embodiment, the property score calculator unit 421
determines an indoor pet index for a property by analyzing property
data for the property (e.g., a dataset 262 comprising property
attributes for the property, user responses to questions relating
to the property, etc.) to identify data points that indicate
potential pet presence at the property. Examples of data points
that indicate potential pet presence at the property may include,
but are not limited to, the following: user responses to pet
questions selected from the question bank 265C (FIG. 3). Examples
of data points that indicate potential amplifications factors for
the indoor pet index for the property may include, but are not
limited to, the following: vacuum usage behaviors, forced air, hard
to clean places, carpeting, and duct age.
[0116] In one embodiment, the property score calculator unit 421
computes an indoor pet index (IPETI) for a property in accordance
with equation (3) provided below:
IPETI=IPETI_Raw.times.IPETI_Amplification.times.IPETI_TotalBurden
(3).
[0117] In one embodiment, the property score calculator unit 421
computes IPETI_Raw based on weighted user responses to questions
selected from the collection 264 (e.g., pet questions from the
question bank 265C) to identify data points related to an indoor
pet index. The property score calculator unit 421 computes
IPETI_Amplification based on weighted user responses to questions
selected from the collection 264 to identify data points related to
amplifications factors for an indoor pet index. The property score
calculator unit 421 computes the product of IPETI_Raw,
IPETI_Amplification and IPETI_TotalBurden to obtain IPETI.
[0118] Outdoor Pollutant Index
[0119] An outdoor pollutant index for a property represents a
combination of various possible sources, locations, and types of
outdoor pollutants, irrespective of other indexes. In one
embodiment, the property score calculator unit 421 determines an
outdoor pollutant index for a property by analyzing property data
for the property (e.g., a dataset 262 comprising property
attributes for the property, user responses to questions relating
to the property, etc.) to identify data points that indicate
potential outdoor pollutant sources, locations, and types in close
proximity to the property. Examples of data points that indicate
potential outdoor pollutant sources, locations, and types in close
proximity to the property may include, but are not limited to, the
following: (a) industrial plants, (b) airports, (c) heavy traffic
including freeways and highways, (d) types of traffic such as
buses, trains, trucks, aircraft, (e) parking lots for malls,
schools, auditoriums, stadiums, (f) business that exhaust
pollutants such as dry cleaners, print shops, restaurants, (g)
agriculture using fertilizers and pesticides, and (h) livestock
ranching or feed lots. Examples of data points that indicate
potential amplifications factors for the outdoor pollutant index
for the property may include, but are not limited to, the
following: heavy truck and bus traffic, industrial pollution, and
agricultural activities.
[0120] In one embodiment, the property score calculator unit 421
computes an outdoor pollutant index (OPI) for a property in
accordance with equation (4) provided below:
OPI=OPI_Raw.times.OPI_Amplification.times.OPI_TotalBurden (4).
[0121] In one embodiment, the property score calculator unit 421
computes OPI_Raw based on weighted user responses to questions
selected from the collection 264 (e.g., proximity questions from
the question bank 265B) to identify data points related to an
outdoor pollutant index. The property score calculator unit 421
computes OPI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an outdoor pollutant index.
The property score calculator unit 421 computes the product of
OPCF_Raw, OPI_Amplification and OPI_TotalBurden to obtain OPI.
[0122] In one embodiment, OPI_Amplification is applied to obtain
OPI only when three or more amplification factors are present.
[0123] Indoor Chemical Index
[0124] An indoor chemical index for a property represents a
combination of various possible sources of potential chemicals in
an indoor environment of the property, irrespective of other
indexes. In one embodiment, the property score calculator unit 421
determines an indoor chemical index for a property by analyzing
property data for the property (e.g., a dataset 262 comprising
property attributes for the property, user responses to questions
relating to the property, etc.) to identify data points that
indicate potential chemical presence in the property. Examples of
data points that indicate potential chemical presence in the
property may include, but are not limited to, the following: (a)
building materials, (b) use of cleaning products, laundry
detergent, air fresheners or personal care products, and (c) use of
chemical pest control. Examples of data points that indicate
potential amplifications factors for the indoor chemical index for
the property may include, but are not limited to, the following:
(a) new building materials containing higher levels of toxic
ingredients, (b) use of fragranced cleaning products or personal
care products, and (c) frequent use of chemical pest control.
[0125] In one embodiment, the property score calculator unit 421
computes an indoor chemical index (ICI) for a property in
accordance with equation (5) provided below:
ICI=ICI_Raw.times.ICI_Amplification.times.ICI_TotalBurden (5).
[0126] In one embodiment, the property score calculator unit 421
computes ICI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points that
indicate potential chemical presence in the property. The property
score calculator unit 421 computes ICI_Amplification based on
weighted user responses to questions selected from the collection
264 to identify data points related to amplifications factors for
an indoor chemical index. The property score calculator unit 421
computes the product of ICI_Raw, ICI_Amplification and
ICI_TotalBurden to obtain ICI.
[0127] In one embodiment, ICI_Amplification is applied to obtain
ICI only when three or more amplification factors are present.
[0128] Indoor Biological Activity Index
[0129] An indoor biological activity index for a property
represents a combination of features, including features from other
indexes, that result in indoor environmental conditions necessary
for germination, amplification, life support, and potential
infestation of an indoor environment of the property by a multitude
of potential biological life forms. One or more other indexes
perform the role of amplification factors for the indoor biological
activity index. For example, the indoor dampness index is the
primary driving force for the growth of mold, bacteria, dust mites,
cockroaches, and rodents plus the release of chemicals from
moisture damaged materials and structures, as long as the other
necessary environmental conditions are present. Other environmental
conditions, structures, and indexes that affect the indoor
biological activity index include: (a) water accumulation indoors
from pipe leaks, wind driven rain penetration of the roof, cladding
on or around windows and doors, and toilet or washing machine
overflows, (b) insufficient stoppage of moisture accumulation and
removal before biological growth, especially mold, can reproduce
and sustain growth, (c) materials, based on the home structural
attributes index, that create surfaces and nutrition for
infestations, (d) structures, based on the home structural
attributes index, that provide pathways for air, moisture,
particulate, spores, pollen, insects and other pests, (e) energy,
based on the air movement index, to create migration of pollutants
and conditions through pathways for air from both outside to inside
and to circulate throughout the indoor environment, (f) particulate
identified, based on the indoor particulate index, as a primary
source of nutrients for biological growth, (g) structures, based on
the indoor cavities index, that provide micro-environments for the
accumulation of particulate, absorption of moisture, and relatively
stable ranges of temperature and available water (aW) per the
indoor dampness index to be sufficiently supportive of biological
amplification, (h) sources of nutrients and moisture based on the
outdoor pollutant index, and (i) based on the air movement index,
moisture and subsequent vapor pressure differentials, the wind and
subsequent air pressure differentials, and the extent over time
that the property is subject to factors which create the imbalance
responsible for conditions that are unhealthy for people, but
healthy for pestilence.
[0130] In one embodiment, the property score calculator unit 421
computes an indoor biological activity index (IBAI) for a property
in accordance with equation (6) provided below:
IBAI=IBAI_Raw.times.IBAI_Amplification.times.IBAI_TotalBurden
(6).
[0131] In one embodiment, the property score calculator unit 421
computes IBAI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an indoor biological activity index. The property score calculator
unit 421 computes IBAI_Amplification based on weighted user
responses to questions selected from the collection 264 to identify
data points related to amplifications factors for an indoor
biological activity index. The property score calculator unit 421
computes the product of IBAI_Raw, IBAI_Amplification and
IBAI_TotalBurden to obtain IBAI.
[0132] In one embodiment, IBAI_Amplification is applied to obtain
IBAI only when two or more amplification factors are present.
[0133] The indoor biological activity index may affect other
indexes, resulting in conditions which include, but are not limited
to: (a) all biological life takes in nutrients, (b) all biological
life excretes waste, and (c) both ingestion and excretion alters
the environment the biological life inhabits. All of the other
indexes are altered to some extent by the presence of biological
activity. The inter-relationships and feedback (both positive and
negative) among and between the Indexes creates a dynamically
changing indoor environment. When the total set of conditions
shifts away from what the human body can easily adjust to,
additional energy and action by the human organs and systems are
stressed which can eventually result in a movement away from
good-health and toward ill-health.
[0134] Home Structural Attributes Index
[0135] In one embodiment, the property score calculator unit 421
determines a home structural attributes index for a property by
analyzing property data for the property (e.g., a dataset 262
comprising property attributes for the property, user responses to
questions relating to the property, etc.) to identify data points
that indicate potential presence of structures at the property.
Examples of data points that indicate potential presence of
structures at the property may include, but are not limited to, the
following: (a) forced air heating or cooling systems, (b) cooling
with air-conditioning, evaporative cooling or natural ventilation,
(c) mechanical ventilation, (d) exhaust fans in kitchen or
bathrooms, (e) attic, with or without conditioned air, (f)
crawlspace, ventilated or conditioned air, with or without a
moisture barrier, (g) fireplace, (h) wall to wall carpeting, and
extent of coverage, (i) number of rooms, assists in identifying
occupancy, (j) stucco cladding, whether natural or synthetic
materials, (k) age of the property identifies most likely types of
structure, materials, and systems which have historically changed
over time, (l) landscaping including slope and vegetation, (m) roof
type and slope, such as flat, steep, slight, tile, shingles of
asphalt or wood or tile, (n) water removal such as gutters and
downspouts, (o) visual conditions of property, such as recent or
deferred maintenance, and (p) complex additions to the main
building. Examples of data points that indicate potential
amplifications factors for the home structural attributes index for
the property may include, but are not limited to, the following:
old construction, conditions signaling poor maintenance of the
property, high property occupancy with inadequate ventilation, over
a damp crawlspace.
[0136] In one embodiment, the property score calculator unit 421
computes a home structural attributes index (HSAI) for a property
in accordance with equation (7) provided below:
HSAI=HSAI_Raw.times.HSAI_Amplification.times.HSAI_TotalBurden
(7).
[0137] In one embodiment, the property score calculator unit 421
computes HSAI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
a home structural attributes index. The property score calculator
unit 421 computes HSAI_Amplification based on weighted user
responses to questions selected from the collection 264 to identify
data points related to amplifications factors for a home structural
attributes index. The property score calculator unit 421 computes
the product of HSAI_Raw, HSAI_Amplification and HSAI_TotalBurden to
obtain HSAI.
[0138] In one embodiment, HSAI_Amplification is applied to obtain
HSAI only when three or more amplification factors are present.
[0139] Indoor Particle Index
[0140] An indoor particle index for a property represents a
combination of various possible sources of potential particulate
(e.g., dust) in an indoor environment of the property, irrespective
of other indexes. In one embodiment, the property score calculator
unit 421 determines an indoor particle index for a property by
analyzing property data for the property (e.g., a dataset 262
comprising property attributes for the property, user responses to
questions relating to the property, etc.) to identify data points
that indicate potential particulate presence in the property.
Examples of data points that indicate potential particulate
presence in the property may include, but are not limited to, the
following: (a) pet dander from furry pets (e.g., dogs, cats,
gerbils, hamsters), (b) human dander from high property occupancy,
(c) particulate accumulation due to hard to clean surfaces such as
wall to wall carpeting, unfinished beams or wall paneling,
horizontal display surfaces such as elevated structures, (d)
particulate accumulation due to forced air systems. Examples of
data points that indicate potential amplifications factors for the
indoor particle index for the property may include, but are not
limited to, the following: multiple furry pets, hard to clean
surfaces, and types of forced air systems.
[0141] In one embodiment, the property score calculator unit 421
computes an indoor particle index (IPI) for a property in
accordance with equation (8) provided below:
IPI=IPI_Raw.times.IPI_Amplification.times.IPI_TotalBurden (8).
[0142] In one embodiment, the property score calculator unit 421
computes IPI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an indoor particle index. The property score calculator unit 421
computes IPI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an indoor particle index. The
property score calculator unit 421 computes the product of IPI_Raw,
IPI_Amplification and IPI_TotalBurden to obtain IPI.
[0143] In one embodiment, IPI_Amplification is applied to obtain
IPI only when two or more amplification factors are present.
[0144] Indoor Dampness Index
[0145] An indoor dampness index for a property represents a
combination of various possible sources of dampness in an indoor
environment of the property, irrespective of the other indexes. In
one embodiment, the property score calculator unit 421 determines
an indoor dampness index for a property by analyzing different
datasets (e.g., a database 260 maintaining property attributes for
the property, user responses to questions, etc.) to identify data
points related to an indoor dampness index. The datasets may
include data identifying potential dampness presence in the
property. Examples of data points that relate to an indoor dampness
index may include, but are not limited to, the following: (a) roof
type and age, (b) plumbing type and age, (c) exterior cladding type
and age, with or without moisture barrier and insulation, (d)
basements, whether full, partial, sub-surface, garden-level, or
walk-out, (e) crawlspaces, whether installed moisture barrier on
open soil, or "rat" slab, (f) cold surfaces such as single pane
windows, insufficient insulation in exterior walls, (g) number of
bathroom showers, with or without bathroom exhaust fans, (h)
cooking behaviors with or without kitchen exhaust fans, (i) high
occupancy, excess production of exhaled vapor in human breath, and
(j) open-water features such as indoor swimming pools, hot tubs,
water fountains, steam rooms. Examples of data points that indicate
potential amplifications factors for the indoor dampness index for
the property may include, but are not limited to, the following:
old and damaged exteriors, damp crawlspaces, history of water
damage, and conditions signaling poor maintenance of the property.
If two or more are present, then a multiplier is applied to the
Index.
[0146] In one embodiment, the property score calculator unit 421
computes an indoor dampness index (IDI) for a property in
accordance with equation (9) provided below:
IDI=IDI_Raw.times.IDI_Amplification.times.IDI_TotalBurden (9).
[0147] In one embodiment, the property score calculator unit 421
computes IDI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an indoor dampness index. The property score calculator unit 421
computes IDI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an indoor dampness index. The
property score calculator unit 421 computes the product of IDI_Raw,
IDI_Amplification and IDI_TotalBurden to obtain IDI.
[0148] In one embodiment, IDI_Amplification is applied to obtain
IDI only when two or more amplification factors are present.
[0149] Outdoor Environmental Index
[0150] An outdoor environmental index for a property represents a
combination of various possible outdoor environmental features and
conditions, including influences such as climate, geography,
landscape, and other features outside of a building envelope of the
property, irrespective of the other indexes. In one embodiment, the
property score calculator unit 421 determines an outdoor
environmental index for a property by analyzing property data for
the property (e.g., a dataset 262 comprising property attributes
for the property, user responses to questions relating to the
property, etc.) to identify data points that indicate potential
climate features of the property. Examples of data points that
indicate potential climate features of the property may include,
but are not limited to, the following: (a) climate zone, such as
hot-humid, hot-dry, cold, frigid, moderate, or mixed--affecting
energy usage per degree day calculations, (b) geography, such as
desert, mountain, plains, coastal, forest, (c) locations such as
urban, suburbs, inner city, industrial, large housing lots, (d)
seasonality, for weather conditions and storms, plus pollen
production, and outdoor activities such as construction, lawn care,
farming activities, tourism, (e) area wind direction and patterns,
and (f) local features and structures such as tall buildings,
trees, and hills that provide extensive shading from the sun.
Examples of data points that indicate potential amplifications
factors for the outdoor environmental index for the property may
include, but are not limited to, the following: extremes of climate
and geography, shading of the sun, stormy weather.
[0151] In one embodiment, the property score calculator unit 421
computes an outdoor environmental index (OEI) for a property in
accordance with equation (10) provided below:
OEI=OEI_Raw.times.OEI_Amplification.times.OEI_TotalBurden (10).
[0152] In one embodiment, the property score calculator unit 421
computes OEI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an outdoor environmental index. The property score calculator unit
421 computes OEI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an outdoor environmental
index. The property score calculator unit 421 computes the product
of OEI_Raw, OEI_Amplification and OEI_TotalBurden to obtain
OEI.
[0153] In one embodiment, OEI_Amplification is applied to obtain
OEI only when three or more amplification factors are present.
[0154] Air Movement Index
[0155] An air movement index for a property represents a
combination of various possible sources, types, and intensities of
factors--both internal and external--creating various pressure
differentials across structures both outdoors and indoors. The air
movement index further represents a combination of various possible
sources of pathways for air from both outside to inside and to
circulate throughout the indoor environment. The air movement
index, unlike other indexes, is generated primarily by a
combination of features selected from other indexes for the
property.
[0156] In one embodiment, the property score calculator unit 421
determines the air movement index for the property by analyzing
property data for the property (e.g., a dataset 262 comprising
property attributes for the property, user responses to questions
relating to the property, etc.) to identify data points that
indicate potential pressure differentials and sources of pathways
for air for the property. Examples of data points that indicate
potential pressure differentials and sources of pathways for air
for the property may include, but are not limited to, the
following: (a) climate zone (e.g., hot-humid, hot-dry, cold,
frigid, moderate, mixed, etc.) affecting energy usage per degree
day calculations, (b) prevailing wind direction and strength, (c)
vapor pressure difference between inside and outside the structure,
(d) frequency of directional change of air pressures, (e) frequency
of directional change of vapor pressures, (f) leak rate of house
per blower door test at 50 Pascal, (g) operation of exhaust fans
inside the house in bathrooms, kitchens, hot tub rooms, laundry
rooms for clothes dryer exhaust, attic fans for house cooling, (h)
use of mechanical ventilation such as HRV or ERV, and (i) air
barriers on exterior assemblies combined with sufficient
insulation. Examples of amplifications factors for an air movement
index may include, but are not limited to, the following: frequent
vapor pressure changes, frequent increases in wind strength, a
leaky property. Examples of data points that indicate potential
amplifications factors for the air movement index for the property
may include, but are not limited to, the following: (a) routine
construction (e.g., if building envelope is not air tight, multiple
tiny openings may accumulate to several square feet total), (b)
chimneys, (c) crawlspaces not air sealed to rest of house, (d)
forced air systems and ducting located in attics or crawlspaces,
(e) combustion make-up air vent (code required for gas fired
appliances), (f) water heater exhaust vents, (g) furnace or boiler
exhaust vents, (h) cracks in basement floor, (i) dryer exhaust
vent, (j) stove hood vent, (k) access door to attic, (l) ceiling
penetrations into cavities or attics, (m) poor fitting windows and
doors, and (n) perimeter drainage pipes into sump pit.
[0157] In one embodiment, the property score calculator unit 421
computes an air movement index (AMI) for a property in accordance
with equation (11) provided below:
AMI=AMI_Raw.times.AMI_Amplification.times.AMI_TotalBurden (11).
[0158] In one embodiment, the property score calculator unit 421
computes AMI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an air movement index. The property score calculator unit 421
computes AMI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an air movement index. The
property score calculator unit 421 computes the product of AMI_Raw,
AMI_Amplification and AMI_TotalBurden to obtain AMI.
[0159] In one embodiment, AMI_Amplification is applied to obtain
AMI only when two or more amplification factors are present.
[0160] Indoor Cavity Index
[0161] An indoor cavity index for a property represents a
combination of various possible sources and types of interstitial
cavities in structural assemblies in indoor environment of the
property, irrespective of other indexes. In one embodiment, the
property score calculator unit 421 determines an indoor cavity
index for a property by analyzing property data for the property
(e.g., a dataset 262 comprising property attributes for the
property, user responses to questions relating to the property,
etc.) to identify data points that indicate potential cavities in
the property. Examples of data points that indicate potential
cavities in the property may include, but are not limited to, the
following: (a) large number of rooms for that particular house
size, (b) complex system of interior walls, (c) additions to the
main building, (d) partial attics, (e) partially finished
basements, (f) cathedral ceilings, (g) air ducting utilizing
"panned" returns in flooring, or located inside wall, floor, or
ceiling assemblies, and (h) total rooms. Examples of data points
that indicate potential amplifications factors for the indoor
cavity index for the property may include, but are not limited to,
the following: multiple additions, "panned" forced air returns, and
partial attics.
[0162] In one embodiment, the property score calculator unit 421
computes an indoor cavity index (ICAVI) for a property in
accordance with equation (12) provided below:
ICAVI=ICAVI_Raw.times.ICAVI_Amplification.times.ICAVI_TotalBurden
(12).
[0163] In one embodiment, the property score calculator unit 421
computes ICAVI_Raw based on weighted user responses to questions
selected from the collection 264 to identify data points related to
an indoor cavity index. The property score calculator unit 421
computes ICAVI_Amplification based on weighted user responses to
questions selected from the collection 264 to identify data points
related to amplifications factors for an indoor cavity index. The
property score calculator unit 421 computes the product of
ICAVI_Raw, ICAVI_Amplification and ICAVI_TotalBurden to obtain
ICAVI.
[0164] In one embodiment, ICAVI_Amplification is applied to obtain
ICAVI only when four or more amplification factors are present.
[0165] In one embodiment, the property score application 420
comprises a property analysis unit 429. In one example
implementation, the property analysis unit 429 functions as a
building architecture and materials recommendation engine for
providing recommendations, based in part on the database 900, on
how to build new properties that are customized to best address
local pollutants and sensitivities of a local population, thereby
reducing risk of liability for builders, developers, etc.
[0166] In another example implementation, the property analysis
unit 429 functions as a housing stock analysis tool for tracking
and assessing health index of multiple properties (e.g., housing
stock) owned, controlled and/or managed by governments, property
management groups, developers, builders, etc.
[0167] In another example implementation, the property analysis
unit 429 functions as a geographic region/multiple properties
analysis tool for determining potential health issues associated
with a particular geographical area.
[0168] In another example implementation, the property analysis
unit 429 functions as a property improvement retailor
recommendations tool for providing recommendations, based in part
on the database 900, on what building materials to sell, when to
sell the building materials, and who to sell the building materials
to, based on regional population health and health risks of a
property.
[0169] FIG. 6 illustrates an example process 600 for obtaining
information used in determining a property score for a property, in
accordance with an embodiment of the invention. In process block
601, obtain property data for a property from one or more data
sources. In one embodiment, the property data includes climate data
about environment around the property and public data about the
property and its construction (e.g., age of property, average
precipitation in the environment around the property, whether the
property is located in an urban area, last major construction of
the property, age of roof of the property).
[0170] In process block 602, select one or more proximity questions
based on the property data, present the selected proximity
questions, and obtain user responses to the selected proximity
questions. In one embodiment, the selected proximity questions are
selected from a question bank 265B (FIG. 3).
[0171] In process block 603, select one or more property attributes
questions based on the property data and prior user responses,
present the selected property attributes questions, and obtain user
responses to the selected property attributes questions. In one
embodiment, the selected property attributes questions are selected
from a question bank 265A (FIG. 3).
[0172] In process block 604, select one or more user behavioral
questions based on the property data and prior user responses,
present the selected user behavioral questions, and obtain user
responses to the selected user behavioral questions. In one
embodiment, the selected user behavioral questions are selected
from a question bank 265D (FIG. 3).
[0173] In process block 605, select one or more pet questions based
on the property data and prior user responses, present the selected
pet questions, and obtain user responses to the selected pet
questions. In one embodiment, the selected pet questions are
selected from a question bank 265C (FIG. 3).
[0174] The order of process blocks 602-605 may change; any one of
the process blocks may lead to any other one of the process
blocks.
[0175] FIG. 7 illustrates an example algorithm 425 applied by the
property score calculator unit 421 to determine a property score
for a property, in accordance with an embodiment of the invention.
The property score calculator unit 421 computes a property score
for a property based on different subsets of property attributes,
such as a first subset of property attributes determined from
climate data about environment around the property, a second subset
of property attributes determined from public data about the
property and its construction, a third subset of property
attributes determined from user responses to property attribute
questions selected from the question bank 265A, and a fourth subset
of property attributes determined from user responses to user
behavioral questions selected from the question bank 265D.
[0176] For each subset, one or more property attributes N of the
subset are assigned an amplification factor. The value of each
property attribute N may differ based on potential impact (i.e.,
severity) that the property attribute N has in influencing an
overall value of a parameter corresponding to a pollutant. A value
may be defined for each property attribute N, and the property
attribute N may be factored into the calculation of more than one
parameter (i.e., may be factored into the calculation of different
parameters for different pollutants). For example, for each
parameter (e.g., Parameter 1, Parameter 2, Parameter 3, Parameter
4), the value of each property attribute N factored into the
calculation of the parameter is summed. The overall value of each
parameter is then summated as a value V for the subset (e.g., V1
for the first subset, V2 for the second subset, V3 for the third
subset, V4 for the fourth subset), and the value V is applied an
amplification factor representing the potential impact (i.e.,
severity) of the subset on the health of a mean population
demographic. Furthermore, the overall value of each parameter may
be amplified on a pollutant basis such that the overall value of
any one parameter corresponding to a pollutant does not overly
influence the property score. Finally, each amplified value V is
summated, and the resulting sum represents the property score.
[0177] The number of parameters may be variable. For example, if
determining the potential impact of mold on the property, the
parameters utilized may include an air movement index and model
data for modeling/projecting the growth of mold. In one example
scenario, some property attributes for the property are used to
determine the air movement index and the model data for
modeling/projecting the growth of mold, which are then summated to
determine the potential impact of mold on the property. In this
example scenario, the property attributes are not factored directly
in the algorithm 425; the property attributes, instead, are used in
a subsystem that generates a result that is factored directly in
the algorithm 425.
[0178] FIG. 8 illustrates an example webpage 710, in accordance
with an embodiment of the invention. The webpage 710 prompts a user
accessing the webpage 710 via a user client device 299 for a
property address. In one embodiment, the webpage 710 includes a
first region 711 comprising an input field for receiving user
input. The user may directly enter a property address into the
input field.
[0179] In one embodiment, if the user client device 299 has
geo-location capabilities, the property address may be acquired
instead via latitudinal and longitudinal positions provided by the
user client device 299, without any user input.
[0180] FIG. 9 illustrates an example webpage 700 generated in
response to receiving a property address, in accordance with an
embodiment of the invention. In one embodiment, the webpage 700
includes a first region 702 that displays a property score for the
property address. The property score is determined using the
property score application 420. The webpage 700 further includes a
second region 701 displaying an image/photo of a property located
at the property address, and a third region 703 displaying a legend
identifying one or more property attributes for the property that
has negatively impacted or positively impacted the property
score.
[0181] The webpage 700 may further include a fourth region 704
identifying a projected accuracy rating for the property score. The
accuracy rating increases or decreases depending on the amount
and/or accuracy of data points available for the property address
(e.g., the amount and/or accuracy of property attributes acquired
from third-party data sources and/or a user responses). The fourth
region 704 may further display a selectable graphical user
interface (GUI) component that, when selected, provides a user with
an opportunity to increase the amount and/or accuracy of data
points available for the property address by manually entering
additional information, thereby refining the property score.
[0182] If the user selects the GUI component, the user is directed
to another webpage presenting questions selected from the
collection 264, wherein the questions presented prompt the user to
enter additional information. Additional property attributes for
the property are determined based on the additional information
entered, and the additional property attributes are stored in the
database 260 for the property. The score calculator unit 421
updates the property score based on the additional property
attributes determined.
[0183] The webpage 700 may include additional regions displaying
other information, such as the average estimated property score for
properties located in the same city as the property address,
information identifying common illnesses, information identifying
physical and/or geographic characteristics that negatively impact
human health, information identifying cities with properties having
the highest property scores, etc.
[0184] Personal Profile Application
[0185] In this specification, the term "personal profile" is used
to denote a profile for a user. A personal profile for a user may
include one or more of the following information relating to the
user: sensitivities of the user, specific triggers of the user,
thresholds of the user, and impacts of the user. The term "personal
profile score" represents a health index for a user with respect to
sensitivities of the user, specific triggers of the user,
thresholds of the user, and impacts of the user. A personal profile
score may be represented using a number grade, a percentage grade,
a letter grade, etc.
[0186] FIG. 10 illustrates an example personal profile application
430, in accordance with an embodiment of the invention. In one
embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
personal profile application 430. The personal profile application
430 comprises a personal profile score calculator unit 431
configured to create a personal profile for a user, and determine a
personal profile score for the user based on the personal profile
created.
[0187] The personal profile score calculator unit 431 may create a
personal profile for a user based on user input (e.g., user
responses to questions selected from the collection 264) and/or
health records for the user. A personal profile for a user may be
maintained in at least one database 260. In one embodiment, the
storage devices 220 (FIG. 1) maintains at least one database 260
including a collection 266 of personal profiles 267 for different
users.
[0188] In one embodiment, to create a personal profile for a user,
the user is presented with questions selected from the collection
264 (e.g., presented with 20 questions selected from a collection
of more than 100 questions) to obtain personal data of the user.
The selected questions may cycle through questions for determining
sensitivities of the user to biologicals, chemicals, particles, and
pets, respectively.
[0189] The personal profile application 430 comprises an adaptive
question selection unit 434 for adaptively selecting questions from
the collection 264 based in part on prior user input (e.g., prior
user responses to questions selected from the collection 264), if
any. If, at any point during the presentation of the selected
questions, user responses seem contradictory or mis-entered, the
adaptive question selection unit 434 runs a related education
module and then repeats or rephrases the selected questions.
Questions selected and presented to a user are dynamically selected
based on prior user interactions (e.g., prior user responses). For
example, if prior user responses to initial screening questions
indicate that pets are not an issue to a user but biologicals are,
the likelihood of questions relating to biologicals being
subsequently selected and presented to the user increases whereas
the likelihood of questions relating to pets being subsequently
selected and presented to the user decreased.
[0190] In one embodiment, the personal profile application 430
comprises a weightings unit 432. The weightings units 432
comprises, but is not limited to, the following: (a) different
weighting values for different attributes, factors or indexes, (b)
different prevalence values for different attributes, factors or
indexes, and (c) data representing interrelationships between
different attributes, factors or indexes.
[0191] In one embodiment, the personal profile application 430
comprises a personal profile report unit 433 for generating a
personal profile report that includes a personal profile for a user
and a personal profile score for the user. A personal profile
report may be presented to a user via a website 295.
[0192] In one embodiment, a personal profile for a user maintained
in the database 260 is updated when updated/additional information
relating to the user obtained.
[0193] In one embodiment, the personal profile score calculator
unit 431 is configured to create a group profile for a group of
multiple users by combining each personal profile for each user of
the group. There may be different types of groups comprising
multiple users. Examples of different types of groups comprising
multiple users may include, but are not limited to, the following:
a family group comprising multiple family members, a population
group comprising multiple members (e.g., a local population, etc.).
A group profile for a group of users may include one or more of the
following information relating to the group: sensitivities of the
group, specific triggers of the group, thresholds of the group, and
impacts of the group. In one example implementation, the personal
profile score calculator unit 431 adds up sensitivities of each
user the group, specific triggers of each user the group,
thresholds of each user the group, and impacts of each user the
group to determine sensitivities of the group, specific triggers of
the group, thresholds of the group, and impacts of the group,
respectively. The sensitivities of the group is determined such
that it reflects sensitivities of the most sensitive user of the
group.
[0194] In one embodiment, a personal profile report for a user
includes a personal action plan customized for the user. The
personal profile report unit 433 determines how compatibility
between a user and a property may be misaligned, and generates
personal action plan including remediation recommendations, wherein
the remediation recommendations suggest actions and/or
interventions for the user to take to remedy any potential
mis-match between the user and the property and improve
compatibility between the user and the property (i.e., improving a
property match score). The personal action plan may be based in
part on user feedback with respect to past actions taken and
results, expert judgment and other data correlations. The personal
action plan may also be based on user feedback with respect to
goals of the user, budget of the user and/or desired outcomes of
the user. For example, to elicit user feedback from the user with
respects to goals of the user, budget of the user and/or desired
outcomes of the user, the personal profile report unit 433 may
present questions selected from the collection 264 (e.g., personal
motivations and goals questions selected from the question bank
265E). User responses received in response to the questions
presented are used to further personalize/customize the personal
action plan for the user. A personal action plan may be presented
to a user via a website 295.
[0195] In one embodiment, the personal action plan comprises a
prioritized set of remediation recommendations, wherein the
remediation recommendations suggest a particular order of actions
and/or interventions for the user to take in order to yield maximum
benefit and compliance. The personal action plan may also include
actions to avoid and guidance on interpretation of results. The
remediation recommendations are prioritized based on data
correlations, such as correlations among property attributes used
in determining a property score, personal profiles, expert
judgment, survey results, and user feedback with respect to prior
remediation interventions and/or actions performed and
results/impact. Necessary remediation interventions and/or actions
may also be covered by existing guidance documents and/or
standards.
[0196] Table 2 below provides an example personal profile report
generated by the personal profile application 430.
TABLE-US-00002 TABLE 2 Personal Profile Your personal profile score
is 80. You have some significant sensitivities, but are overall
around average and share this score with an estimated 50% of the
U.S. population and about 40% of users of the Personal Profile
tool. You are highly sensitive to chemicals, which can easily cross
the threshold for triggering a response. These interruptions,
however, are at a nuisance level (2 out of 6 with 1 being no impact
and 6 being life threatening) and do not typically require
substantial lifestyle changes or cause significant harm. A few
example data points used in this determination are: Your
sensitivity to diesel fuel A dislike of the cleaning aisle A strong
response to air fresheners An assessment that you don't leave a
room with an air freshener Nail polish bothers you, but you go to
nail salons regularly Some specific chemicals that affect you are:
Alcohol based perfumes Petroleum products You are moderately
sensitive to particles. While particles don't easily cross the
threshold to trigger a response, when you have a response it is
rather strong. These interruptions, are at a 4 out of 6 (2 out of 6
with 1 being no impact and 6 being life threatening). A few example
data points used in this determination are: Sensitivity to
cigarette smoke Comfort around 2-3 dogs, but inability to go into
pet stores Seasonal allergies that are non-existent most of the
year, but severe a few times a year Comfort with cleaning and
vacuuming for all rooms except the attic, which you avoid Allergies
to cats that prevent you from visiting friends with cats at their
properties, though meeting outside it fine Some specific particles
that affect you are: Cat dander Pollen You have a low sensitivity
to biologicals. You have a relatively high trigger point and are
not substantially bothered by biologicals. These interruptions, are
at a nuisance level (2 out of 6 with 1 being no impact and 6 being
life threatening). A few example data points used in this
determination are: The dampness of your current living environment
Your lack of sinus infections during past stays in musty properties
and dorms Your love of antiques, old carpets and upholstery
Personal Action Plan We recommend keeping windows closed during
peak allergy seasons. 30% of people with personal profiles like
yours report significant improvements in how they feel after
implementing this strategy. Use only low toxic cleaning materials
and air out the house while doing so with open windows. 50% of
people with personal profiles like yours report significant
improvements in how they feel after implementing this strategy.
[0197] In one embodiment, after a personal action plan is presented
to a user for review, the personal profile report unit 433 is
configured to refine/adjust the personal action plan based on user
feedback. For example, to elicit user feedback from the user, the
personal profile report unit 433 may present questions selected
from the collection 264 (e.g., feedback and assessment questions
selected from the question bank 265L, or other questions such as
"Which of the suggested interventions would you like to do first?"
or "What deadline do you want to give yourself for this action?").
User responses received in response to the questions presented are
used to refine/adjust the personal action plan for the user.
[0198] In this specification, the term "trigger" is used to
represent a substance/item, without any assigned weighting, that
has a perceived impact on an individual (i.e., how the individual
reacts to the substance). Examples of triggering items may include
nail polish, pet dander, or petroleum products.
[0199] A threshold for a trigger denotes how much of a trigger must
be present to elicit a response from a user.
[0200] An impact rating for a trigger denotes severity of a
response an individual will exhibit when a threshold for the
trigger is crossed.
[0201] The personal profile score calculator unit 431 is configured
to collect different reported triggers from a user, and determine
the influence of each reported trigger on a personal profile score
based on a corresponding weighting value and a corresponding
prevalence value.
[0202] In one embodiment, the personal profile application 430
determines a health sensitivity data (e.g., pattern relating to a
sensitivity) from personal data associated with a user. The
personal profile application 430 determines a potential impact data
(e.g., pattern relating to personal impact) that a pollutant data
(e.g., pattern relating to a pollutant) may have on health of the
user based in part on the health sensitivity data, and generates a
personal profile for the user, wherein the personal profile
comprises a personal profile score representing health
sensitivities of the user to pollutants based in part on the
potential impact data.
[0203] In one embodiment, the personal profile score calculator
unit 431 determines a personal profile score for a user based on
the following factors/indexes: specific triggers (i.e.,
biologicals, chemicals, particles and pets), prevalence and
thresholds for the specific triggers, impact rating of the specific
triggers, and total burden. A selection of top triggers
corresponding may be included in a personal profile report
generated for a user.
[0204] Table 3 provided below comprises a listing identifying
different parameters referenced in this specification.
TABLE-US-00003 TABLE 3 Abbreviation Definition
PersonalProfile_Score Personal profile score BiologicalSensitivity
Raw score for biologicals trigger BiologicalThresholds_Sum Sum of
thresholds for biologicals trigger
BiologicalThresholds_Amplification Thresholds amplification factors
for biologicals trigger BiologicalImpactRatings Impact ratings for
biologicals trigger BiologicalImpactRatings_Amplification Impact
ratings amplification factors for biologicals trigger
MoldSensitivity Raw score for mold trigger MoldThresholds_Sum Sum
of thresholds for mold trigger MoldThresholds_Amplification
Thresholds amplification factors for mold trigger MoldImpactRatings
Impact ratings for mold trigger MoldImpactRatings_Amplification
Impact ratings amplification factors for mold trigger
ChemicalSensitivity Raw score for chemicals trigger
ChemicalThresholds_Sum Sum of thresholds for chemicals trigger
ChemicalThresholds_Amplification Thresholds amplification factors
for chemicals trigger ChemicalImpactRatings Impact ratings for
chemicals trigger ChemicalImpactRatings_Amplification Impact
ratings amplification factors for chemicals trigger
ParticleSensitivity Raw score for particles trigger
ParticleThresholds_Sum Sum of thresholds for particles trigger
ParticleThresholds_Amplification Thresholds amplification factors
for particles trigger ParticleImpactRatings Impact ratings for
particles trigger ParticleImpactRatings_Amplification Impact
ratings amplification factors for particles trigger PetSensitivity
Raw score for pets trigger PetThresholds_Sum Sum of thresholds for
pets trigger PetThresholds_Amplification Thresholds amplification
factors for pets trigger PetImpactRatings Impact ratings for pets
trigger PetImpactRatings_Amplification Impact ratings amplification
factors for pets trigger Trigger_Raw Raw score for trigger
TriggeringItem Indication (Yes/No) of whether a user reacts to a
particular triggering item for a trigger
TriggeringItem_Amplification Amplification factors for a particular
triggering item for a trigger ThresholdAmplificationFactors
Threshold amplification factors for trigger
ThresholdDeterminationRatings Threshold determination ratings for
trigger ImpactRatings Impact ratings for trigger MaskingEffects
Masking effects UserBehavioralClues User behavioral clues
UserBehavioralClues_Amplification Amplification factors for user
behavioral clues ImpactRatings_Amplification Impact ratings
amplification factors
[0205] In one embodiment, the personal profile score calculator
unit 431 computes PersonalProfile_Score in accordance with the
equation (13) provided below:
PersonalProfile_Score=BiologicalSensitivity+MoldSensitivity+ChemicalSens-
itivity+ParticleSensitivity+PetSensitivity (13).
[0206] In one embodiment, the personal profile score calculator
unit 431 computes BiologicalSensitivity in accordance with the
equation (14) provided below:
BiologicalSensitivity=BiologicalThresholds_Sum.times.BiologicalThreshold-
s_Amplification.times.BiologicalImpactRatings.times.BiologicalImpactRating-
s_Amplification (14).
[0207] In one embodiment, the personal profile score calculator
unit 431 computes MoldSensitivity in accordance with the equation
(15) provided below:
MoldSensitivity=MoldThresholds_Sum.times.MoldThresholds_Amplification.ti-
mes.MoldImpactRatings.times.MoldImpactRatings_Amplification
(15).
[0208] In one embodiment, the personal profile score calculator
unit 431 computes ChemicalSensitivity in accordance with the
equation (16) provided below:
ChemicalSensitivity=ChemicalThresholds_Sum.times.ChemicalThresholds_Ampl-
ification.times.ChemicalImpactRatings.times.ChemicalImpactRatings_Amplific-
ation (16).
[0209] In one embodiment, the personal profile score calculator
unit 431 computes ParticleSensitivity in accordance with the
equation (17) provided below:
ParticleSensitivity=ParticleThresholds_Sum.times.ParticleThresholds_Ampl-
ification.times.ParticleImpactRatings.times.ParticleImpactRatings_Amplific-
ation (17).
[0210] In one embodiment, the personal profile score calculator
unit 431 computes PetSensitivity in accordance with the equation
(18) provided below:
PetSensitivity=PetThresholds_Sum.times.PetThresholds_Amplification.times-
.PetImpactRatings.times.PetImpactRatings_Amplification (18).
[0211] For each trigger, the personal profile score calculator unit
431 computes Trigger_Raw in accordance with equation (19) provided
below:
Trigger_Raw=(TriggeringItem.times.TriggeringItem_Amplification.times.Thr-
esholdAmplificationFactors.times.ThresholdDeterminationRatings).times.(Imp-
actRatings.times.MaskingEffects+UserBehavioralClues.times.UserBehavioralCl-
ues_Amplification.times.ImpactRatings_Amplification)(19).
[0212] If a raw score computed for a trigger is greater than a
display threshold assigned to the trigger, then the trigger is
included in a property match report or a personal action plan
generated for the user.
[0213] A display threshold assigned to a trigger represents degree
of importance of including the trigger in a property match report
or personal action plan generated for the user. In one embodiment,
a display threshold may be assigned one of the following degrees of
importance--"high", "medium" or "low". The degree of importance
assigned may be based on amount of points accumulated based on
weighted data inputs and weighted data correlations. In one example
implementation, a "low" degree of importance is assigned to the
threshold if the amount of points accumulated is less than 200
points, a "medium" degree of importance is assigned to the
threshold if the amount of points accumulated is between 200 and
400 points, and a "high" degree of importance is assigned to the
threshold if the amount of points accumulated is more than 400
points.
[0214] In one embodiment, an impact rating assigned to a trigger is
a ranking that reflects degree of impact the trigger has on a user.
In one example implementation, an impact rating assigned to a
trigger is a ranking in the range of "1" to "6". For example, a
ranking of "1" reflects that the trigger has no impact on the user,
a ranking of "2" reflects that the trigger is merely a nuisance and
any impact of the trigger on the user is insufficient to trigger an
action to alleviate the impact, a ranking of "3" reflects that any
impact of the trigger on the user is sufficient to trigger an
action to alleviate the impact, a ranking of "4" reflects that any
impact of the trigger on the user is pervasive, complex, and life
altering, a ranking of "5" reflects that any impact of the trigger
on the user is disabling, and a ranking of "6" reflects that any
impact of the trigger on the user is nearly non-functioning or life
threatening.
[0215] The ranking assigned may be based on amount of impact points
accumulated based on weighted data inputs and weighted data
correlations. For example, a ranking of "1" is assigned if the
amount of points accumulated is in the range 1-100, a ranking of
"2" is assigned if the amount of points accumulated is in the range
101-200, a ranking of "3" is assigned if the amount of points
accumulated is in the range 201-300, a ranking of "4" is assigned
if the amount of points accumulated is in the range 301-400, a
ranking of "5" is assigned if the amount of points accumulated is
in the range 401-500, and a ranking of "6" is assigned if the
amount of points accumulated is in the range 501-600.
[0216] A threshold amplification factor is a weighted multiplier. A
threshold amplification factor lowers a triggering threshold for
triggering an item (i.e., makes the triggering item more potent).
For example, dusts issues are amplified if the user has a dust
allergy and the property has hard to clean places and forced
air.
[0217] A threshold determination rating is a weighted assessment of
how easily an individual is affected by a specific trigger. The
personal profile score calculator unit 431 computes a threshold
determination rating for a trigger based on user responses to
questions selected from the collection 264 (e.g., threshold
questions from the question bank 265G).
[0218] For example, to determine a threshold determination rating
for dust, the questions selected may include the following: "Do you
sneeze when you dust or vacuum?", "Do you sneeze when the forced
air turns on?", and "Do you sneeze when vacuuming or dusting and
the forced air turns on?". The threshold determination rating for
dust is based on user responses to the questions selected (e.g.,
the user responses may indicate that the user can handle dust
without reaction). The threshold determination rating for dust is
multiplied by a corresponding weighting to determine the threshold
for response of the user to dust. Weightings are created by machine
learning algorithm over time.
[0219] A personal impact rating for a trigger is an assessment on a
sliding scale by a user about how much a triggering item for the
trigger impacts the user.
[0220] A user behavioral clue is an indicator of potential user
reactivity. User behavioral clues are determined from user
responses to questions selected from the collection 264 (e.g., user
behavioral questions selected from the question bank 265D).
[0221] An impact amplification factor is a weighted multiplier. An
impact amplification factor increases severity of impact of a
trigger. For example, impact amplification factors such as
upholstery, carpeting and a high suck rate may increase severity of
impact of chemicals.
[0222] A masking effect for a trigger reduces a user's perception
of the impact that the trigger has on the user. For example,
smoking, drinking alcohol, or drinking coffee regularly may impact
how a user perceives his/her response to pets, mold, and chemicals.
Masking effects are determined from user responses to questions
selected from the collection 264 (e.g., masking questions selected
from the question bank 265J).
[0223] A total burden factor is a calculation about how overall
sensitivity may make specific sensitivities worse. Sensitivity
levels, when appearing in certain combinations, are correlated to
significantly higher lower thresholds and/or to specific triggering
items and significantly higher impacts on individuals. When a total
burden, as calculated from specific trigger scores tips into a high
level, the personal profile score calculator unit 431 will adjust
and lower thresholds and raise impact scores accordingly based on
data and previously discovered correlations from machine learning
about how this total level of burden and the components correlates
with thresholds and impacts.
[0224] In one example use case, assume that user responses to
questions indicate the following: (1) nail polish and diesel are
specific triggers for the user, (2) the user attempts to avoid each
specific trigger with a personal impact score of 3, and (3) the
property of interest to the user has materials such as carpeting
and retail chemicals. Table 4 below provides example pseudo code
for determining a raw score for the chemical trigger based on
triggering item nail polish.
TABLE-US-00004 TABLE 4 raw score for nail polish = [triggering item
(yes/no) (i.e., Nail polish YES) .times. triggering item
amplification factors (i.e., amplification factors for nail polish
based on data correlations among a general population, average
population response to nail polish, and severity of the average
population response) .times. threshold amplification factors (i.e.,
weighted amplification indicators such as diesel fuel and
carpeting) .times. threshold determination rating] .times.
[personal impact rating (i.e., 3) + masking effects + behavioral
clues .times. behavioral clues amplification factors .times. impact
ratings amplification factors (i.e., weighted impact of affirmative
user behavioral indicators that confirm or challenge the personal
impact rating, such as the user indicating that he/she avoids nail
salons and can't be in the same room with someone putting on nail
polish)]
[0225] As another example, Table 5 below provides example pseudo
code for determining a raw score for the chemical trigger based on
different triggering items.
TABLE-US-00005 TABLE 5 raw score for different chemical triggers =
[Triggering item (yes/no) .times. triggering item amplification
factors (e.g., New clothes YES .times. amplification factors
Fragrance YES .times. amplification factors Paint YES .times.
amplification factors) .times. threshold amplification factors
(e.g., new house, plug in deodorizers, scented detergent) .times.
threshold determination rating (e.g., user indicates ratings of
4/6, 2/6, 4/6 in response to questions such as "How much of an
issue are these three triggering items?"; also, user responses to
questions relating to environment, behavior and reactivity such as
"Do you use perfume or scented laundry detergent?", "Do you
frequently buy new clothes?", "Have you recently remodeled or
repainted?")] .times. [personal impact rating (e.g., user indicates
rating of 4/6 in response to questions such as "What's it like
being near these chemicals? How much does it influence you?") +
masking effects (e.g., user indicates that he/she does not consume
coffee or alcohol) + user behavioral clues (e.g., user indicates
that he/she avoids hardware stores and paint aisles) .times. user
behavioral clues amplification factors .times. impact ratings
amplification factors (e.g., user indicates property is near a
freeway and the property has had recent water leaks)]
[0226] As another example, Table 6 below provides example pseudo
code for determining a raw score for the biological trigger based
on different triggering items.
TABLE-US-00006 TABLE 6 raw score for different biological triggers
= [Triggering item (yes/no) .times. triggering item amplification
factors (e.g., Old musty buildings YES .times. amplification
factors Antiques YES .times. amplification factors Old books YES
.times. amplification factors) .times. threshold amplification
factors (e.g., property score estimates high mold risk index)
.times. threshold determination rating (e.g., user indicates
ratings of 3/6, 4/6 in response to questions such as "How much of
an issue are these three triggering items?"; also, user responses
to questions relating to environment, behavior and reactivity that
indicate the user avoids the basement and feels when he/she leaves
the property)] .times. [personal impact rating (e.g., user
indicates rating of 2/6 in response to questions such as "What's it
like being near mold? How much does it influence you?") + masking
effects (e.g., user indicates that he/she consumes a lot of alcohol
and smokes) + user behavioral clues .times. user behavioral clues
amplification factors .times. impact ratings amplification
factors]
[0227] Table 7 below provides example questions and user responses
used in determining thresholds and impacts for the particles
trigger.
TABLE-US-00007 TABLE 7 Examples of initial screening questions What
is it like around: Seasonal changes Dust Outdoor windy days
Examples of user responses to user behavioral questions and
sensitivity questions that contribute to threshold determinations I
react to following situations: Forced air turns on Run vacuum When
I dust When I open the windows When I was in a previous property
(or at other times in my history e.g., college dorm) Examples of
user responses to property attributes questions, user behavioral
questions, proximity questions and sensitivity questions that
contribute to amplifiers (impact and threshold) I have forced air
My family has stuffed animals I have carpeting I have upholstery I
keep all my windows open I live near agriculture I live near
construction I live near a freeway
[0228] Table 8 below provides example questions and user responses
used in determining thresholds and impacts for the pets
trigger.
TABLE-US-00008 TABLE 8 Examples of initial screening questions What
is it like around pets and animals? Have I ever had rodents or
insects in the house? What was that like? Examples of pet questions
that contribute to threshold determinations How many pets do I
have? Do I respond to the pet dander on someone else's clothes when
no pets are around? Do I respond to pet dander on a spouse that
only interacts with pets outside the house? Do I keep pets outside
of the house? Why? Examples of indicators in user responses to
property attributes questions, user behavioral questions, proximity
questions and sensitivity questions that contribute to amplifiers
(impact and threshold) Forced air Carpet Vacuum Upholstery Have
pets Basement or crawlspace
[0229] Table 9 below provides example questions and user responses
used in determining thresholds and impacts for the biologicals
trigger.
TABLE-US-00009 TABLE 9 Examples of initial screening questions
What's it like around: old books, musty houses? What's it like
around damp leaves? What's it like around old carpet? What's it
like around mold? Examples of indicators in user responses to
property attributes questions, user behavioral questions, proximity
questions and sensitivity questions that contribute to amplifiers
(impact and threshold) Moisture and dampness Wetting and drying
cycles in living environment Upholstered furniture
[0230] In one embodiment, the personal profile application 430
comprises a career match calculator unit 446 configured to
determine a career match score representing compatibility between a
user and a profession of interest to the user based on a personal
profile of the user and information identifying working conditions
associated with the profession (e.g., potential exposures
associated with a working environment that an individual working in
the profession may face). The information identifying working
conditions associated with the profession may be acquired from
third-party data sources 120 and/or user feedback.
[0231] Typically, 25% of employees consciously or unconsciously opt
out of a profession they have been working at for a period of time
because they do not feel good in their working environment or do
not feel motivated. For example, an individual who is chemically
sensitive may find working in an environment with high exposure to
chemicals unpleasant and may pursue another career. As another
example, an individual who works as a painter may succumb to
alcoholism as a coping mechanism to illnesses caused from exposure
to chemicals while working as a painter. The career match
calculator unit 446 provides a tool that allows a user to gauge
their compatibility with a particular profession. The higher the
compatibility between a user and a profession of interest, the
higher the likelihood of the user will feel satisfied, healthy and
motivated in the profession.
[0232] In one embodiment, the personal profile application 430
comprises a career match report unit 448 configured to generate a
career match report for a user based in part on a personal profile
for the user and feedback with respect to professions from other
users with similar personal profiles. The career match report may
include a suggested list of professions for the user to avoid in
view of sensitivities of the user. The career match report may also
include a suggested list of professions for the user to pursue. A
career match report may be presented to a user via a website
295.
[0233] In one embodiment, the career match calculator unit 446 is
configured to determine a career match score representing
compatibility between a user and a property address at which a
working environment for a profession of interest to the user is
located based on a personal profile of the user and property data
for the property address.
[0234] Table 10 below provides an example career match report
generated by the personal profile application 430.
TABLE-US-00010 TABLE 10 Your sensitivity profile is X and your
personal impact is Y for Chemicals. People with similar personal
profiles generally tend to avoid the following professions and
exposures: [suggested list of professions and exposures to avoid].
They are typically successfully employed in these professions:
[suggested list of professions to pursue]
[0235] In one embodiment, the personal profile application 430
comprises a profile analysis unit 447. In one example
implementation, the profile analysis unit 447 functions as a
population profile tool for generating, based in part on group
profiles created for specific populations, population-level
sensitivity analysis reports for the specific populations. The
population-level sensitivity analysis reports may be used by
politicians, government agencies, companies and other entities to
seek insight into the specific populations.
[0236] In one example implementation, the profile analysis unit 447
functions as a liability analyzer tool for assessing, based in part
on group profiles created for specific populations, likelihood that
minor, but common, health issues within the specific populations
are caused by industry, such as oil spills, chemical leaks,
etc.
[0237] In one example implementation, the profile analysis unit 447
functions as an academic outcomes prediction and advice engine for
correlating, based in part on group profiles created for regional
populations, regional property attributes with regional student
performance and suggesting changes to improve academic
performance.
[0238] In one example implementation, the profile analysis unit 447
functions as a life insurance calculator tool for predicting, based
in part on longitudinal data and group profiles created for
regional populations, how regional and individual home and health
correlations impact life expectancy at the population level.
[0239] In one example implementation, the profile analysis unit 447
functions as a relocation recommendation engine for providing,
based in part on regional conditions and a personal/group profile,
a hyper-local relocation suitability recommendation that suggests
targeted regions for relocation
[0240] FIG. 11 illustrates an example process 610 for obtaining
information used in creating a personal profile for a user, in
accordance with an embodiment of the invention. In process block
611, select one or more personal motivations and goals questions,
present the selected personal motivations and goals questions, and
obtain user responses to the selected personal motivations and
goals questions. In one embodiment, the selected personal
motivations and goals questions are selected from a question bank
265E (FIG. 4).
[0241] In process block 612, select one or more initial screening
questions, present the selected initial screening questions, and
obtain user responses to the selected initial screening questions.
In one embodiment, the selected initial screening questions are
selected from a question bank 265F (FIG. 4).
[0242] In process block 613, select one or more threshold
questions, present the selected threshold questions, and obtain
user responses to the selected threshold questions. In one
embodiment, the selected threshold questions are selected from a
question bank 265G (FIG. 4).
[0243] In process block 614, select one or more sensitivity
questions, present the selected sensitivity questions, and obtain
user responses to the selected sensitivity questions. In one
embodiment, the selected sensitivity questions are selected from a
question bank 265H (FIG. 4).
[0244] In process block 615, select one or more symptoms questions,
present the selected symptoms questions, and obtain user responses
to the selected symptoms questions. In one embodiment, the selected
symptoms questions are selected from a question bank 265I (FIG.
4).
[0245] In process block 616, select one or more user behavioral
questions, present the selected user behavioral questions, and
obtain user responses to the selected user behavioral questions. In
one embodiment, the selected user behavioral questions are selected
from a question bank 265D (FIG. 3).
[0246] In process block 617, select one or more personal impact
questions, present the selected personal impact questions, and
obtain user responses to the selected personal impact questions. In
one embodiment, the selected personal impact questions are selected
from a question bank 265K (FIG. 4).
[0247] In process block 618, select one or more masking questions,
present the selected masking questions, and obtain user responses
to the selected masking questions. In one embodiment, the selected
masking questions are selected from a question bank 265J (FIG.
4).
[0248] The order of process blocks 611-618 may change; any one of
the process blocks may lead to any other one of the process blocks
(e.g., process block 612 may lead directly to process block 616
which in turn leads directly to process block 615).
[0249] Property Match Application
[0250] In this specification, the term "property match score" is
used to denote a grade (e.g., a number grade, a percentage grade, a
letter grade) representing compatibility between a property and a
user/group of users. A property match score for a property of
interest to a user represents compatibility between the property
and the user for healthy living.
[0251] FIG. 12 illustrates an example property match application
440, in accordance with an embodiment of the invention. In one
embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
property match application 440. The property match application 440
comprises a property match calculator unit 441 configured to
determine a property match score for a property of interest to a
user based on a personal profile of the user and one or more
property attributes maintained in a database 260 for the property.
The property match calculator unit 441 combines data from one or
more personal profiles for one or more users associated with the
property with property data for the property to calculate potential
health impact correlations.
[0252] In one embodiment, the property match calculator unit 441
determines compatibility between a property and a user by
evaluating a personal profile for the user against property data
for the property. As described in detail later herein, the property
match calculator unit 441 may look for specific triggers of the
user, specific exposures of the user and property attributes (e.g.,
potential exposures associated with the property, such as mold risk
index, pet factor, etc.) used in determining a property score for
the property. For example, for a property with a high mold risk
index, the property will have a substantially lower property match
score with respect to a user who has a high sensitivity to
biologicals compared to another user with minimal/no sensitivities
to biologicals. As another example, for a property with a high pet
factor, the property will have a substantially higher property
match score with respect to a user who has minimal/no sensitivities
to pets compared to another user with a high sensitivity to
pets.
[0253] In one embodiment, the property match application 440
comprises an adaptive question selection unit 445 for adaptively
selecting questions from the collection 264 based on prior user
responses to previously presented questions and/or property data
for a property associated with the user. If, at any point during
the presentation of questions, user responses seem contradictory or
mis-entered, the adaptive question selection unit 445 runs a
related education module and then repeats or rephrases the target
questions. Questions selected and presented to a user are
dynamically selected based on prior user interactions (e.g., prior
user responses). For example, if prior user responses to initial
screening questions indicate that pets are not an issue to a user
but biologicals are, the likelihood of biological questions being
subsequently selected and presented to the user increases whereas
the likelihood of pet questions being subsequently selected and
presented to the user decreased.
[0254] In one embodiment, the property match application 440
comprises a weightings unit 442. The weightings units 442
comprises, but is not limited to, the following: (a) different
weighting values for different attributes, factors or indexes, (b)
different prevalence values for different attributes, factors or
indexes, and (c) data representing interrelationships between
different attributes, factors or indexes.
[0255] In one embodiment, the property match application 440
comprises a property match report unit 447 for generating a
property match report that includes a property match score for a
property of interest to a user. The property match report may
include one or more suggested improvements to the property to
increase compatibility between the property and the user. The
improvements, when undertaken, may help improve the property match
score. The property match report may also provide estimated costs
associated with the improvements. The estimated costs may be based
on contractor fees, fees for past improvement projects, expert
judgment, user feedback and other data sources. A property match
report may be presented to a user via a website 295.
[0256] Table 11 below provides an example property match report
generated by the property match application 440.
TABLE-US-00011 TABLE 11 70% of properties like this one typically
have poor indoor air quality, which results in negative impact on
occupant health. Based on your Match analysis this property will be
a grade C match. Stucco Walls in this climate with signs of
landscaping sprinklers hitting the wall on the shaded side of the
house have high risk of biological growth inside the wall cavities.
Typical cost to repair this kind of problem ranges from
$3,000-$20,000. The priority level of this change for someone like
you is MEDIUM This property was built in 1938. The paint around the
windows appears to be original. It is highly likely to contain lead
paint. Remediation or encapsulation needs to be done. Typical cost
in your area is $1,000-$3,000. The priority level of this change
for someone like you is HIGH Properties with basements in this
climate negatively impact occupant health 50% of the time. This
basement shows signs of moisture intrusion in photo #3. That
increases likelihood to 80%. Typical costs to remediate and repair
range from $3,000 to $15,000 in your area. The priority level of
this change for someone like you is LOW Cat is living in the house.
You indicated you are sensitive to cats. Effective remediation
would require painting to encapsulate existing dander on the wall,
removal of the carpet, and cleaning the duct work to reduce risk of
impact on you. Typical cost in your area is $3,000-5,000. The
priority level of this change for someone like you is HIGH Property
is near a freeway and concentrates chemicals and fumes from
outside. Substantive, but not complete remediation would require
[insert requirement here]. The priority level of this change for
someone like you is HIGH. Projected cost to improve house to a
grade C+ match (high priority items) is around $16,000 Projected
cost to improve house to a grade B match (High and medium priority
improvements) is $26,000 Projected cost to improve house to a grade
B+ match (High, medium and low priority improvements) is $35,000
Grade A and A+ matches are not possible given the properties
history and location. Consider the creating a property match score
for others who will live in the dwelling. While the Match grade of
the property is improvement by your lack of sensitivity to
biological agents, this property would be a very poor match for
someone sensitive to biological such as mold. 30% of people with a
property match score of C+ report being satisfied with the air
quality in their property 50% of people with a property match score
of B report being satisfied with the air quality in their property
65% of people with a property match score of B+ report being
satisfied with the air quality in their property 80% of people with
a property match score of A report being satisfied with the air
quality in their property 95% of people with a property match score
of A+ report being satisfied with the air quality in their
property
[0257] In one embodiment, the property match calculator unit 441 is
configured to determine a property match score for a property of
interest to a group of multiple users (i.e., a collective group)
based on a group profile of the group and one or more property
attributes maintained in a database 260 for the property. As
described above, a group profile for a group of multiple users
combines personal profiles of each user of the group. A property
match score for a property of interest to a group of multiple users
represents compatibility between the property and the group for
healthy living.
[0258] For example, the property match calculator unit 441 may
determine a property match score representing compatibility between
a family and a property by evaluating each personal profile of each
family member of the family against property data for the
property.
[0259] In one embodiment, the property match application 440
extracts/determines a property attribute data (e.g., pattern
relating to a property attribute) from property data associated
with a property area. The property match application 440 combines
the property attribute data with at least one other property
attribute data to determine presence or movement of a pollutant
data (e.g., pattern relating to a pollutant) within the property
area. The property match application 440 determines a health
sensitivity data (e.g., pattern relating to a sensitivity) from
personal data associated with a user. The property match
application 440 determines a potential impact data (e.g., pattern
relating to personal impact) that the pollutant data may have on
health of the user based in part on the health sensitivity data and
the combination, and computes a property match score representing
compatibility of the property area with the health of the user
based in part on the first potential impact data.
[0260] In one embodiment, the property match calculator unit 441
determines a property match score based on the following factors:
biological match, chemical match, particle match, pet match, total
burden and corresponding weighting.
[0261] A weighting for a total burden is dynamically determined by
based on current total burden of a user and increased/decreased
stress that the property would put on health of the user.
[0262] Table 12 provided below comprises a listing identifying
different parameters referenced in this specification.
TABLE-US-00012 TABLE 12 Abbreviation Definition PropertyMatch_Score
Property match score BiologicalMatch Match score for biologicals
MoldMatch Match score for mold ChemicalMatch Match score for
chemicals ParticleMatch Match score for particles PetMatch Match
score for pets TotalBurden Total burden TotalBurden_Amplification
Amplification factors for total burden
[0263] In one embodiment, the property match calculator unit 441
computes PropertyMatch_Score in accordance with the equation (20)
provided below:
PropertyMatch_Score=[BiologicalMatch+MoldMatch+ChemicalMatch+ParticleMat-
ch+PetMatch].times.TotalBurden.times.TotalBurden_Amplification
(20).
[0264] In one embodiment, a PropertyMatch_Score is a raw score that
is converted to a number grade, a percentage grade, a letter grade,
etc. The higher a PropertyMatch_Score computed for a property of
interest to a user, the smaller the degree of compatibility between
the property and the user (i.e., the property is unsuitable for the
user).
[0265] In one embodiment, the property match calculator unit 441
computes BiologicalMatch in accordance with the equation (21)
provided below:
BiologicalMatch=BiologicalSensitivity.times.IBAI (21).
[0266] In one embodiment, the property match calculator unit 441
computes MoldMatch in accordance with the equation (22) provided
below:
MoldMatch=MoldSensitivity.times.IMI (22).
[0267] In one embodiment, the property match calculator unit 441
computes ChemicalMatch in accordance with the equation (23)
provided below:
ChemicalMatch=ChemicalSensitivity.times.ICI (23).
[0268] In one embodiment, the property match calculator unit 441
computes ParticleMatch in accordance with the equation (24)
provided below:
ParticleMatch=ParticleSensitivity.times.IPI.times.IPETI (24).
[0269] In one embodiment, the property match calculator unit 441
computes PetMatch in accordance with the equation (25) provided
below:
PetMatch=PetSensitivity.times.IPETI (25).
[0270] In one embodiment, the property match application 440
comprises a property analysis unit 449. In one example
implementation, the property analysis unit 449 functions as a
geographic region/multiple properties analysis tool for determining
potential health issues associated with a particular geographical
area.
[0271] In another example implementation, the property analysis
unit 449 functions as a property default risk calculator tool for
predicting, based in part on group profiles for regional
populations, regional and individual risks of property default,
based on property, banking and mortgage data. If a property match
score indicates that a property of interest to a user is compatible
with the user, a bank is more likely to provide a loan to the user
for use in purchasing the property.
[0272] FIG. 13 illustrates an example process 620 for obtaining
information used in determining a property match score, in
accordance with an embodiment of the invention. In process block
621, select one or more initial screening questions, present the
selected initial screening questions, and obtain user responses to
the selected initial screening questions. In one embodiment, the
selected initial screening questions are selected from a question
bank 265F (FIG. 4).
[0273] In process block 622, select one or more sensitivity
questions, present the selected sensitivity questions, and obtain
user responses to the selected sensitivity questions. In one
embodiment, the selected sensitivity questions are selected from a
question bank 265H (FIG. 4).
[0274] In process block 623, select one or more user behavioral
questions, present the selected user behavioral questions, and
obtain user responses to the selected user behavioral questions. In
one embodiment, the selected user behavioral questions are selected
from a question bank 265D (FIG. 3).
[0275] In process block 624, select one or more personal impact
questions, present the selected personal impact questions, and
obtain user responses to the selected personal impact questions. In
one embodiment, the selected personal impact questions are selected
from a question bank 265K (FIG. 4).
[0276] The order of process blocks 621-624 may change; any one of
the process blocks may lead to any other one of the process
blocks.
[0277] FIG. 14 illustrates an example algorithm 443 applied by the
property match calculator unit 441 to determine a property match
score, in accordance with an embodiment of the invention. The
property match calculator unit 443 computes a property match score
based on user responses to different subsets of questions selected
from the collection 264, such as a first subset of initial
screening questions selected from the question bank 265F, a second
subset of sensitivity questions selected from the question bank
265H, a third subset of user behavioral questions selected from the
question bank 265D, and a fourth subset of personal impact
questions selected from the question bank 265K.
[0278] For each subset, one or more questions N of the subset are
assigned an amplification factor. The value of each question N may
differ based on potential impact (i.e., severity) that the question
N has in influencing an overall value of a parameter corresponding
to a pollutant. A value may be defined for each question N, and the
question N may be factored into the calculation of more than one
parameter (i.e., may be factored into the calculation of different
parameters for different pollutants). For example, for each
parameter (e.g., Parameter 1, Parameter 2, Parameter 3, Parameter
4), the value of each question N factored into the calculation of
the parameter is summed. The overall value of each parameter is
then summated as a value V for the subset (e.g., V5 for the first
subset, V6 for the second subset, V7 for the third subset, V8 for
the fourth subset), and the value V is applied an amplification
factor representing the potential impact (i.e., severity) of the
subset on the health of a mean population demographic. Furthermore,
the overall value of each parameter may be amplified on a pollutant
basis such that the overall value of any one parameter
corresponding to a pollutant does not overly influence the property
score. Finally, each amplified value V is summated, and the
resulting sum represents the property match score.
[0279] The number of parameters may be variable.
[0280] Property Health Advice Application
[0281] FIG. 15 illustrates an example property health advice
application 450, in accordance with an embodiment of the invention.
In one embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
property health advice application 450. Approximately 35% of
illnesses are attributable to airborne pollutants that swirl around
in the air inside properties.
[0282] The property health advice application 450 may be used to
model an indoor environment to predict changing health conditions.
The property health advice application 450 is configured to model
an ecosystem within an indoor air environment of a property to
predict when conditions within the property become detrimental to
human health.
[0283] The property health advice application 450 provides property
health advice in real-time on how a user may interact with the
ecosystem of the property for better health, such as providing
recommended actions for the user to take to reduce impact on
his/her health. For example, the property health advice may
comprise user behavioral advice including suggested remediation
actions and/or interventions for a user to take with respect to the
property to reduce impact on his/her health.
[0284] The property health advice application 450 predicts when the
ecosystem of the property changes in ways that stress human health,
such as when pollutants harbored within places like wall cavities,
crawlspaces, attics and other interstitial spaces and carpets
become more active which in turn puts pressure on an occupant's
health. The ecosystem of the property represents the biology of the
property; when the biology of the property changes, occupants of
the property may get sick. The property health advice application
450 predicts when the biology of the property changes and how a
user may intervene.
[0285] The property health advice application 450 comprises a
health-o-meter unit 452 configured to analyze property attributes
of a property and effects of the local climate and outdoor air on
the property. To improve the analysis, a user may be presented with
questions selected from the collection 264 (e.g., property
attributes questions and sensitivity questions). The property
health advice application 450 comprises an adaptive question
selection unit 453 for adaptively selecting questions from the
collection 264. The property health advice application 450 may also
draw on factors/indexes used in determining a property score and a
property match score.
[0286] The property health advice application 450 comprises a
monitor unit 451 for monitoring local climatic changes to predict
daily and hourly changes in the indoor environment that could lead
to stress (impact) on the user's health. The health-o-meter unit
452 then provides, in real-time, health advice that suggest actions
and/or interventions for the user to take that will lead to
reductions of pollutants within the property as the weather or
climatic conditions change. The user may be to provide user
feedback on the outcome of the actions and/or interventions. The
user feedback will be used to further refine and improve the
intelligence of the health-o-meter unit 452. Users can track the
actions that they have taken and see those collected in reports and
graphs. The user may pull up a report with graphs and data on the
intervention actions they have taken to date, the projected impact
and their self-reported impact to track their actions over time.
This graph should also contain any larger remediation actions they
have done (remodeling, changing air ducts, removing carpeting,
etc.) that have been completed, i.e., any actions recommended in a
score or match report. Users can now visualize the impact of their
actions over time. The sense of accomplishment encourages them to
continue on.
[0287] The health-o-meter unit 452 may also provide preventative
advice in advance of climatic cycles, advice to manage risk during
cycles, and how to monitor for as well as ward off new problems
that could develop after the cycle is complete. The health-o-meter
unit 452 may also provide seasonal tips.
[0288] In one embodiment, the property health advice application
450 comprises a health advice report unit 455 for generating a
health advice report that includes customized health advice for a
user. A health advice report may be presented to a user via a
website 295.
[0289] The property health advice application 450 comprises a
notifications unit 454 configured to send notifications of health
advice through text, email or any other electronic method depending
on user preference and urgency of the health advice. Users can
delay or set reminders for actions, following notifications. They
can also report whether they did the action through a number of
methods, including directs responses to notifications.
[0290] In one embodiment, the health-o-meter unit 452 provides
health advice based in part on health events reported by a user.
The application 450 may also interface with a health app that is
already tracking health events of the user. These health events
will be correlated to further personalize health advice. The
health-o-meter unit 452 will map both cycles effecting the
ecosystem of the property along with user reported health events
and vital statistics.
[0291] The property health advice application 450 comprises a
maintenance unit 456 configured to track when property health
related maintenance routines/tasks needs to be performed, such as
replacing filters on HVAC, air purifiers, water filters, duct
cleaning, etc. The maintenance unit 456 will have the capacity to
prompt a user for when other property health related maintenance
routines/tasks needs to be performed, like changing the filters on
the vacuum.
[0292] In one embodiment, the property health advice application
450 extracts/determines a property attribute data (e.g., pattern
relating to a property attribute) from property data associated
with a property area. The property health advice application 450
combines the property attribute data with at least one other
property attribute data to determine presence or movement of a
pollutant data (e.g., pattern relating to a pollutant) within the
property area. The property health advice application 450 monitors
environmental context of the property area and detects a change
affecting the environmental context of the property area. If the
property health advice application 450 detects a change that
impacts the presence or the movement of the pollutant data within
the property area, the property health advice application 450
provides a recommendation for reducing the impact of the detected
change.
[0293] Table 13 below provides an example health advice report
generated by the property health advice application 450 in response
to real-time changes in climate.
TABLE-US-00013 TABLE 13 Sample Real Time Climatic Advice Climatic
conditions have shifted causing the ecosystem in your house to
stress your system. We recommend opening a few windows in each room
to mildly flush the house with fresh outdoor air. Outdoor climatic
conditions have high pollution and pollen. Based on your reported
sensitivities we recommend keeping your doors and windows closed
and filtering your air either by running your forced air in
ventilation mode providing it has a MERV 13 filter or better
installed and/or running your air purifiers. Climatic conditions
have shifted suddenly and forcefully. Open all doors and windows
for an aggressive flush for one hour. Best to leave the property
during this hour to clear the air. Families with properties like
yours in these kind of climatic shifts report nasal congestion 60%
of the time which leads to sinus infections 40% of the time.
Families who intervene by flushing the air report no adverse health
effect 90% of the time.
[0294] Table 14 below provides an example sequence of notifications
generated and sent by the property health advice application 450
over time in response to real-time changes in weather.
TABLE-US-00014 TABLE 14 Weather Event Advice Preemptory [First
notification sent in advance of upcoming weather event] Heavy Rains
are coming. Insure your gutters are clean, drains around the
property are unobstructed and the roof is clean. Concurrent [Second
notification generated and sent during the weather event] Rains
have subsided. Be aware of wet spots in the house. Look into your
crawlspace to insure there is no standing water. Post Event [Third
notification generated and sent after the weather event] It is now
a day later, be weary of any wet damp odors. Those will indicate
leaks within the walls, roof or floor that will likely lead to
biological growth. If these are cleaned up and dried within 24
hours you will avert health threats and expensive cleanup after the
fact.
[0295] In one embodiment, the property health advice application
450 comprises a property health analysis unit 459. In one example
implementation, the property health analysis unit 459 functions as
a population health analysis tool for providing health maps,
suggestions and insights for hospital, governments, insurance
agencies and other entities. The population health analysis tool
may be used to predict issues, such as flu outbreaks, pest
infestations, magnitude of population level health issues, etc.
[0296] In another example implementation, the property health
analysis unit 459 functions as a disaster response planner tool for
assisting disaster relief organizations and agencies, such as FEMA
and the Red Cross, in predicting and responding to disaster-related
events, such as floods.
[0297] Health Insurance Correlation Application
[0298] FIG. 16 illustrates an example health insurance correlation
application 460, in accordance with an embodiment of the invention.
In one embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a health
advice application 460. Approximately 35% of illnesses are
attributable to airborne pollutants that swirl around in the air
inside properties. The health insurance correlation application 460
comprises a correlation unit 461 and a health records unit 462 that
may be used at the direction of health insurance companies to
process and correlate thousands of health insurance records with
property attributes of insured record holders in order to predict
patterns of disease and symptomology that are a probable result of
a property of an insured record holder.
[0299] In one embodiment, the health insurance correlation
application 460 may implement certain firewalls to maintain HIPPA
confidentiality.
[0300] In one embodiment, the correlation unit 461 will correlate
disease codes in each health insurance record with the analytics
implemented by the property score application 420 based on public
data for properties occupied by insured record holders.
[0301] To improve the analysis, an insured record holder may be
presented with questions selected from the collection 264 (e.g.,
property attributes questions and sensitivity questions). Insurance
companies have the option to request that insured record holders
respond to sensitivity and user behavior questions, allowing
individualization of intervention strategies and projected costs.
The health insurance correlation application 460 comprises an
adaptive question selection unit 464 for adaptively selecting
questions from the collection 264. For example, if the property is
a school, students of the school may be asked to rate indoor air
quality of the school and other questions to determine the
attributes and climatic conditions affecting the school. Image data
of the school may also be obtained to improve the analysis. The
accuracy of the data may also be improved when an insured record
holder submits DNA, micro biome or blood test data to be
analyzed.
[0302] If indoor exposures are indicated as probable/correlated
cause of disease and symptomology pattern, but the insured record
holder's property does not appear to be high risk, the record
holder's place of work, school or other dominant place where he/she
spends significant time may be analyzed next using the health
insurance correlation application 460.
[0303] In one embodiment, the correlation unit 461 uses machine
learning to extract, collate, and analyze data from personal
profiles, property scores, and health insurance records to identify
correlations among disease codes, medical symptoms, medical
histories and conditions of current (or prior) properties. The
correlation unit 461 searches for possible correlations for a
particular insured record holder starting from elements that have
the highest known correlation with diseases and disease codes. The
correlation unit 461 evaluates correlations which include, but are
not limited to, the following: (1) disease codes and history to
personal susceptibility for exposure to biologicals, chemicals,
pets, and particles, (2) symptomology history and prescriptions to
amplification factors over time (such as windy or humid climates),
and (3) correlation between total burden on the insured record
holder and cost of health insurance claims over the next year.
[0304] For example, the correlation unit 461 may determine that
asthma attacks for children occupying a property have a 65%
correlation to start within 2 weeks from the start of biological
activity in the property resulting from leaks, water events and
cold fronts. As another example, the correlation unit 461 may
determine that pollen seasons have a 90% correlation with decreased
compliance in an insured record holder taking medications as
prescribed. As another example, the correlation unit 461 may
determine that an insured record holder is 10 points away from
moving to the next level on the total burden scale and their total
burden has recently risen; those who move up to this level on the
total burden scale typically cost $20K more per year in health
insurance claims than those who remain at their current level (70%
correlation).
[0305] In one embodiment, correlations determined by the
correlation unit 461 may be used to refine a property score, a
property match score, a personal profile and personal action plan,
etc.
[0306] In one embodiment, the health insurance correlation
application 460 comprises a health insurance correlation report
unit 463 for generating a health insurance correlation report. A
health insurance correlation report may be presented to an
insurance company via a website 295. The health insurance
correlation report may include a cost range of proposed
interventions so that the insurance company can correlate this
potential remedy with their actuary tables on the cost to insure.
Additionally, the insurance company can provide the insured record
holder the correlation and intervention cost so that the insured
record holder can make a decision as to whether the cost is a
worthy expense to improve his/her quality of life. The website 295
may include a web portal to certified contractors who can perform
the recommend interventions.
[0307] In one embodiment, the health insurance correlation
application 460 extracts/determines a property attribute data
(e.g., pattern relating to a property attribute) from property data
associated with a property area. The property health advice
application 450 combines the property attribute data with at least
one other property attribute data to determine presence or movement
of a pollutant data (e.g., pattern relating to a pollutant) within
the property area. The health insurance correlation application 460
determines a potential impact data (e.g., pattern relating to
personal impact) that the pollutant data may have on individual
health based in part on the combination, collects a health record
of a user associated with the property, and determines a
correlation between the health record and the potential impact
data.
[0308] Table 15 below provides an example health insurance
correlation report generated by the health insurance correlation
application 460.
TABLE-US-00015 TABLE 15 Asthma Insured has been to the emergency
room 3 times this year for asthma attacks. Insured's property has a
property score of 62 and combination of property attributes that
correlate with asthma attacks 78% of the time. Recommendation:
Insured responds to questions (e.g., personal sensitivity
questions) to improve probability of correlation. Follow-up report
[Generated in response to the insured responding to questions]: The
following interventions [list of suggested actions provided] in
properties with this pattern of property attributes and climate
have reduced emergency room visits for 68% of insured individuals
with disease and symptomology patterns like yours.
[0309] Table 16 below provides another example health insurance
correlation report generated by the health insurance correlation
application 460.
TABLE-US-00016 TABLE 16 Chronic Sinus Infections Insured has a
history of chronic sinus infections. Insured's property has a
property score of 50 with a high mold risk index for the property.
Additionally, the timing of infection correlates with local weather
patterns that lead to fungal activity within properties in this
climate. These patterns correlate with 80% likelihood that many of
these sinus infections are caused by the property. Recommendation:
Insured responds to questions (e.g., personal sensitivity and
symptoms questions) to improve probability of correlation.
Follow-up report [Generated in response to the insured responding
to questions]: The following interventions [list of suggested
actions provided] has reduced pattern of sinus infections by 60%
within patients with these characteristics 80% of the time.
[0310] In one embodiment, the health insurance correlation
application 460 comprises a health insurance correlation analysis
unit 469. In one example implementation, the health insurance
correlation analysis unit 469 functions as a geographic
region/multiple properties analysis tool for determining potential
health issues associated with a particular geographical area.
[0311] In another example implementation, the health insurance
correlation analysis unit 469 functions as a health insurance
coverage assessor tool for predicting cost of insuring groups with
particular types of properties.
[0312] FIG. 17 illustrates an example algorithm 465 applied by the
correlation unit 461 to determine health insurance correlations, in
accordance with an embodiment of the invention. The algorithm 465
includes variables determined using algorithms 425 and 443, as
described above.
[0313] Crowdsourcing Application
[0314] FIG. 18 illustrates an example crowdsourcing application
470, in accordance with an embodiment of the invention. In one
embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
crowdsourcing application 470. The crowdsourcing application 470
comprises crowdsourcing tools 472 for crowdsourcing information
associated with a property (e.g., commercial and public buildings
such as hotels, restaurants, schools, gyms, offices, theaters,
apartments, and churches) from a community of users. The
crowdsourcing tools 472 includes one or more virtual tools through
which one or more users may provide user feedback (e.g., ratings or
scores) relating to air quality of the property. The crowdsourcing
tools 472 may provide the user provided input for public viewing
via a website 295. Users may visit the website 295 to provide user
feedback about a particular property and/or view user feedback
submitted by other users. This enables a user to factor into user
feedback from other users when determining whether or not to
frequent/visit the property. The users may be business travelers,
parents, school children, teachers, office and service workers,
restaurant patrons, etc.
[0315] In one embodiment, the website 295 includes a score
submission webpage for receiving user feedback from users. The
score submission webpage comprises a graphical user interface (GUI)
that includes a submission form for users to rate air quality of a
particular property on a predetermined scale. For example, a user
may rate the air quality on a scale of 1 star to 5 stars, wherein 1
star represents a lowest degree of air quality (i.e., the air
quality is dirty and/or harmful), and wherein 5 stars represents a
highest degree of quality (i.e., the air quality is clean). The
score submission webpage may also prompt a user to describe how the
property makes them feel, and include an input text box that the
user may use to enter qualitative comments relating to the
property. Users may also submit photos and/or videos of the
property.
[0316] The crowdsourcing application 470 comprises a property air
quality calculator unit 471 for determining a property score for
air quality of a property based on user feedback received, via the
website 295, from one or more users, climate data about the
environment around the property, and/or public data about the
property and its construction. The property score determined may be
displayed on the website 295 together with some of the user
feedback received. In one embodiment, the website 295 provides a
summary of the input feedback received, and presents the summary
with top insights and highlights indicating the most frequently
mentioned feelings, complaints, or positives associated with the
air quality of the property.
[0317] The crowdsourcing tools 472 includes one or more tools
configured to suggest improvements to an owner of the property. For
example, an owner operating a business on a particular property
that has received input feedback may visit the website, and, upon
indicating that the owner is associated with the property, submit
additional information relating to the property. Based on the
additional information submitted and the property score, the
crowdsourcing system may provide one or more recommendations for
improving the air quality of the property, costs estimates and
return-on-investment (ROI) estimates for the improvements.
Improving the air quality of the property based on the
recommendations suggested may help improve customer experience of
the business and revenues of the business.
[0318] To improve the analysis, users may be presented with
questions selected from the collection 264 (e.g., property
attributes questions and sensitivity questions). The crowdsourcing
application 470 comprises an adaptive question selection unit 474
for adaptively selecting questions from the collection 264. For
example, additional information related to the property may be
obtained from an owner operating a business on the property by
presenting one or more property attributes questions to the
owner.
[0319] In one embodiment, the crowdsourcing application 470
comprises a property air quality report unit 473 for generating a
property air quality report. The property air quality report may
include one or more recommendations for improving the air quality
of the property, costs estimates and return-on-investment (ROI)
estimates for the improvements. A recommendation may be a suggested
intervention or a suggested action that the owner may take to
improve the air quality of the property. The property air quality
report may also include, if available, an estimated impact each
recommendation has on the property score of the property, as well
as impacts on the customer/user experience and business revenue.
The reports and recommendations are based on correlations between
property attributes of the property, input feedback received,
environmental factors and results of past interventions that the
owner had taken.
[0320] Table 17 below provides an example property air quality
report generated by the crowdsourcing application 470.
TABLE-US-00017 TABLE 17 Building has a commonly reported musty
smell and a rating of 63 out of 100. This is in the bottom 40% of
buildings. Based on the feelings of fatigue and sinus congestion
reported by users, images of moldy basement, high frequency of
water leaks in the building and past flooding in the area, there is
a . . . % likelihood that there is moldy air circulating throughout
the building - not just the basement. Typically, this issue leads
to a drop in a building air quality score by . . . points and has a
80% correlation with 25% lower foot traffic through the building.
Around 30% of the population is sensitive to damp, wet building
exposure and may experience the following symptoms while in the
building - uncomfortable with odors, loss of motivation,
congestion, burning eyes, mild stomach pain, foggy thinking Here
are interventions that can be taken to address the issues with a
typical cost range for the intervention and the improvements that
were seen by the building In your area, previous owners who have
employed contractors to intervene have rated the contractors as
follows . . .
[0321] In one embodiment, the crowdsourcing tools 472 provides a
collective action platform that facilitates collaboration among a
community of users with regards to improving air quality of a
property, such that an owner of a business being operated on the
property is not the only one with a say with regards to
improvement. The collective action platform, for example, may be
utilized by a community of users attending a particular school, a
particular office, or a particular library. The community of users
may come together to advocate for one or more changes in improving
the air quality of the property. The website may provide a suite of
collaboration tools, such as a discussion forum where different
users can post comments and discuss issues relating to the
property, form message threads for sharing tips relating to the
property, and upload videos and/or photos related to the property.
On the discussion forum, users may also create and support
different causes for specific improvements to the property that
users care about. Users may help group organize, advocate for
changes or contribute funding to a cause. A user may contribute to
funds for a cause using a third-party site, such as Kickstarter or
a trusted financial partner.
[0322] In one embodiment, the crowdsourcing tools 472 can allow
users of the community to indicate who their health insurance
carrier/provider is, such that the crowdsourcing tools 472 can
determine how many users have health insurance with the same
carrier/provider, and provide the carrier/provider with an estimate
of total health costs incurred as a result of the air quality of
the property.
[0323] The collective action platform may provide resource tools,
such as articles, website links, scientific studies and an advocacy
tool kit with literature, best practices for change, and cases
studies that show the ROI, cost and impact of past building
interventions. The resource tools may include a webpage listing
different partnerships (e.g., a health department, insurance
companies, etc.) that help advocate for change. If an insurance
company observes a high prevalence of sinus infections by users at
a particular property (e.g., a school), the insurance company may
become an ally in funding or supporting changes at the property for
improving air quality at the property.
[0324] In one embodiment, a user of the discussion forum may be
assigned the role of a community manager. The community manager
monitors forum discussions and comments, and may collaborate with
causes or set up contacts between partners and community groups, as
appropriate.
[0325] Contractor Recommendation Application
[0326] FIG. 19 illustrates an example contractor recommendation
application 480, in accordance with an embodiment of the invention.
In one embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a
contractor recommendation application 480. The contractor
recommendation application 480 comprises crowdsourcing tools 482
including a web portal for contractor referrals. The web portal may
also receive user feedback relating to different contractors from
owners who have engaged the contractors' services. For example, an
owner may rate and/or comment on service quality of a contractor,
and other owners may review the rating and/or comment provided.
Business owners who want access to contractors others than those
specifically recommended to them can search a certified contractor
database by location, contractor rating, contractor popularity,
intervention options offered, price and more. Users may list the
contractors they used in their area to perform work and submit what
they paid as well as their satisfaction with the services
performed. The web portal provides a contractor referral network
and collects a compilation of market prices as provided by users
self-reporting costs. The contractor recommendation application 480
also maintains a database of different certified contractors.
[0327] The contractor recommendation application 480 comprises a
contractor match unit 481 configured to, based on a location of a
property and information identifying specific interventions or
actions needed to improve the property and budget, time, or other
constraints and preferences of the user (e.g., price preferences),
generate recommendations identifying contractors that can perform
the interventions or actions identified within the budget
constraints. To improve the analysis, users may be presented with
questions selected from the collection 264 (e.g., property
attributes questions and sensitivity questions). The contractor
recommendation application 480 comprises an adaptive question
selection unit 484 for adaptively selecting questions from the
collection 264.
[0328] The contractor recommendation application 480 comprises a
contractor recommendation report unit 483 for generating a
contractor recommendation report including recommendations
identifying contractors that can perform interventions or actions
within particular budget constraints.
[0329] Virtual Inspection Application
[0330] FIG. 20 illustrates an example virtual inspection
application 490, in accordance with an embodiment of the invention.
In one embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is a virtual
inspection application 490. The virtual inspection application 490
provides a standardized set of instructions for capturing
images/videos (e.g., photographs) of physical attributes of a
property to facilitate a virtual inspection or user inspection
(guided based on the instructions) of the property.
[0331] The images/videos captured may be used to determine property
information relating to the property, such as key physical
attributes, proximity, and environmental context information. The
virtual inspection application 490 may generate a custom set of
instructions for capturing images/videos of particular areas of
interest of the property, wherein the areas of interest are based
on the property information and/or other sources of information
relating to the property (e.g., property score, personal profile,
health insurance information, etc.). The areas of interest may
represent suspected high risk areas, such as areas that are likely
to affect health of an occupant of the property.
[0332] An example area of interest may include an area of the
property where water staining or warping of walls and/or flooring
is detected, indicating water damage and/or dampness indoors. Water
damage and/or dampness indoors is likely to affect occupants who
are sensitive to biological amplification, including mold
growth.
[0333] Another example area of interest may include an area of the
property where dust and/or debris is visible (e.g., on carpets),
air filters, and air ducts. Accumulation of a particulate
(typically composed of multiple, complex substances), is likely to
affect occupants with heightened sensitivity/reactivity to dust,
pollen, pet dander, and other irritants and asthmagens.
[0334] In one embodiment of the invention, a property score
determined by the property score application 420 may be used to
identify areas of interest in the property. The areas of interest
may include areas of the property with sources of exposure to
pollutants, such as attic, basement, fireplace, crawlspace, water
features, and, external sources of pollutants such as restaurants,
factories, highways, dry cleaners, in close proximity to the
property. For example, an attic with visible water damage or a
crawlspace where the HVAC is located could pose substantial risk
for susceptible individuals. As another example, a property located
within proximity and downwind of a dry cleaning business could be
at risk for an individual who is chemically intolerant.
[0335] In one embodiment of the invention, health insurance data
for one or more occupants of a property may be used to identify
areas of interest in the property. The health insurance data may
include information identifying reported illnesses, syndromes and
health sensitivities/reactivities of the occupants. Based on the
health insurance data, areas of interest may include areas and
conditions of the property that are likely to contribute to the
reported illnesses, syndromes, and health
sensitivities/reactivities of the occupants.
[0336] The virtual inspection application 490 comprises an adaptive
question selection unit 494 for adaptively selecting questions from
the collection 264.
[0337] In one embodiment of the invention, a personal profile for
one or more occupants of a property may be used to identify areas
of interest in the property.
[0338] For example, if health insurance data for an occupant of the
property indicates that the occupant has asthma and sinus
infections that correlate with windy days and pollen, the
photo-based inspection system may provide an additional set of
instructions for capturing additional images of sealants around
windows and/or doors of the property. The condition of sealants
around windows and/or doors of the property may suggest how "leaky"
the property is and may amplify the impact that wind in the area of
the property may have on the occupant.
[0339] The virtual inspection application 490 comprises an
image/video recognition and correlation unit 491. Using a machine
learning algorithm, the image/video recognition and correlation
unit 491 learns over time, which images/videos captured are most
likely to correlate with recommendations that an expert adjusts for
a personal action plan or a property match score. The image/video
recognition and correlation unit 491 can, over time, learn which
images/videos are most likely to have an impact on recommendations,
such that instructions for capturing images that have the highest
likelihood of impacting recommendations are requested.
[0340] The virtual inspection application 490 may request
additional images/videos capturing unusual property features or
systems, areas suspected by the occupants of involvement with their
experience, areas based on expert judgment, areas previously fixed
that indicate past problems inadequately addressed, occupant
behaviors that may alter the conditions of the indoor
environment.
[0341] In one embodiment, a property score for a property and/or
recommendations for improving the property score may be refined
using images requested by the virtual inspection application 490.
For example, the virtual inspection application 490 may provide a
set of instructions, via a website 295 accessible to the user, for
capturing images and/or video of interior and/or exterior areas of
the property.
[0342] In one embodiment, the virtual inspection application 490
comprises an expert consultation unit 492 that allows one or more
consultation experts to make observations regarding physical
attributes of the property based on the images and/or videos
captured. A consultation expert may be a trained in-house
specialist. The expert consultation unit 492 may also facilitate
live consultation between a user and a consultation expert. The
consultation may be pre-arranged for a pre-determined fee (e.g., an
hourly rate).
[0343] The virtual inspection application 490 comprises an
inspection report unit 493 for generating an inspection report
including recommendations. In one embodiment, an inspection report
is provided in exchange for a fee paid by the user.
[0344] In one embodiment, the virtual inspection application 490
identifies an area of interest of a property area based on property
data associated with the property area. The area of interest
identified represents a potential area of the property area that
may negatively impact health of a user. The virtual inspection
application 490 provides the user an instruction for capturing
image data relating to the area of interest identified, receiving
the image data from the user, and extracts/determines a property
attribute data (i.e., pattern relating to a property attribute)
from the image data. The virtual inspection application 490
combines the property attribute data with at least one other
property attribute data to determine presence or movement of a
pollutant data (e.g., pattern relating to a pollutant) within the
property area.
[0345] Table 18 below provides an example inspection report
generated by the virtual inspection application 490.
TABLE-US-00018 TABLE 18 Sample Buyer Report: 80% of properties like
this typically have poor indoor air quality, a condition that
results in negative impact on occupant health. Stucco Walls in this
climate with signs of landscaping sprinklers hitting the wall on
the shaded side of the house have high risk of biological growth
inside the wall cavities. The two northeastern walls shown in this
picture should be investigated. Typical cost to repair this kind of
problem ranges from $3,000-$20,000. This property was built in
1938. The paint around the windows appears to be original. It is
highly likely to contain lead paint. Remediation or encapsulation
needs to be done. Typical cost in your area is $1,000-$3,000.
Properties with basements in this climate negatively impact
occupant health 50% of the time. This basement shows signs of
moisture intrusion in photo #3. That increases likelihood to 80%.
Typical costs to remediate and repair range from $3,000 to $15,000
in your area Cat is living in the house. You indicated you are
sensitive to cats. Effective remediation would require painting to
encapsulate existing dander on the wall, removal of the carpet, and
cleaning the duct work to reduce risk of impact on you. Typical
cost in your area is $3,000-5,000.
[0346] Table 19 below provides another example inspection report
generated by the virtual inspection application 490.
TABLE-US-00019 TABLE 19 Sample Occupant Report Based on the
characteristics of your property and your answers about how the
house has impacted you we recommend the following interventions
prioritized by what has proven to be the highest efficacy when
applied to properties with similar characteristics and climate
conditions to yours. 1. Data - Your property is 10 years old and
the photo #4 provide of the furnace appears to show it is of the
same age. You have a crawlspace and the ducts travel through the
crawlspace. 10 year old ducts typically leak and draw crawlspace
air into the property. You answered that your typically sneeze when
the furnace comes on. Solution We recommend cleaning and sealing
the duct work as a minimum. It would be better to replace it. We
recommend air sealing between the crawlspace and the property as
well as sealing the dirt floor of the crawlspace with a layer of
poly as outlined. 80% of people who own properties with
characteristics like yours report significant improvements in how
they feel after implementing this strategy. Crawlspace Air Sealing
- Click this link Crawlspace Floor Sealing - Click this link How to
hire a local installer - Click to see video.
[0347] Investment Risk Application
[0348] FIG. 21 illustrates an example investment risk application
800, in accordance with an embodiment of the invention. In one
embodiment, one of the applications 410 (FIG. 2)
executing/operating on the server devices 210 (FIG. 1) is an
investment risk application 800. The investment risk application
800 comprises an investment risk comparison unit 801 configured to
compare property scores and/or property match scores for multiple
properties, and provide an estimated cost of improvements for each
property. The comparison allows a prospective buyer to compare
purchase costs for each property against an estimated cost of
improvements for the property.
[0349] In one embodiment, the investment risk application 800
comprises an adaptive question selection unit 804 for adaptively
selecting questions from the collection 264.
[0350] In one embodiment, the investment risk application 800
comprises a weightings unit 802. The weightings units 802
comprises, but is not limited to, the following: (a) different
weighting values for different attributes, factors or indexes, (b)
different prevalence values for different attributes, factors or
indexes, and (c) data representing interrelationships between
different attributes, factors or indexes.
[0351] The investment risk application 800 comprises an investment
risk comparison report unit 803 for generating an investment risk
comparison report. FIG. 22 illustrates an example investment risk
comparison report 850, in accordance with an embodiment of the
invention.
[0352] FIG. 23 is a high level block diagram showing an information
processing system 300 useful for implementing one embodiment of the
invention. The computer system includes one or more processors,
such as processor 302. The processor 302 is connected to a
communication infrastructure 304 (e.g., a communications bus,
cross-over bar, or network).
[0353] The computer system can include a display interface 306 that
forwards graphics, text, and other data from the communication
infrastructure 304 (or from a frame buffer not shown) for display
on a display unit 308. The computer system also includes a main
memory 310, preferably random access memory (RAM), and may also
include a secondary memory 312. The secondary memory 312 may
include, for example, a hard disk drive 314 and/or a removable
storage drive 316, representing, for example, a floppy disk drive,
a magnetic tape drive, or an optical disk drive. The removable
storage drive 316 reads from and/or writes to a removable storage
unit 318 in a manner well known to those having ordinary skill in
the art. Removable storage unit 318 represents, for example, a
floppy disk, a compact disc, a magnetic tape, or an optical disk,
etc. which is read by and written to by removable storage drive
316. As will be appreciated, the removable storage unit 318
includes a computer readable medium having stored therein computer
software and/or data.
[0354] In alternative embodiments, the secondary memory 312 may
include other similar means for allowing computer programs or other
instructions to be loaded into the computer system. Such means may
include, for example, a removable storage unit 320 and an interface
322. Examples of such means may include a program package and
package interface (such as that found in video game devices), a
removable memory chip (such as an EPROM, or PROM) and associated
socket, and other removable storage units 320 and interfaces 322,
which allows software and data to be transferred from the removable
storage unit 320 to the computer system.
[0355] The computer system may also include a communication
interface 324.
[0356] Communication interface 324 allows software and data to be
transferred between the computer system and external devices.
Examples of communication interface 324 may include a modem, a
network interface (such as an Ethernet card), a communication port,
or a PCMCIA slot and card, etc. Software and data transferred via
communication interface 324 are in the form of signals which may
be, for example, electronic, electromagnetic, optical, or other
signals capable of being received by communication interface 324.
These signals are provided to communication interface 324 via a
communication path (i.e., channel) 326. This communication path 326
carries signals and may be implemented using wire or cable, fiber
optics, a phone line, a cellular phone link, an RF link, and/or
other communication channels.
[0357] The present invention may be a system, a method, and/or a
computer program product. The computer program product may include
a computer readable storage medium (or media) having computer
readable program instructions thereon for causing a processor to
carry out aspects of the present invention. The computer readable
storage medium can be a tangible device that can retain and store
instructions for use by an instruction execution device. The
computer readable storage medium may be, for example, but is not
limited to, an electronic storage device, a magnetic storage
device, an optical storage device, an electromagnetic storage
device, a semiconductor storage device, or any suitable combination
of the foregoing. A non-exhaustive list of more specific examples
of the computer readable storage medium includes the following: a
portable computer diskette, a hard disk, a random access memory
(RAM), a read-only memory (ROM), an erasable programmable read-only
memory (EPROM or Flash memory), a static random access memory
(SRAM), a portable compact disc read-only memory (CD-ROM), a
digital versatile disk (DVD), a memory stick, a floppy disk, a
mechanically encoded device such as punch-cards or raised
structures in a groove having instructions recorded thereon, and
any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0358] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0359] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, or either source code or object
code written in any combination of one or more programming
languages, including an object oriented programming language such
as Smalltalk, C++ or the like, and conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The computer readable program
instructions may execute entirely on the user's computer, partly on
the user's computer, as a stand-alone software package, partly on
the user's computer and partly on a remote computer or entirely on
the remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider). In some embodiments, electronic circuitry
including, for example, programmable logic circuitry,
field-programmable gate arrays (FPGA), or programmable logic arrays
(PLA) may execute the computer readable program instructions by
utilizing state information of the computer readable program
instructions to personalize the electronic circuitry, in order to
perform aspects of the present invention.
[0360] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
[0361] These computer readable program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in
a computer readable storage medium that can direct a computer, a
programmable data processing apparatus, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
[0362] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing
apparatus, or other device to cause a series of operational steps
to be performed on the computer, other programmable apparatus or
other device to produce a computer implemented process, such that
the instructions which execute on the computer, other programmable
apparatus, or other device implement the functions/acts specified
in the flowchart and/or block diagram block or blocks.
[0363] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
[0364] From the above description, it can be seen that the present
invention provides a system, computer program product, and method
for implementing the embodiments of the invention. The present
invention further provides a non-transitory computer-useable
storage medium for implementing the embodiments of the invention.
The non-transitory computer-useable storage medium has a
computer-readable program, wherein the program upon being processed
on a computer causes the computer to implement the steps of the
present invention according to the embodiments described herein.
References in the claims to an element in the singular is not
intended to mean "one and only" unless explicitly so stated, but
rather "one or more." All structural and functional equivalents to
the elements of the above-described exemplary embodiment that are
currently known or later come to be known to those of ordinary
skill in the art are intended to be encompassed by the present
claims. No claim element herein is to be construed under the
provisions of 35 U.S.C. section 112, sixth paragraph, unless the
element is expressly recited using the phrase "means for" or "step
for."
[0365] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0366] The corresponding structures, materials, acts, and
equivalents of all means or step plus function elements in the
claims below are intended to include any structure, material, or
act for performing the function in combination with other claimed
elements as specifically claimed. The description of the present
invention has been presented for purposes of illustration and
description, but is not intended to be exhaustive or limited to the
invention in the form disclosed. Many modifications and variations
will be apparent to those of ordinary skill in the art without
departing from the scope and spirit of the invention. The
embodiment was chosen and described in order to best explain the
principles of the invention and the practical application, and to
enable others of ordinary skill in the art to understand the
invention for various embodiments with various modifications as are
suited to the particular use contemplated.
* * * * *