U.S. patent application number 12/536999 was filed with the patent office on 2010-05-27 for dynamic insurance rates.
Invention is credited to Himanshu S. Amin, Brian Asquith, Fred Collopy, Ronald Charles Krosky, Craig Allen Nard, Gustavo Arnaldo Narvaez, David Noonan, Seyed Vahid Sharifi Takieh, Gregory Turocy.
Application Number | 20100131303 12/536999 |
Document ID | / |
Family ID | 42197144 |
Filed Date | 2010-05-27 |
United States Patent
Application |
20100131303 |
Kind Code |
A1 |
Collopy; Fred ; et
al. |
May 27, 2010 |
DYNAMIC INSURANCE RATES
Abstract
Systems and methods that customize insurance rates in real time
to correspond to unique behavior/character traits of a user/driver.
A rate adjustment component can interact with insurance companies
that provide bids based on the contextual data--wherein, insurance
costs can be dynamically adjusted, and the user/driver switched in
real-time between such insurance companies (e.g., based on bids),
to ensure obtaining optimum rates. A switching component can switch
user/driver) to an insurance company that bids the best rate.
Hence, during a trip the user/driver can actually be insured by
various suppliers during different segments of such trip.
Inventors: |
Collopy; Fred; (Cleveland
Heights, OH) ; Nard; Craig Allen; (Shaker Heights,
OH) ; Amin; Himanshu S.; (Solon, OH) ; Turocy;
Gregory; (Moreland Hills, OH) ; Sharifi Takieh; Seyed
Vahid; (Broadview Heights, OH) ; Krosky; Ronald
Charles; (Lakewood, OH) ; Noonan; David;
(Webster Groves, MO) ; Narvaez; Gustavo Arnaldo;
(Solon, OH) ; Asquith; Brian; (Cleveland Heights,
OH) |
Correspondence
Address: |
TUROCY & WATSON, LLP
127 Public Square, 57th Floor, Key Tower
CLEVELAND
OH
44114
US
|
Family ID: |
42197144 |
Appl. No.: |
12/536999 |
Filed: |
August 6, 2009 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61118400 |
Nov 26, 2008 |
|
|
|
Current U.S.
Class: |
705/4 ; 340/5.82;
348/148; 348/E7.085; 706/54 |
Current CPC
Class: |
G06Q 30/0273 20130101;
G06Q 30/0201 20130101; G06Q 30/06 20130101; G06Q 30/0251 20130101;
G06Q 30/0269 20130101; G06Q 30/0224 20130101; G06Q 30/04 20130101;
G06Q 40/08 20130101; G06Q 30/0265 20130101 |
Class at
Publication: |
705/4 ; 340/5.82;
348/148; 348/E07.085; 706/54 |
International
Class: |
G06Q 40/00 20060101
G06Q040/00; G06F 7/04 20060101 G06F007/04; H04N 7/18 20060101
H04N007/18 |
Claims
1. A computer implemented system that customizes insurance rates to
user profiles comprising: a rate adjustment component that
dynamically adjusts an insurance rate in real time for a user based
on contextual data; and a switching component that switches the
user to an insurance provider(s) that supplies optimal rate based
on the contextual data.
2. The computer implemented system of claim 1 further comprising a
retrieval agent that pulls insurance data from the insurance
provider(s.)
3. The computer implemented system of claim 1, the contextual data
includes data pertaining to a motor vehicle; or data related to a
driver of the motor vehicle; or data related to environment that
the motor vehicle operates therein; or real time data related to
driving behavior; or a combination thereof.
4. The computer implemented system of claim 1 further comprising an
analyzer component that employs threshold ranges to accept or
reject insurance bids from the insurance provider.
5. The computer implemented system of claim 3, the real time
driving data pertains to both frequency and intensity of driving
actions.
6. The computer implemented system of claim 2 further comprising
sensor positioned on a body of driver for collection of biometric
data.
7. The computer implemented system of claim 1 further comprising an
inference component that facilitates customization of insurance
rates.
8. The computer implemented system of claim 7 further comprising an
artificial intelligence component that employs classifiers.
9. The computer implemented system of claim 8, the switching
component is an automatic switch.
10. A computer implemented method comprising the following computer
executable acts: employing a processor to execute computer
executable instructions stored on a computer readable medium to
perform the following acts: acquiring contextual data associated
with a driver of a motor vehicle; and; dynamically adjusting
insurance rates in real time based on contextual data via a rate
determination component that receives offers from insurance
companies.
11. The computer implemented method of claim 10 further comprising
switching insurance policy for a motor vehicle of a user to an
insurance company via a switching component mounted on the motor
vehicle.
12. The computer implemented method of claim 11 further comprising
pulling insurance bids from the insurance company.
13. The computer implemented method of claim 11 further comprising
employing an interrupt for the switching act.
14. The computer implemented method of claim 11 further comprising
setting threshold values or ranges to accept or reject a bid.
15. The computer implemented method of claim 11 further comprising
evaluating an insurance policy via a rule-based implementation.
16. The computer implemented method of claim 11 further comprising
collecting data by cameras mounted on the motor vehicle.
17. The computer implemented method of claim 11 further comprising
automatically switching a driver to an insurance provider.
18. The computer implemented method of claim 11 further comprising
employing both intensity and frequency of a driving act as part of
the contextual data.
19. The computer implemented method of claim 11 further comprising
employing an artificial intelligence component to facilitate
selection of an insurance policy.
20. A computer implemented system that customizes insurance rates
to user profiles comprising: means for dynamically adjusting an
insurance rate in real time for a user based on contextual data;
and means for switching the user to an insurance provider that
supplies optimal rate based on the contextual data.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 61/118,400 filed on 26 Nov. 2008 entitled
"INSURANCE OPTIMIZER AND REAL TIME ANALYTICS", and the entirety of
this application is hereby incorporated by reference.
BACKGROUND
[0002] Insurance policies typically include legal agreements that
specify items to be afforded coverage with respect to particular
perils. For such agreements, numerous conditions apply, such as
applicable deductibles, coverage limits, and the like, wherein
related expense/billing can further be broken down into elements by
covered item and peril.
[0003] Moreover, insurance carriers often view such policies as
being derived from and related to a "policy product". Typically, a
policy product defines the attributes and shared data for its
derived policies, wherein a process of writing a specific policy
involves referring to the available attributes of the policy as
defined by the policy product and the corresponding selection of
appropriate values for a given customer. As such, a coverage
typically comprises an obligation to pay for damages that are
caused by a particular peril (or collection of perils). Such
obligation typically has corresponding financial limits and
deductibles that circumscribe the insurer's responsibility for
losses against that coverage. For example, a policy's total cost is
usually determined as a function of the aggregate cost of the
policy's constituent coverage sections.
[0004] Moreover, insurance coverage typically applies to risk units
(e.g., a scenario or circumstance that may be exposed to loss). For
example, risk units can comprise buildings, vehicles, personal
property, on-going business, or the like. In such cases, insurance
is obtained by receiving quotes from various companies and
selecting the most desirable policy considering coverage, price,
and other factors. In particular, insurance companies generate
coverage premiums based on a number of factors that represent
averaged scenarios regarding the item to be covered. Insurance
companies typically have highly proprietary systems that
automatically generate premiums using the factors, and each
insurance company typically has its own system resulting in varying
premiums for different items with respect to different policy
holders and desired coverage levels.
[0005] Moreover, insurance premiums are typically fixed in price
and billed in monthly, semi-annual, or annual time periods.
Premiums can be affected by many policy parameters for which cost
is averaged and can be adjusted for a given billing period. For
example, with respect to automobile insurance, rates can be
determined based on desired coverage level, automobile make, model,
and color, automobile features, estimated miles driven each year,
zip code, and the like In addition, rates can be evaluated at the
end of a premium period based on number of claims filed in the
primary zip code. With such speculative and broad premium
computation, it can become difficult to offer precise and
competitive rates for insurance policies, hence hindering insurance
markets.
[0006] Put differently, an insurance company determines insurance
costs based on insurance models that classify segments of the
population to groups sharing similar data, such as; age range, sex,
marital status, residence, driving record, and the like. For each
segment, the insurance model then employs a "one size fit" for all
members--with no further differentiation. Nonetheless, such
approach fails to consider additional variances that exist between
members in same category, and hence squanders valuable data related
to each individual's unique traits that can further affect
respective insurance rates.
SUMMARY
[0007] The following presents a simplified summary in order to
provide a basic understanding of some aspects described herein.
This summary is not an extensive overview of the claimed subject
matter. It is intended to neither identify key or critical elements
of the claimed subject matter nor delineate the scope thereof. Its
sole purpose is to present some concepts in a simplified form as a
prelude to the more detailed description that is presented
later.
[0008] The subject innovation customizes insurance rates in real
time to correspond to unique behavior/character traits of a
user/driver by exploiting contextual data (e.g., from third party
data banks, driving behavior, and the like), which are related to
such user/driver. A rate adjustment component can interact with
insurance companies that provide bids based on the contextual
data--wherein, insurance costs can be dynamically adjusted, and the
user/driver switched in real-time between such insurance companies
(e.g., based on bids)--to ensure obtaining optimum rates. The
contextual data and/or data banks can include data pertaining to
the motor vehicle (e.g., maintenance history, current vehicle
conditions, sensor monitoring operation of the motor vehicle, and
the like); data related to the driver (e.g., via health insurance
records, police records, internet records, and the like); and data
related to operating environment (e.g., weather, geographical
location, and the like.) Moreover, the real-time contextual driving
data can include both an intensity portion and a frequency portion,
which represent severity and regularity of driving episodes (e.g.,
slamming the brakes, gradual/sudden deceleration, velocity
variances, and number of such acts in a predetermined period).
[0009] In a related aspect, a switching component can switch
user/driver (e.g., automatically with no additional input from
user) to an insurance company that bids the best rate. Hence,
during a trip the user/driver can actually be insured by various
suppliers during different segments of such trip--(each of which
supplies an optimal rate for the trip segment that switching
thereto occurred.) Alternatively, the user can remain with the same
insurance company throughout the trip; and yet comply with its
mandates (e.g., limits on speed/acceleration, car maintenance) for
obtaining optimal rates.
[0010] Hence, the subject innovation introduces two insurance
models, namely: 1) a user/driver complying with requirements of a
single insurance company to keep current insurance rates; or 2)
different insurance companies bidding for the behavior of user not
willing to necessarily abide to requirements of a single insurance
company. Moreover, the subject innovation can be implemented as
part of a system local to each motor vehicle (e.g., the rate
adjustment component and the switching component are positioned on
the motor vehicle); or part of a central management system, or a
combination thereof. It is to be appreciated that even though the
subject innovation is primarily described in context of an
automobile, the subject innovation is not so limited and can be
applied to any type of vehicle that requires insurance; such as
motor boats, airplanes, motorcycles, and the like.
[0011] To the accomplishment of the foregoing and related ends,
certain illustrative aspects of the claimed subject matter are
described herein in connection with the following description and
the annexed drawings. These aspects are indicative of various ways
in which the subject matter may be practiced, all of which are
intended to be within the scope of the claimed subject matter.
Other advantages and novel features may become apparent from the
following detailed description when considered in conjunction with
the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1 illustrates an exemplary block diagram of a switching
component and a rate adjustment component according to an aspect of
the subject innovation.
[0013] FIG. 2 illustrates a particular aspect of a switching
component that has an analyzer component according to a further
aspect.
[0014] FIG. 3 illustrates a particular aspect of a system that
illustrates exemplary type of contextual data according to a
further aspect.
[0015] FIG. 4 illustrates a system that determines location of a
vehicle as part of contextual data related to driving behavior of
an owner or user.
[0016] FIG. 5 illustrates a particular methodology of customizing
insurance rates according to a further aspect of the subject
innovation.
[0017] FIG. 6 illustrates a related methodology of switching
insurance to a policy with an optimal rate according to a further
aspect.
[0018] FIG. 7 illustrates an exemplary system that obtains
contextual data related to biometrics of a driver/owner in
real-time.
[0019] FIG. 8 illustrates an inference component that facilitates
customizing insurance rates based on contextual data.
[0020] FIG. 9 illustrates a particular system that employs cameras
mounted on the vehicle in conjunction with various aspects of the
subject innovation.
[0021] FIG. 10 illustrates an exemplary environment for
implementing various aspects of the subject innovation.
[0022] FIG. 11 is a schematic block diagram of a sample-computing
environment that can be employed for dynamically determining an
insurance rate according to a further aspect of the subject
innovation.
DETAILED DESCRIPTION
[0023] The various aspects of the subject innovation are now
described with reference to the annexed drawings, wherein like
numerals refer to like or corresponding elements throughout. It
should be understood, however, that the drawings and detailed
description relating thereto are not intended to limit the claimed
subject matter to the particular form disclosed. Rather, the
intention is to cover all modifications, equivalents and
alternatives falling within the spirit and scope of the claimed
subject matter.
[0024] FIG. 1 illustrates an exemplary system 100 that customizes
insurance rates to correspond to unique behavior
of--and/or-character traits of a user/owner by exploiting data
banks 111, 112, 113 such as data mined by third parties. Such
leveraging from data banks enables insurance providers to bid in
real time, and hence an owner and/or user of a vehicle can benefit
from competition among various insurance providers, to obtain
optimum rates. The system 100 includes a rate adjustment component
131 that in real time can determine the various rates from a
plurality of insurance providers 121, 122, 123 (1 to m, where m is
an integer). In one particular aspect, a retrieval agent (not
shown) associated with the rate adjustment component 131 can pull
insurance data from the insurance providers based on the contextual
data supplied thereto. For example, such contextual data can be
data records related to the vehicle 111 (such as auto shop service
records, current service status for the car, and the like); data
related to the individual driver 112 (such as health records,
criminal records, shopping habits, and the like); data related to
the environment 113 (road condition, humidity, temperature, and the
like) and data related to real time driving 115 (frequency of
braking, accelerating, intensity of such actions, and the
like).
[0025] The retrieval agent (not shown) can pull data from the
insurance providers 121, 122, 123 and further publish such data to
enable a rich interaction between the users on a display or a
within a written communication environment. The retrieval agent can
further generate an instance for a connection with the insurance
providers. Accordingly, a connection instance can be employed by
the rate adjustment component 131 to store connection information
such as the state of data conveyance, the data being conveyed,
connection ID and the like. Such information can additionally be
employed to monitor progress of data transfer to the written
communication environment or display, for example.
[0026] Accordingly drivers/owners of motor vehicles can pull or
receive data from the insurance providers 121, 122, 123, wherein
received data can be posted (e.g., displayed on a monitor) and the
connection instance can be concurrently updated to reflect any
successful and/or failed data retrievals. Thus, at any given moment
the connection instance can include the most up-to-date version of
data transferred between the motor vehicle and the insurance
providers.
[0027] Moreover, the switching component 141 can automatically
switch user/driver to an insurance provider/company that bids the
best rate. Such switching component 141 can employ interrupts both
in hardware and/or software to conclude the switching from one
insurance provider to another insurance provider. For example, the
interrupt can convey receipt of a more optimal insurance rate or
completion of a pull request to the insurance providers 121, 122,
123 or that a configuration has changed. In one particular aspect,
once an interrupt occurs, an operating system analyzes the state of
the system 100 and performs an action in accordance with the
interrupt, such as a change of insurance provider, for example.
[0028] Such interrupts can be in form of asynchronous external
events to the processor that can alter normal program flow.
Moreover, the interrupts can usually require immediate attention
from a processor(s) associated with the system 100. In one aspect,
when an interrupt is detected, the system often interrupts all
processing to attend to the interrupt, wherein the system can
further save state of the processor and instruction pointers on
related stacks.
[0029] According to a further aspect, the switching component 141
can employ an interrupt dispatch table in memory, which can be
accessed by the processor to identify a function that is to be
called in response to a particular interrupt. For example, a
function can accept a policy from an insurance provider, cancel an
existing policy, and/or clear the interrupt for a variety of other
reasons. The function can execute processes such as clearing the
state of the interrupt, calling a driver function to check the
state of an insurance policy and clearing, setting a bit, and the
like.
[0030] FIG. 2 illustrates a switching component 241 that further
includes an analyzer component 251, which further employs threshold
ranges and/or value(s) (e.g., pricing ranges for insurance
policies, terms of the insurance policy, and the like) according to
a further aspect of the subject innovation. The analyzer component
251 can compare a received value for insurance coverage to the
predetermined thresholds, which can be designated by an
owner/driver. Accordingly, the analyzer component 251 can determine
if the received insurance coverage policies are within the desired
range as specified by a user an "accept" or "reject", and/or
further create a hierarchy from "low" to "high" based on criteria
designated by the user (e.g., price of the insurance policy, terms
of the insurance policy, and the like).
[0031] According to a further aspect, the analyzer component 251
can further interact with a rule engine component 252. For example,
a rule can be applied to define and/or implement a desired
evaluation method for an insurance policy. It is to be appreciated
that the rule-based implementation can automatically and/or
dynamically define and implement an evaluation scheme of the
insurance policies provided. Accordingly, the rule-based
implementation can evaluate an insurance policy by employing a
predefined and/or programmed rule(s) based upon any desired
criteria (e.g., criteria affecting an insurance policy such as
duration of the policy, number of drivers covered, type of risks
covered, and the like.)
[0032] In a related example, a user can establish a rule that can
implement an evaluation based upon a preferred hierarchy (e.g.,
weight) of a criteria that affects the insurance policy. For
example, the rule can be constructed to evaluate the criteria based
upon predetermined thresholds, wherein if such criteria does not
comply with set thresholds, the system can further evaluate another
criteria or attribute(s) to validate the status (e.g., "accept" or
"reject" the insurance bid and operate the switching component
based thereon). It is to be appreciated that any of the attributes
utilized in accordance with the subject invention can be programmed
into a rule-based implementation scheme.
[0033] FIG. 3 illustrates a system 300 that illustrates type of
data for dynamically adjusting insurance costs according to an
aspect of the subject innovation. As explained earlier, the subject
innovation customizes insurance rates to correspond to unique
behavior/character traits of a user/driver by exploiting data banks
(e.g., from third parties), in conjunction with real time
contextual driving data (e.g., driving behavior) of such
user/driver. Accordingly, insurance costs can be dynamically
adjusted and the user/driver switched in real-time between
insurance companies (e.g., based on bids), to ensure obtaining
optimum rates.
[0034] The data banks can include data pertaining to the motor
vehicle 310 (e.g., maintenance history, current vehicle conditions,
and the like); data related to the driver (e.g., via health
insurance records, police records, internet records, and the like);
and data related to operating environment 330 (e.g., weather,
geographical location, and the like.) Moreover, the real-time
contextual driving data 340 can include both an intensity portion
and a frequency portion, which represent severity and regularity of
driving episodes (e.g., slamming the brakes, gradual/sudden
deceleration, velocity variances, and the like). Although a single
data store for each of data type, it is to be understood that
multiple data stores can be employed in connection with the subject
innovation. In addition, it is to be appreciated that any number of
reference data sources and stores can be located remotely from the
rate adjustment component (not shown), and the analyzer component
(not shown). In one particular aspect, the data bank 320 can
further include user profiles and demographics such as user
preferences, age, gender, religion, ethnicity, education level,
likes, dislikes, interests, occupation, political ideology, and the
like--which can be employed in connection with the contextual
information to facilitate generating customized insurance policies
by the insurance providers.
[0035] Furthermore, the system 300 can aggregate such user
information amongst a plurality of users in connection with
providing relevant results to a group of individuals (e.g., with
similar interaction histories, engaged in a common activity, part
of a multi-user collaboration, within a work environment or social
network). Such retrieval can benefit from the construction of
models of interest from data about information access or
consumption patterns by people with similar attributes and/or
immersed in similar contexts (e.g., similar demographics, similar
locations, and the like). It is to be appreciated that the
functionality associated with context-based insurance policies can
also be employed as a context-based filter, to eliminate policies
that do not match user predetermined thresholds.
[0036] The insurance providers 350, 352, 354 and the motor vehicle
can also be part of a network 370 (e.g., wireless network) such as
a system area network or other type of network, and can include
several hosts, 361, 362, 363, 364, 365, which can be personal
computers, servers or other types of computers. Such hosts
generally can be capable of running or executing one or more
application-level (or user-level) programs, as well as initiating
an I/O request (e.g., I/O reads or writes). Moreover, such I/O
units can include one or more I/O controllers connected thereto,
and each of the I/O can be any of several types of I/O devices,
such as storage devices (e.g., a hard disk drive, tape drive) or
other I/O device. The hosts and I/O units and their attached I/O
controllers and devices can be organized into groups such as
clusters, with each cluster including one or more hosts and
typically one or more I/O units (each I/O unit including one or
more I/O controllers). The hosts and I/O units can be
interconnected via a collection of routers, switches and
communication links (such as wires, connectors, cables, and the
like) that connects a set of nodes (e.g., connects a set of hosts
and I/O units) of one or more clusters.
[0037] Furthermore, the wireless communication network can be
cellular or WLAN communication network; such as Global System for
Mobile communication (GSM) networks, Universal Mobile
Telecommunication System (UMTS) networks, and wireless Internet
Protocol (IP) networks like Voice over Internet Protocol (VOIP) and
IP Data networks. Accordingly, the portable device employed by
insurance providers 350, 352, 354 can be a hand-held wireless
communication device that can communicate with a wireless
communication network, (e.g. wireless communication network) to
further engage in an enriched text messaging in the written
communication environment. Such connections can be shared among the
insurance providers 350, 352, 354 which can employ, personal
computers, workstations, and any device capable of text messaging
such as mobile phones for example.
[0038] It is to be appreciated that the system can supply data to
insurance providers in accordance with determined and/or inferred
context as well as automatically generate queries in the background
as a function of user state. For example, a device (e.g., cell
phone, computing device, on-board computer system for a vehicle,
boat, plane, or machine, and the like) can dynamically generate
responses for queries in the background as a function of constantly
changing state, initiate searches in the background and cache
results for immediate viewing to the user. As an example, searches
of databases of detailed highway safety information, conditioned on
a current weather context, can be retrieved as a function of the
location and velocity of a user's vehicle. Moreover, the
driver/owner of the vehicle can be appropriately notified (e.g.,
via visual and/or audio signals) regarding a potential change of
insurance premiums. For example, immediate visual or audio feedback
can be supplied to the driver via a heads up display, as to provide
instantaneous notifications regarding change in driver's insurance
policy--while mitigating driving distractions (e.g., line of sight
for driver remains substantially unchanged.)
[0039] Accordingly, the subject innovation introduces two insurance
models, namely: 1) a user/driver complying with requirements of a
single insurance company to maintain current insurance rates; or 2)
different insurance companies bidding for the behavior of user not
willing to necessarily abide to requirements of an insurance
company. Moreover, the subject innovation can be implemented as
part of a system local to each motor vehicle (e.g., the rate
adjustment component and the switching component are positioned on
the motor vehicle); or part of a central management system, or a
combination thereof.
[0040] FIG. 4 illustrates a system 400 that determines location of
a vehicle 450 as part of customizing contextual data related to
driving behavior of an owner/user in real-time, according to an
aspect of the subject innovation. As explained earlier, the
real-time contextual driving data can include both an intensity
portion 465 and a frequency portion 475, which represent severity
and regularity of driving episodes/actions respectively (e.g.,
slamming the brakes, gradual/sudden deceleration, velocity
variances, and number of times such acts occur). Initially, a
geographic location for the vehicle can be determined via a GPS
positioning system 406, wherein such data can then be matched with
real-time weather and/or road conditions for the determined
location via the wireless network 410 and/or the IP network 416,
which interact with geographic maps serve 416 or weather server
420. In general, the geographic location data is determined by
receiving geographic location signals of a GPS (global positioning
system) technology. For example, the GPS can consist of a
constellation of twenty-four satellites each in its own orbit
approximately 11,000 miles above the earth. Each of the satellites
orbits the earth in about twelve hours, and the positions of which
are monitored by ground stations. The satellites each include
atomic clocks for extremely accurate timing (e.g., within three
nanoseconds of each other) that provides the capability to locate
the receiver (e.g., a handheld terrestrial receiver) on the earth
within, in some applications, one meter resolution.
[0041] The GPS location data can be received from a receiver (not
shown) which is, for example, a wireless assisted GPS (WAGPS)
device such as a GPS-enabled cellular telephone, GPS-enabled PDA,
and the like WAGPS facilitates the transmission of the GPS location
data from the receiver to a remote location. Generally, such can
occur through a cellular network (not shown) where the receiver is
a cellular telephone associated with insurance providers, to an IP
network (not shown) (e.g., the Internet), and terminating at the
remote location, node or device on the Internet or on a subnet
thereof.
[0042] When receiving geographic location signals from several of
the GPS satellites, the receiver can further calculate the distance
to each satellite of the communicating satellites and then
calculate its own position, on or above the surface of the earth.
It is to be appreciated, however, that the geographic location
technology can also include, for example, WiFi triangulation,
cellular telephone triangulation, radio frequency signal strengths,
and digital television signals.
[0043] FIG. 5 illustrates a particular methodology 500 of
customizing insurance rates according to a further aspect of the
subject innovation. While the exemplary method is illustrated and
described herein as a series of blocks representative of various
events and/or acts, the subject innovation is not limited by the
illustrated ordering of such blocks. For instance, some acts or
events may occur in different orders and/or concurrently with other
acts or events, apart from the ordering illustrated herein, in
accordance with the innovation. In addition, not all illustrated
blocks, events or acts, may be required to implement a methodology
in accordance with the subject innovation. Moreover, it will be
appreciated that the exemplary method and other methods according
to the innovation may be implemented in association with the method
illustrated and described herein, as well as in association with
other systems and apparatus not illustrated or described. Initially
and at 510 contextual data from various data banks can be accessed
by the insurance providers or supplied thereto. As explained
earlier, the data banks can include data pertaining to the motor
vehicle (e.g., maintenance history, current vehicle conditions, and
the like); data related to the driver (e.g., via health insurance
records, police records, internet records, and the like); and data
related to operating environment (e.g., weather, geographical
location, and the like.) Moreover, the real-time contextual driving
data can include both an intensity portion and a frequency portion,
which represent severity and regularity of driving episodes (e.g.,
slamming the brakes, gradual/sudden deceleration, velocity
variances, and the like). Subsequently and at 520, such data can be
analyzed by the insurance providers as to customize an insurance
rate based thereon at 530. Subsequently, the customized insurance
rate can then be sent from an insurance provider to an owner/user
of the vehicle (e.g., in form of an insurance bid) at 540.
[0044] FIG. 6 illustrates a related methodology 600 of switching
insurance to a policy with an optimal rate according to a further
aspect of the subject innovation. Initially threshold ranges and/or
discrete values can be set by the user/owner of the vehicle. For
example, such threshold values and/or discrete ranges can relate to
pricing ranges that the owner/user will consider or will not
consider at all, various terms of the insurance policy such as
minimum amount of liability desired, number of drivers that
user/owner desires to be included in the policy, and the like. Such
thresholds can facilitate determining whether an insurance bid
should be considered and/or out right rejected. At 620, the
insurance bids can be obtained from the insurance providers, and an
optimal insurance rate selected at 630. The insurance policy can
then be switched (e.g., automatically) to such optimal rate. Hence,
during a trip the user/driver can actually be insured by various
suppliers during different segments of such trip--(each of which
supplied an optimal rate for the trip segment that switching
thereto occurred.)
[0045] FIG. 7 illustrates exemplary system 700 that collects
contextual data related to acquiring biometrics from a driver/owner
701 of a vehicle 704 (e.g., in real time) to facilitate customizing
an insurance policy and further switching the user/owner 701 to an
optimal policy. In one particular aspect, values such as a
biometric data (e.g., temperature, blood sugar level, and the like)
can be asynchronously read via sensor of the modular component 708
and output values can be written directly to the I/O table by slave
processors for subsequent communication to the process by
specialized communications circuitry.
[0046] During execution of a control routine, (e.g., real time
monitoring of blood sugar level), values of the inputs and outputs
exchanged with and/or acquired by the components 711, 712, 713, 714
and/or controlled process for data collection, can pass through the
I/O table. The values of inputs in the I/O table can further be
asynchronously updated from the controlled process by dedicated
modular components. Moreover, modality specific circuitry can
communicate with input and/or output modules over a bus on a
backplane or network communications. The modality specific
circuitry can also asynchronously write values of the outputs in
the I/O table to the controlled process of data collection. The
output values from the I/O table can then be communicated to one or
more of the modular components and/ or associated output modules
for interfacing with the process of data collection. Thus, a slave
processor(s) can simply access the I/O table rather than needing to
communicate directly with the master processor and/or controlled
process of data collection.
[0047] For example, the system 700 can be adapted to acquire data
related to Electromyography (EMG, frequency range 2-500 Hz),
Electrocardiography (ECG, frequency range 0.05-100 Hz, resolution
of 24 bits), Electroencephalography (EEG, frequency range 0.16-100
Hz), blood pressure, and the like. The system can employ a Common
Data Controller, which has a Bus Interface, I/O functions
(controls), and a module clock. The Bus Interface can coordinate
activities of the system 700 with a bus controller of the master
controller (not shown), for transmittal of biometric indicia (e.g.,
medical parameter data) and reception of control data.
[0048] Likewise, the I/O functions can control operation for the
specific circuitry (e.g., specific to EKG, EEG, and the like).
Typically, the system 700 (e.g., required for a controlled data
collection, such as collecting/monitoring blood sugar in real time)
can be connected to other modular components on a common backplane
through a network or other communications medium. As explained
earlier, the system 700 can include processors, power supplies,
network communication modules, and I/O modules exchanging input and
output signals directly with the master controller and/or the
controlled process. Data may be exchanged between modules using a
backplane communications bus, which may be serial or parallel, or
via a network.
[0049] In addition to performing I/O operations based solely on
network communications, smart modules can be employed that can
execute autonomous logical or other control programs or routines. A
RAM memory medium can function as a data storage medium for
buffering of collected, so that data is not lost when the system
bus is in use by other functions. Such memory also enables
asynchronous data collection. Additionally, the module clock
provides for timing on a modular component for data collection
functions. The module clock supplies timing for data collection
functions, and enables synchronous collection of data for supplying
to insurance providers.
[0050] It is to be appreciated that various sensor components for a
distributed controlled data collection system can be spatially
distributed along a common communication link, such as a belt 716
around a user's body as illustrated in FIG. 7. Certain components
can thus be located proximate to predetermined portions of a
driver's body. Data can be communicated with such modular
components 711, 712, 713, 714 over a common communication link, or
network, wherein all modules on the network communicate via a
standard communications protocol.
[0051] Likewise, sensor can be distributed at various location of
the vehicle 704 to monitor health of the vehicle and driving
behavior of user (e.g., on gas pedal, steering wheel, and the
like). Similarly, in such a distributed control system of the
vehicle 704, one or more I/O modules are provided for interfacing
with a data collection process, wherein the outputs derive their
control or output values in the form of a message from a master
controller over a network or a backplane. For example, a sensor
component can receive an output value from a processor, via a
communications network or a backplane communications bus. The
desired output value for controlling data collection associated
with biometric indicia can be generally sent to the output module
in a message, such as an I/O message. The system 700 that receives
such a message can provide a corresponding output (analog or
digital) to the controlled process for data collection. The system
700 can also measure a value of a process variable and report the
input values to a master controller or peer modular component over
a network or backplane. The input values can further be employed by
the master processor for performing control computations.
[0052] FIG. 8 illustrates a system 800 with an inference component
830 that can facilitate customizing insurance rates based on
contextual data and switching to an optimal rate based thereon. As
used herein, the term "inference" refers generally to the process
of reasoning about or inferring states of the system, environment,
and/or user from a set of observations as captured via events
and/or data. Inference can be employed to identify a specific
context or action, or can generate a probability distribution over
states, for example. The inference can be probabilistic--that is,
the computation of a probability distribution over states of
interest based on a consideration of data and events. Inference can
also refer to techniques employed for composing higher-level events
from a set of events and/or data. Such inference results in the
construction of new events or actions from a set of observed events
and/or stored event data, whether or not the events are correlated
in close temporal proximity, and whether the events and data come
from one or several event and data sources.
[0053] For example a process for determining an insurance rate can
be facilitated via an automatic classifier system and process. A
classifier is a function that maps an input attribute vector,
x=(x1, x2, x3, x4, xn), to a confidence that the input belongs to a
class, that is, f(x)=confidence(class). Such classification can
employ a probabilistic and/or statistical-based analysis (e.g.,
factoring into the analysis utilities and costs) to prognose or
infer an action that a user desires to be automatically
performed.
[0054] A support vector machine (SVM) is an example of a classifier
that can be employed. The SVM operates by finding a hypersurface in
the space of possible inputs, which hypersurface attempts to split
the triggering criteria from the non-triggering events.
Intuitively, this makes the classification correct for testing data
that is near, but not identical to training data. Other directed
and undirected model classification approaches include, e.g., naive
Bayes, Bayesian networks, decision trees, neural networks, fuzzy
logic models, and probabilistic classification models providing
different patterns of independence can be employed. Classification
as used herein also is inclusive of statistical regression that is
utilized to develop models of priority.
[0055] As will be readily appreciated from the subject
specification, the subject invention can employ classifiers that
are explicitly trained (e.g., via a generic training data) as well
as implicitly trained (e.g., via observing user behavior, receiving
extrinsic information). For example, SVM's are configured via a
learning or training phase within a classifier constructor and
feature selection module. Thus, the classifier(s) can be used to
automatically learn and perform a number of functions, including
but not limited to determining according to a predetermined
criteria when to update or refine the previously inferred schema,
tighten the criteria on the inferring algorithm based upon the kind
of data being processed (e.g., type of contextual data, real time
driving behavior and the like.)
[0056] FIG. 9 illustrates a further aspect of the subject
innovation that employs a plurality of cameras 901, 902, 903, 904,
905 to facilitate collection of contextual data, and/or for
accident analysis. In one particular aspect, any of the cameras
901. 902, 903, 904 and 905 can include a monitor shell having a
monitor lens on the outside and a charge-coupled device (CCD) on
the inside. Such camera can further include a motherboard shell
with motherboard peripheral circuits on the inside, and a
transmission line can electrically couple the motherboard and the
CDD--wherein an image output line can be additionally mounted on
the motherboard. It is to be appreciated that the cameras can be
mounted on various locations, such as by mounting the motherboard
on the inside of the car trunk apart from a car bumper, for
example. It is further to be appreciated that other type of cameras
such as metal oxide semiconductor (CMOS) cameras, infrared cameras,
and the like can be employed to transfer data to insurance
providers via buffers 916, 918, 920 (1 to k, where k is an
integer).
[0057] As illustrated by the exemplary system 910, a threading and
communication architecture can be employed to facilitate
interaction of the cameras 901, 902, 903, 904, 905 with the
insurance provider(s) 950. The system 910 includes two threads,
namely, a camera interface thread 912 and an instruction thread
914. The camera interface thread 912 can process user interface
activity of the cameras, such as managing commands, menus and the
like. Likewise, the instruction thread 914 provides instructions
for retrieving of data to and from the cameras and their associated
applications.
[0058] The two threads 912 and 914 are operatively linked or
connected through one or more buffers 916, 918, and 920. Each
buffer 916, 918, 920 can hold information retrieved from the
cameras for a predetermined time, as well as queues commands and
requests from the camera interface thread 912 to the instruction
thread 914. The buffers 916, 918, and 920 can further serve as a
synchronization system between the threads.
[0059] For example, when an application associated with a camera is
initiated, initially only one interface thread such as 912 can
become active. The interface thread 912 can perform application
initialization operations, such as creation of the initial GUI
elements, command-line parsing, and the like. The camera interface
thread 912 also gathers information about the process to be
performed from command-line arguments, menu selections and dialog
boxes.
[0060] The instruction thread 914 can be responsible for all major
use of the associated cameras such as view angle, pixel size,
number of frames collected per second, and the like. The
instruction thread 914 can supply a queue of commands to the camera
interface thread 912, such as data being stored in buffers 916,
918, and 920, and by carrying out active requests. Accordingly,
buffers can be refilled, wherein data that has been expired (e.g.,
after a predetermined period such as several minutes) can be
discarded. The predetermined period can further be extended by the
insurance provider(s) 950, such as when an accident occurs and the
driver contacts the insurance provider--and hence data related to
the accident can be preserved.
[0061] The word "exemplary" is used herein to mean serving as an
example, instance or illustration. Any aspect or design described
herein as "exemplary" is not necessarily to be construed as
preferred or advantageous over other aspects or designs. Similarly,
examples are provided herein solely for purposes of clarity and
understanding and are not meant to limit the subject innovation or
portion thereof in any manner. It is to be appreciated that a
myriad of additional or alternate examples could have been
presented, but have been omitted for purposes of brevity.
[0062] Furthermore, all or portions of the subject innovation can
be implemented as a system, method, apparatus, or article of
manufacture using standard programming and/or engineering
techniques to produce software, firmware, hardware or any
combination thereof to control a computer to implement the
disclosed innovation. For example, computer readable media can
include but are not limited to magnetic storage devices (e.g., hard
disk, floppy disk, magnetic strips . . . ), optical disks (e.g.,
compact disk (CD), digital versatile disk (DVD) . . . ), smart
cards, and flash memory devices (e.g., card, stick, key drive . . .
). Additionally it should be appreciated that a carrier wave can be
employed to carry computer-readable electronic data such as those
used in transmitting and receiving electronic mail or in accessing
a network such as the Internet or a local area network (LAN). Of
course, those skilled in the art will recognize many modifications
may be made to this configuration without departing from the scope
or spirit of the claimed subject matter.
[0063] Furthermore, all or portions of the subject innovation can
be implemented as a system, method, apparatus, or article of
manufacture using standard programming and/or engineering
techniques to produce software, firmware, hardware or any
combination thereof to control a computer to implement the
disclosed innovation. For example, computer readable media can
include but are not limited to magnetic storage devices (e.g., hard
disk, floppy disk, magnetic strips . . . ), optical disks (e.g.,
compact disk (CD), digital versatile disk (DVD) . . . ), smart
cards, and flash memory devices (e.g., card, stick, key drive . . .
). Additionally it should be appreciated that a carrier wave can be
employed to carry computer-readable electronic data such as those
used in transmitting and receiving electronic mail or in accessing
a network such as the Internet or a local area network (LAN). Of
course, those skilled in the art will recognize many modifications
may be made to this configuration without departing from the scope
or spirit of the claimed subject matter.
[0064] In order to provide a context for the various aspects of the
disclosed subject matter, FIGS. 10 and 11 as well as the following
discussion are intended to provide a brief, general description of
a suitable environment in which the various aspects of the
disclosed subject matter may be implemented. While the subject
matter has been described above in the general context of
computer-executable instructions of a computer program that runs on
a computer and/or computers, those skilled in the art will
recognize that the innovation also may be implemented in
combination with other program modules.
[0065] As used in this application, the terms "component",
"system", "engine" are intended to refer to a computer-related
entity, either hardware, a combination of hardware and software,
software, or software in execution. For example, a component can
be, but is not limited to being, a process running on a processor,
a processor, an object, an executable, a thread of execution, a
program, and/or a computer. By way of illustration, both an
application running on a server and the server can be a component.
One or more components can reside within a process and/or thread of
execution, and a component can be localized on one computer and/or
distributed between two or more computers.
[0066] Generally, program modules include routines, programs,
components, data structures, and the like, which perform particular
tasks and/or implement particular abstract data types. Moreover,
those skilled in the art will appreciate that the innovative
methods can be practiced with other computer system configurations,
including single-processor or multiprocessor computer systems,
mini-computing devices, mainframe computers, as well as personal
computers, hand-held computing devices (e.g., personal digital
assistant (PDA), phone, watch . . . ), microprocessor-based or
programmable consumer or industrial electronics, and the like. The
illustrated aspects may also be practiced in distributed computing
environments where tasks are performed by remote processing devices
that are linked through a communications network. However, some, if
not all aspects of the innovation can be practiced on stand-alone
computers. In a distributed computing environment, program modules
may be located in both local and remote memory storage devices.
[0067] With reference to FIG. 10, an exemplary environment 1010 for
implementing various aspects of the subject innovation is described
that includes a computer 1012. The computer 1012 includes a
processing unit 1014, a system memory 1016, and a system bus 1018.
The system bus 1018 couples system components including, but not
limited to, the system memory 1016 to the processing unit 1014. The
processing unit 1014 can be any of various available processors.
Dual microprocessors and other multiprocessor architectures also
can be employed as the processing unit 1014.
[0068] The system bus 1018 can be any of several types of bus
structure(s) including the memory bus or memory controller, a
peripheral bus or external bus, and/or a local bus using any
variety of available bus architectures including, but not limited
to, 11-bit bus, Industrial Standard Architecture (ISA),
Micro-Channel Architecture (MSA), Extended ISA (EISA), Intelligent
Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component
Interconnect (PCI), Universal Serial Bus (USB), Advanced Graphics
Port (AGP), Personal Computer Memory Card International Association
bus (PCMCIA), and Small Computer Systems Interface (SCSI).
[0069] The system memory 1016 includes volatile memory 1020 and
nonvolatile memory 1022. The basic input/output system (BIOS),
containing the basic routines to transfer information between
elements within the computer 1012, such as during start-up, is
stored in nonvolatile memory 1022. By way of illustration, and not
limitation, nonvolatile memory 1022 can include read only memory
(ROM), programmable ROM (PROM), electrically programmable ROM
(EPROM), electrically erasable ROM (EEPROM), or flash memory.
Volatile memory 1020 includes random access memory (RAM), which
acts as external cache memory. By way of illustration and not
limitation, RAM is available in many forms such as synchronous RAM
(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data
rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM
(SLDRAM), and direct Rambus RAM (DRRAM).
[0070] Computer 1012 also includes removable/non-removable,
volatile/non-volatile computer storage media. FIG. 10 illustrates a
disk storage 1024, wherein such disk storage 1024 includes, but is
not limited to, devices like a magnetic disk drive, floppy disk
drive, tape drive, Jaz drive, Zip drive, LS-60 drive, flash memory
card, or memory stick. In addition, disk storage 1024 can include
storage media separately or in combination with other storage media
including, but not limited to, an optical disk drive such as a
compact disk ROM device (CD-ROM), CD recordable drive (CD-R Drive),
CD rewritable drive (CD-RW Drive) or a digital versatile disk ROM
drive (DVD-ROM). To facilitate connection of the disk storage
devices 1024 to the system bus 1018, a removable or non-removable
interface is typically used such as interface 1026.
[0071] It is to be appreciated that FIG. 10 describes software that
acts as an intermediary between users and the basic computer
resources described in suitable operating environment 1010. Such
software includes an operating system 1028. Operating system 1028,
which can be stored on disk storage 1024, acts to control and
allocate resources of the computer system 1012. System applications
1030 take advantage of the management of resources by operating
system 1028 through program modules 1032 and program data 1034
stored either in system memory 1016 or on disk storage 1024. It is
to be appreciated that various components described herein can be
implemented with various operating systems or combinations of
operating systems.
[0072] A user enters commands or information into the computer 1012
through input device(s) 1036. Input devices 1036 include, but are
not limited to, a pointing device such as a mouse, trackball,
stylus, touch pad, keyboard, microphone, joystick, game pad,
satellite dish, scanner, TV tuner card, digital camera, digital
video camera, web camera, and the like. These and other input
devices connect to the processing unit 1014 through the system bus
1018 via interface port(s) 1038. Interface port(s) 1038 include,
for example, a serial port, a parallel port, a game port, and a
universal serial bus (USB). Output device(s) 1040 use some of the
same type of ports as input device(s) 1036. Thus, for example, a
USB port may be used to provide input to computer 1012, and to
output information from computer 1012 to an output device 1040.
Output adapter 1042 is provided to illustrate that there are some
output devices 1040 like monitors, speakers, and printers, among
other output devices 1040 that require special adapters. The output
adapters 1042 include, by way of illustration and not limitation,
video and sound cards that provide a means of connection between
the output device 1040 and the system bus 1018. It should be noted
that other devices and/or systems of devices provide both input and
output capabilities such as remote computer(s) 1044.
[0073] Computer 1012 can operate in a networked environment using
logical connections to one or more remote computers, such as remote
computer(s) 1044. The remote computer(s) 1044 can be a personal
computer, a server, a router, a network PC, a workstation, a
microprocessor based appliance, a peer device or other common
network node and the like, and typically includes many or all of
the elements described relative to computer 1012. For purposes of
brevity, only a memory storage device 1046 is illustrated with
remote computer(s) 1044. Remote computer(s) 1044 is logically
connected to computer 1012 through a network interface 1048 and
then physically connected via communication connection 1050.
Network interface 1048 encompasses communication networks such as
local-area networks (LAN) and wide-area networks (WAN). LAN
technologies include Fiber Distributed Data Interface (FDDI),
Copper Distributed Data Interface (CDDI), Ethernet/IEEE 802.3,
Token Ring/IEEE 802.5 and the like. WAN technologies include, but
are not limited to, point-to-point links, circuit switching
networks like Integrated Services Digital Networks (ISDN) and
variations thereon, packet switching networks, and Digital
Subscriber Lines (DSL).
[0074] Communication connection(s) 1050 refers to the
hardware/software employed to connect the network interface 1048 to
the bus 1018. While communication connection 1050 is shown for
illustrative clarity inside computer 1012, it can also be external
to computer 1012. The hardware/software necessary for connection to
the network interface 1048 includes, for exemplary purposes only,
internal and external technologies such as, modems including
regular telephone grade modems, cable modems and DSL modems, ISDN
adapters, and Ethernet cards.
[0075] FIG. 11 is a schematic block diagram of a sample-computing
environment 1100 that can be employed for customizing insurance
rates according to an aspect of the subject innovation. The system
1100 includes one or more client(s) 1110. The client(s) 1110 can be
hardware and/or software (e.g., threads, processes, computing
devices). The system 1100 also includes one or more server(s) 1130.
The server(s) 1130 can also be hardware and/or software (e.g.,
threads, processes, computing devices). The servers 1130 can house
threads to perform transformations by employing the components
described herein, for example. One possible communication between a
client 1110 and a server 1130 may be in the form of a data packet
adapted to be transmitted between two or more computer processes.
The system 1100 includes a communication framework 1150 that can be
employed to facilitate communications between the client(s) 1110
and the server(s) 1130. The client(s) 1110 are operatively
connected to one or more client data store(s) 1160 that can be
employed to store information local to the client(s) 1110.
Similarly, the server(s) 1130 are operatively connected to one or
more server data store(s) 1140 that can be employed to store
information local to the servers 11 30.
[0076] What has been described above includes various exemplary
aspects. It is, of course, not possible to describe every
conceivable combination of components or methodologies for purposes
of describing these aspects, but one of ordinary skill in the art
may recognize that many further combinations and permutations are
possible. Accordingly, the aspects described herein are intended to
embrace all such alterations, modifications and variations that
fall within the spirit and scope of the appended claims.
[0077] Furthermore, to the extent that the term "includes" is used
in either the detailed description or the claims, such term is
intended to be inclusive in a manner similar to the term
"comprising" as "comprising" is interpreted when employed as a
transitional word in a claim.
* * * * *