U.S. patent application number 13/037095 was filed with the patent office on 2011-09-01 for smart power strip.
Invention is credited to Koorosh Mozayeny.
Application Number | 20110213510 13/037095 |
Document ID | / |
Family ID | 44504651 |
Filed Date | 2011-09-01 |
United States Patent
Application |
20110213510 |
Kind Code |
A1 |
Mozayeny; Koorosh |
September 1, 2011 |
SMART POWER STRIP
Abstract
A power strip includes a controller that controls the transfer
of electricity to one or more outlet electrical connectors based at
least in part on a set of rules and certain status information.
Some embodiments provide for apparatuses and methods of controlling
the transfer of electricity to one or more outlet electrical
connectors of a power strip based on various status information,
such as cost, personal preferences, time information, power
consumption.
Inventors: |
Mozayeny; Koorosh; (Newport
Beach, CA) |
Family ID: |
44504651 |
Appl. No.: |
13/037095 |
Filed: |
February 28, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61309363 |
Mar 1, 2010 |
|
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Current U.S.
Class: |
700/297 |
Current CPC
Class: |
H02J 3/14 20130101; Y02B
70/3225 20130101; H02J 3/00 20130101; Y04S 20/222 20130101; A61M
5/1723 20130101; H01R 25/003 20130101; G06F 1/26 20130101; A61M
2230/201 20130101 |
Class at
Publication: |
700/297 |
International
Class: |
G06F 1/26 20060101
G06F001/26 |
Claims
1. A power strip comprising: a first inlet electrical connector
configured to be plugged into a first electrical socket and to
receive an input of electricity from the first electrical socket;
one or more outlet electrical connectors electrically coupled to
the first inlet electrical connector and configured to receive a
second inlet electrical connector of an energy consuming device for
transmission of at least a portion of the electricity from the
first inlet electrical connector to the energy consuming device;
and a controller configured to control the transfer of electricity
from the first inlet electrical connector to the one or more outlet
electrical connectors based at least in part on a set of rules and
status information related to the set of rules.
2. The power strip of claim 1, wherein the status information
comprises electricity rate information.
3. The power strip of claim 1, wherein the status information
comprises information related to personal preferences of a
user.
4. The power strip of claim 1, wherein the status information
comprises energy demands of the energy consuming device.
5. The power strip of claim 1, wherein the status information
comprises time of day and/or day of week information.
6. The power strip of claim 1, wherein the controller is further
configured to receive information from a smart meter and to control
the input of electricity to the one or more outlet electrical
connectors based on the information.
7. The power strip of claim 1, wherein the controller is further
configured to receive feedback information from the energy
consuming device and to control the input of electricity to the one
or more outlet electrical connectors based on the feedback
information.
8. The power strip of claim 1, configured to receive information
from a smart grid electrical system.
9. The power strip of claim 8, wherein the status information
comprises information received from the smart grid electrical
system.
10. The power strip of claim 1, wherein the controller is
programmable by a user.
11. A method of regulating the distribution of electrical energy
comprising: providing a power strip comprising: a first inlet
electrical connector configured to be plugged into a first
electrical socket and to receive an input of electricity from the
first electrical socket; and one or more outlet electrical
connectors electrically coupled to the first inlet electrical
connector and configured to receive a second inlet electrical
connector of an energy consuming device for transmission of at
least a portion of the electricity from the first inlet electrical
connector to the energy consuming device; and controlling the
transfer of electricity from the first inlet electrical connector
to the one or more outlet electrical connectors based at least in
part on a set of rules and status information related to the set of
rules.
Description
RELATED APPLICATIONS
[0001] This application claims the benefit under 35 U.S.C.
.sctn.119(e) of U.S. Provisional Patent Application No. 61/309,363,
titled FLOW OPTIMIZER DECISION DEVICE, filed Mar. 1, 2010, the
entire contents of which are incorporated by reference herein and
made a part of this specification. This application is also related
to U.S. Application No. XX/XXX,XXX, entitled "Medication Delivery
System," and U.S. Application No. XX/XXX,XXX, entitled "Water Flow
Regulation System," which were filed on the same day as the present
application and are hereby incorporated by reference in their
entirety.
BACKGROUND
[0002] 1. Field
[0003] The present disclosure relates generally to smart power
strips.
[0004] 2. Description of the Related Art
[0005] Power strips are commonly employed for powering electronic
appliances, including computer systems, high fidelity and stereo
equipment, home theatre installations and the like. Current sensing
devices are known in the art for controlling the power supplied by
one or more secondary electrical outlets of a power strip. However,
power strips have not previously had the capability of controlling
the power supplied to secondary outlets based on a set of
rules.
SUMMARY
[0006] Embodiments described herein have several features, no
single one of which is solely responsible for their desirable
attributes. Without limiting the scope of the inventions as
expressed by the claims, some of the advantageous features will now
be discussed briefly.
[0007] Some embodiments provide a power strip comprising a first
inlet electrical connector configured to be plugged into a first
electrical socket and to receive an input of electricity from the
first electrical socket, one or more outlet electrical connectors
electrically coupled to the first inlet electrical connector and
configured to receive a second inlet electrical connector of an
energy consuming device for transmission of at least a portion of
the electricity from the first inlet electrical connector to the
energy consuming device, and a controller configured to control the
transfer of electricity from the first inlet electrical connector
to the one or more outlet electrical connectors based at least in
part on a set of rules and status information related to the set of
rules.
[0008] The status information can include electricity rate
information, information related to personal preferences of a user,
energy demands of the energy consuming device, time of day and/or
day of week information, information received from a smart grid
electrical system, or other information.
[0009] The controller can be further configured to receive
information from a smart meter and to control the input of
electricity to the one or more outlet electrical connectors based
on the information. The controller can be further configured to
receive feedback information from the energy consuming device and
to control the input of electricity to the one or more outlet
electrical connectors based on the feedback information. The
controller may be programmable by a user.
[0010] Some embodiments provide a method of regulating the
distribution of electrical energy comprising providing a power
strip comprising a first inlet electrical connector configured to
be plugged into a first electrical socket and to receive an input
of electricity from the first electrical socket, and one or more
outlet electrical connectors electrically coupled to the first
inlet electrical connector and configured to receive a second inlet
electrical connector of an energy consuming device for transmission
of at least a portion of the electricity from the first inlet
electrical connector to the energy consuming device, and
controlling the transfer of electricity from the first inlet
electrical connector to the one or more outlet electrical
connectors based at least in part on a set of rules and status
information related to the set of rules.
[0011] For purposes of this summary, certain aspects, advantages,
and novel features of the invention are described herein. It is to
be understood that not necessarily all such aspects, advantages,
and features may be employed and/or achieved in accordance with any
particular embodiment of the invention. Thus, for example, those
skilled in the art will recognize that the invention may be
embodied or carried out in a manner that achieves one advantage or
group of advantages as taught herein without necessarily achieving
other advantages as may be taught or suggested herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] Various embodiments are depicted in the accompanying
drawings for illustrative purposes, and should in no way be
interpreted as limiting the scope of the inventive subject matter.
In addition, various features of different disclosed embodiments
can be combined to form additional embodiments, which are part of
this disclosure.
[0013] FIG. 1 illustrates an embodiment of a smart power strip.
[0014] FIG. 2 illustrates an embodiment of a energy management
system.
[0015] FIG. 3 illustrates an embodiment of a meter for a smart
appliance.
[0016] FIG. 4 illustrates an embodiment of an electrical flow
regulation system.
[0017] FIG. 5 illustrates an embodiment of an electrical flow
regulation system.
[0018] FIG. 6 illustrates an embodiment of a water management
system.
[0019] FIG. 7 illustrates an embodiment of a cash flow management
system.
[0020] FIG. 8 illustrates an embodiment of a cash flow management
system.
[0021] FIGS. 9 and 9A-9B illustrate an embodiment of a flow chart
of a flow management system.
[0022] FIGS. 10 and 10A-10C illustrate an embodiment of a flow
chart of a flow management system.
[0023] FIGS. 11 and 11A-11B illustrate an embodiment of a flow
chart of a flow management system.
[0024] FIG. 12 illustrates an embodiment of a flow chart of a flow
management system.
[0025] FIG. 13 illustrates an embodiment of a medication-
distribution management system.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0026] Although certain preferred embodiments and examples are
disclosed below, inventive subject matter extends beyond the
specifically disclosed embodiments to other alternative embodiments
and/or uses and to modifications and equivalents thereof. Thus, the
scope of the claims that may arise herefrom is not limited by any
of the particular embodiments described below. For example, in any
method or process disclosed herein, the acts or operations of the
method or process may be performed in any suitable sequence and are
not necessarily limited to any particular disclosed sequence.
Various operations may be described as multiple discrete operations
in turn, in a manner that may be helpful in understanding certain
embodiments; however, the order of description should not be
construed to imply that these operations are order dependent.
[0027] Additionally, the structures, systems, and/or devices
described herein may be embodied as integrated components or as
separate components. For purposes of comparing various embodiments,
certain aspects and advantages of these embodiments are described.
Not necessarily all such aspects or advantages are achieved by any
particular embodiment. Thus, for example, various embodiments may
be carried out in a manner that achieves or optimizes one advantage
or group of advantages as taught herein without necessarily
achieving other aspects or advantages as may also be taught or
suggested herein.
Flow Optimizer Decision Device (FODD)
[0028] A Flow Optimizer Decision Device (FODD) may be a hardware
device. The device may use one or more algorithms to calculate and
make complex decisions on how to distribute one-directional or
bi-directional flows in a grid. Regulation of flow using a hardware
device may provide certain advantages relating to the ability to
make decisions in a limited time frame or even in real-time.
Moreover, calculations relating to the regulation or optimization
of flow may become significantly more intricate in connection with
complex criterion matrices. These, as well as other considerations
indicate the desirability of a dedicated hardware device for
regulating flow. Such devices often communicate with one or more
sensors (e.g., remote sensors) and make decisions in real-time.
FODD is such a device.
[0029] Embodiments in which a FODD is a dedicated hardware device
may provide a number of benefits, such as facilitating increased
system security. For example, a dedicated hardware device may be a
component of a proprietary system. Proprietary systems may be more
difficult for hackers or other persons or systems to infiltrate.
Such security may provided added protection of privacy, resources,
system integrity, etc.
[0030] In certain embodiments, a hardware device may be required
for proper function of the FODD. For example, in a medical
environment, a FODD may be implanted in a patient. In water or
electricity distribution system environments, utilities may have
their own interface with which a FODD may communicate. With further
reference to water distribution, in an exemplary home sprinkler
system, it may be impractical, or expensive to run a FODD system as
software on a separate computer system, and therefore a dedicated
FODD device may be desired.
[0031] A FODD may be suitable in applications that require
controlling flow (e.g., of physical matter, resources, goods,
supply chains, energy, data, etc.) based on criteria represented in
or by static or dynamic criterion matrices. As is apparent with
respect to the exemplary flow charts in FIGS. 9-12, a FODD can use
one or more criterion matrices to regulate the distribution of the
flow of a relevant parameter. Criterion in a criterion matrix may
include, relate to, or be based on certain status information
relating to the particular system of which the FODD is a part. A
FODD may be a bi-directional device that is capable of handling
positive as well as negative flows. In certain embodiments,
bi-directional flow regulation may be achieved through the use of
separate negative and positive flow criterion matrices. A FODD may
operate in connection with a criterion matrix that is configured to
be automatically modified in accordance with preferences "learned"
by the system, i.e., the FODD may be configured to adapt to
accommodate or reflect certain perceived preferences, behaviors,
conditions, etc.
[0032] The application of FODD devices in various fields is vast,
however, to demonstrate the devices' use, embodiments are disclosed
herein in the context of the following exemplary fields: 1)
Distribution of electrical power, such as in connection with the
new Smart Grid Electrical system, 2) distribution of water, such as
in irrigation systems, 3) delivery of medication to a patient, and
4) distribution of economic resources, e.g., vis-a-vis cash flow
between and among business partners ("Partner Cash Flow
Analysis").
Electrical Grid System
[0033] In certain embodiments, a FODD may be used to optimize and
coordinate the flow of electrical energy within an electrical
system. For example, implementation of a FODD may be desirable for
distributing electrical flow in the new smart grid system being
implemented in various municipalities throughout the world. While
certain currently implemented flow regulation systems involve
one-way manual flow distribution, certain systems incorporating a
FODD may implement a two-way communication flow system. Smart grid
is used to control the delivery of electricity to end users or
customers by monitoring and controlling the end user's appliances.
Countries such as France, England, China, and US are moving rapidly
to this new system.
[0034] Therefore, the electrical industry is being transformed from
a centralized producer-controlled network to one that is less
centralized. This two-way flow of electricity and information will
be capable of monitoring everything from power plants to customer
preferences to individual appliances.
[0035] Many countries are adopting the smart grid system. Please
note the following examples:
[0036] Canada
[0037] The government of Ontario, Canada, through the Energy
Conservation Responsibility Act in 2006, has mandated the
installation of Smart Meters in all Ontario businesses and
households by 2010.
[0038] China
[0039] On May 21, 2009, China has announced an aggressive framework
for Smart Grid deployment. As part of its current 5-year plan,
China is building a Wide Area Monitoring system (WAMS) and by 2012
plans to have PMU sensors at all generators of 300 megawatts and
above, and all substations of 500 kilovolts and above.
[0040] European Union
[0041] Development of smart grid technologies is part of the
European Technology Platform (ETP) initiative and is called the
Smart Grids Technology platform. The Smart Grids European
Technology Platform for Electricity Networks of the Future began
its work in 2005. Its aim is to formulate and promote a vision for
the development of European electricity networks looking towards
2020 and beyond
[0042] United States
[0043] Support for smart grids became federal policy with passage
of the Energy Independence and Security Act of 2007. The law,
Title13, sets out $100 million in funding per fiscal year from
2008-2012, establishes a matching program to states, utilities and
consumers to build smart grid capabilities, and creates a Grid
Modernization Commission to assess the benefits of demand response
and to recommend needed protocol standards. The Energy Independence
and Security Act of 2007 directs the National Institute of
Standards and Technology to coordinate the development of smart
grid standards, which FERC would then promulgate through official
rulemakings.
Electricity Distribution System
[0044] In certain embodiments, a Flow Optimizer Decision Device
(FODD) algorithm and computer model can be used to: a) control and
optimize the use of various user's appliances in light of cost
matrices and user criterion requirements, among other possible uses
b) help generate cost matrices to be used to set utility prices,
and c).control and optimize the flow of electricity between various
power stations, homes, offices, factories, etc. [0045] A. Control
and Optimization of Use of Various User Appliances in Light of Cost
Matrices and Users Criterion Requirements
[0046] In certain embodiments, a cost matrix (cost to the user) is
calculated and transmitted to an end user. In certain embodiments,
this information, together with the new smart meters being
implemented, may help determine the cost of energy to the end user
at a given time.
[0047] As discussed in further detail below, the user, like a
utility company, for example, may have its own criterion matrix.
The user criterion matrix may include information relating to
various parameters and/or user preferences. In certain embodiments,
the parameters and/or preferences are manually input by a user.
This could be done in several ways, including, for example, through
the use of a computer questionnaire or form. This matrix would
describe the user's preferences.
[0048] For example, a user may not like to run the pool heater if
the cost of electricity reaches a certain amount. This information
may be inside the user's preference/criterion matrix. In certain
embodiments, the parameters and/or preferences are set
automatically. For example, parameters or preferences may be
learned by the system based on the electricity usage practices of
the user. The FODD may act as a form of "artificial intelligence,"
wherein parameters or preferences are set or modified without
required user input. This may be beneficial in scenarios where a
user/consumer has inadequate time or desire to modify or otherwise
input information relating to parameters or preferences. The
following example may help explain the attributes of such an
embodiment: a homeowner returns home from work in the evening and
therefore does not use the home's water supply during the day. A
FODD-based water heating system therefore may "learn" that there is
no need to maintain water temperature levels during the middle of
the day. The Flow Optimizer Decision Device (FODD) may use the
user's criterion matrix to make decisions on which appliance(s) to
turn on or off in light of the current cost matrix transmitted by
the utility companies. In certain embodiments, the FODD makes
decisions relating to the distribution of electrical energy based
on a user end criterion matrix, without input from an electricity
provider. The FODD can be configured to make decisions in
real-time.
[0049] It may be beneficial to implement a FODD in connection with
smart appliances, which may be configured to access a smart grid,
as discussed above, and operate accordingly. However, not all
appliances currently in use are smart appliances. Use of
"Smart-Grid" technology and associated variable power rate
structure might have required a user to obtain a new set of "smart"
appliances. However, users of legacy devices may not want to
discard existing, non-"smart," appliances. A "Smart Power Strip"
may provide the option to appliance users to maintain use of legacy
devices and still take advantage of smart grid technology. In
certain embodiments, if a user plugs his or her legacy devices into
a smart power strip, the devices may be able to take on "smart"
attributes. In certain embodiments, a device may be hard-wired to a
FODD unit, such as SPS 110.
[0050] The Smart Power Strip (SPS) is an electrical power strip
configured to allow for the regulation of power to its outlet(s)
according to control logic. FIG. 1 provides an illustration of an
embodiment of an energy management system incorporating an SPS 110.
The SPS is associated with a FODD 160, which may be incorporated
into the power strip 110 itself, or may be an independent device in
communication with the power strip. Discussion of SPS 110 herein
may refer to either a power strip separate from, but in
communication with, a FODD, or to a power strip with a built in
FODD. The SPS 110 includes an inlet electrical connector 120, such
as an electrical plug that connects to a power source, such as via
a wall electrical outlet. The SPS 110 includes one or more outlet
electrical connectors 112 for allowing electrical connection of
devices, such as conventional, non-smart, appliances. In certain
embodiments, one or more of the electrical connectors 112 is
controllable independently of one or more other electrical
connectors 112. FIG. 1 further depicts a user's criterion matrix
150 and a cost matrix 170, which concepts are discussed above with
reference to FIGS. 4 and 5. In certain embodiments, the SPS 110
operates or behaves in accordance with either the cost matrix 170,
the user's criterion matrix 150, or both.
[0051] In certain embodiments, the SPS 110, or its associated FODD
160, is programmable. The SPS may be programmed, for example, via a
monitoring and/or programming station 130, such as a user input
device (shown as a personal computer in FIG. 1). Communication
between the SPS 110, or FODD 160, may include two-way
communication, or may be limited to flow of information in one
direction. In certain embodiments, the SPS 110, or FODD 160, is
programmable through the Internet, and programming may be performed
wirelessly, or using a hardwire connection. For example, the SPS
110 may work with the new Smart Metering and/or a FODD 160 unit to
power down or power up various appliances connected to it. For
example, if a utility cost increases to a certain threshold level,
the SPS may power down one or more appliances, e.g., non-critical
appliances, but may keep power turned on to a one or more other
devices, e.g., critical devices, such as a needed medical
equipment.
[0052] In certain embodiments, an SPS 110 may operate in accordance
with the FODD algorithm illustrated in FIGS. 9-12 (discussed
below). However, an SPS 110 may, in certain embodiments operate in
accordance with any other suitable flow-regulation algorithm.
Furthermore, the system 100 may include an independent FODD device
160, which communicates with the SPS 110, or may include an
integrated FODD algorithm built into the SPS 110. In certain
embodiments, the power strip may be programmed to turn on or off at
certain times or for certain time intervals. In embodiments
including an independent FODD that communicates with the SPS 110,
such communication may be achieved via a wired or wireless
connection 140, such as a local area network, an internet
connection, or any other suitable connection.
[0053] The SPS 110 may obtain feedback information from one or more
devices that are electrically connected to the SPS 110, and such
information may be relied upon by the FODD 160 or SPS 110 in
determining how to regulate electrical power. Feedback information
may be obtained by the SPS 110 in addition to, or in place of,
information obtained from a smart meter, independent or integrated
FODD, etc. For example, a cell phone may be connected to the SPS
110, such that the cell phone provides information related to its
charge state, or other criteria, for consideration by the SPS 110.
Consider, for example, the following rules, or criteria that may be
provided by the cell phone to the SPS: if the cell phone is less
than 70% charged, charge it no matter what the cost; if the cell
phone is at least 70% charged, and the energy cost is less than a
threshold amount, resume charging until the cell phone reaches 90%,
and so on. The advantages associated with the use of an SPS may be
more apparent in the context of more power-hungry devices, such as
electric automobiles.
[0054] Much of the discussion above, with respect to FIG. 1, of
system 100 is applicable to the system 200 of FIG. 2. FIG. 2
illustrates an energy management system generally incorporating a
smart appliance 210, one example of which would be a smart power
strip, as discussed above. Other examples of smart appliances that
may be suitable for system 200 include smart washing machines,
dishwashers, climate control devices, television or other media
devices, etc.
[0055] FIG. 3 illustrates an embodiment of a meter and/or control
component for a smart appliance or smart power strip. In certain
embodiments, the component 314 includes a clock 315. In certain
embodiments, the clock and controls 315 can be set by a FODD using
a user's utility matrix and/or cost matrix with a manual override.
In certain embodiments, the clock and/or controls can be set using
controls on the smart appliance or power strip. The meter may
include one or more indicators indicating the cost of relevant
electricity consumption, or any other flow-related parameter. Any
indication means may be employed to communicate cost information to
a user. For example, a green or blue light or color may indicate
low cost; a yellow or orange light or color may indicate moderate
cost; and a red light or color may indicate a high cost. Cost
information for the meter may be provided by the FODD, user's
matrix or cost matrix. In certain embodiments, a meter and/or
control component includes a sophisticated display. In certain
embodiments, information associated with a FODD may be accessed
through a web interface. For example, a system may be configured
such that a user could obtain information as to cost, etc., through
a web interface. [0056] B. Control and Optimization of Flow of
Electricity Between Various Power Stations, Homes, Offices,
Factories, Etc.
[0057] FIG. 4 depicts an embodiment of an electrical flow
regulation system which demonstrates the control and optimization
of the flow of electricity between various power stations, homes,
offices, and/or factories, etc. The various utility plants depicted
in FIG. 4 may generate electricity from various sources. For
example, Utility Plan A 410 may generate electricity from a fossil
fuel, such as coal, or through another means of electricity
generation (e.g., nuclear reaction), while Utility Plant B 412 may
generate electricity from a renewable source (e.g., wind,
hydropower, solar energy, biomass, biofuel, geothermal energy,
etc.). An embodiment in accordance with FIG. 4 may include a
complex criterion matrix 450 with certain requirements or rules,
such as, for example: i) Utility Plant A 410 should run at least at
10% of maximum capacity, ii) all available energy beyond 10% of
Utility Plant A's 410 maximum capacity should be provided by
Utility Plant B 412 (renewable), until Utility Plant B 412 is
running at 70% of maximum capacity, iii) once Utility Plant B
reaches 70% maximum capacity, then power should be drawn equally
from Utility Plant A 410 and B 412 equally until Utility Plant B
412 reaches 85% capacity.
[0058] As can be seen, the above criterion requirements can become
very complex, especially in the context of numerous power
generation facilities. Moreover, an end user, such as a home, may
also generate electricity from one or more renewable sources, which
may be considered as another "power plant" in the framework of FIG.
4.
[0059] The criterion requirements detailed above may be downloaded
to the Flow Optimizer Decision Device 460 (FODD), or otherwise
incorporated into the FODD 460. The device may then determine how
much energy to draw from each power plant based on the above
criterion matrix, and/or other factors, such as the current demand
for energy.
[0060] As illustrated in FIG. 4, the collective input 418 (and/or
output in the case of bi-directional flow) of electrical energy in
the system 400 may be provided to the FODD 460 for consideration in
determining distribution of the electrical energy. As indicated in
FIG. 4, each source of energy provides some portion, or percentage,
of the overall input 418 of electrical power. The percentage of
electrical power drawn from a given energy source may be determined
by the FODD 460 based on a criterion matrix 450 and/or one or more
parameters, and may be positive or negative. In certain
embodiments, determinations by the FODD 460 take into account
parameters such as cost, whether or not the source is a renewable
source, distance, regulatory requirements, or other relevant
factors. Decisions relating to the distribution of energy from one
or more of the energy sources 410-416 may be made automatically. In
certain embodiments, decisions are made manually in connection with
suggestions generated by the FODD. Furthermore, the FODD 460 may
make decisions according to any desired time increment (e.g.,
seconds, minutes, etc.), or in real time, or substantially real
time.
[0061] The collective distribution 488 of energy too and/or from
energy consumption/production modules 480-486 is also depicted. In
certain embodiments, modules 480-486 in FIG. 4 represent end users,
or points of consumption of energy provided by one or more
electrical power generators 410-416. However, as discussed above,
systems in accordance with embodiments disclosed herein may be
bi-directional. In such systems, modules 480-486 may be equipped to
generate or otherwise contribute electrical power sack to the grid.
For example, a home, which in certain embodiments acts as an energy
consumer, may be equipped with solar panels that generate
electrical energy from the Sun. Electrical energy produced by the
home in excess of its needs may be provided to the system for
distribution. [0062] C. Generation of Cost Matrices to Be Used to
Set Utility Prices
[0063] The Flow Optimizer Decision Device may calculate the
percentage distribution of energy draw from each source. In certain
embodiments, this information, or any other desired parameter, is
used to generate the cost of the energy at a given time, which
information may be contained in a cost matrix 470. Such a cost
matrix 470 may include price structure for various user
classifications. In certain embodiments, the FODD 460 operates in
accordance with the cost matrix 470 or a user's criterion matrix
450, or both. Moreover, the cost/price structure may fluctuate in
real-time as percentage distribution from each source changes.
[0064] FIG. 5 depicts the user end of an embodiment of an
electrical flow regulation system. In the illustrated embodiment, a
FODD 560 manages the flow of electrical power between an end user
home 580 and a utility source 504. In certain embodiments, the FODD
560 is configured to handle negative, as well as positive, flows of
electricity. The system 500 may include a cost matrix 570 as
well-as a user's criterion matrix 550. The FODD 560 and/or the cost
matrix 570 may receive information input from a utility company, or
other source of information 502. The transfer of information
between the input source 502 and the FODD 560 and/or cost matrix
570 may be either a one or two-way form of communication. For
example, information relating to the electricity consumption of an
end user (e.g., home 580) may be communicated to the source 502. In
addition, communication with the FODD 560 may be achieved via the
internet, or other means of wired or wireless communication. In
certain embodiments, input source 502 communicates with either the
cost matrix 570, the FODD 560, or both, over a computer network
540, according to an.sub.y suitable connection, topology, scale or
technology. In certain embodiments, the criterion matrix is
automatically updated to reflect "learned" electricity consumption
preferences, behaviors, rules, etc.
[0065] FIG. 5 further depicts an electricity meter 506, such as a
smart meter, which may be coupled to a source of electricity 504,
which provides electricity to the home 580 via, for example, above
or below-ground power lines.
[0066] The home 580 depicted in FIG. 5 is an example end user that
may be included within an energy management system in accordance
with the embodiments disclosed herein. However, it should be
understood that discussion of home 580 with reference to FIG. 5 may
be applicable to other types of end users, such as, for example,
factories, offices or other commercial buildings, or any other
point of energy consumption or production. In certain embodiments,
home 580 includes one or more electricity-consuming devices, such
as, for example, electric or hybrid-electric vehicles 514, power
strips 510 (e.g. "smart" power strips) or various household
appliances (e.g., "smart" appliances 512). The home 580 may include
a smart thermostat 516. In certain embodiments, the end user is
equipped with one or more power generating devices or sources of
renewable energy, such as devices that generate electricity from
wind 590 or from solar energy 592 (i.e., photovoltaics), among
possibly others. The home 580 may include a device for energy
storage and/or generation 530. In certain embodiments device 530
includes an electrical storage battery. In certain embodiments, a
user/consumer may have a generator for use during power outage or
insufficient local power generation. An electrical storage unit may
be useful for a number of reasons. For example, electricity may be
cheaper to buy or sell at certain time periods, and therefore
storage of electricity for use at certain time periods may be
desirable. Moreover, power requirements may be greater during
certain periods of time, and therefore storage of electricity for
use during periods of greater need may be desirable. The following
example, which is not intended to limit or define the scope of any
terms or concepts disclosed herein, may be helpful in demonstrating
the possible utility of an electrical storage device in a
FODD-based electricity distribution system: In a certain
embodiment, energy may be less expensive to buy or sell at 3:00
p.m. than it is at 5:00 p.m. In this particular example, it is
assumed that at 5:30, energy storage is at around 70%. If a family
usually comes home at around 6:00 p.m. and needs a significant
amount of electricity at that time, an unsophisticated system may
sell energy at 3:00 p.m. and buy it back at the make expensive rate
at 6:00 p.m. A FODD system, however, may take energy usage patterns
into account to reduce energy expenses of a user. For example, if a
storage battery is charged prior to 5:00 p.m., electricity may
possibly be sold at around 5:00 pm at a higher rate. At 6:00 p.m.,
when the family comes home, the FODD may make the decision to start
drawing down the battery at 60% and buy electricity at 40%. In this
way, the battery maybe still be 30% charged by the time the family
goes to bed. Ideally, it would be almost at zero by the time the
sun comes up and the user's photovoltaic panels start generating
energy adequate to meet the user's energy requirements. The FODD
algorithm in this case may be programmed into the FODD via a
criterion matrix, or simply "learned" by the FODD using artificial
intelligence.
[0067] The home 580 may include an internet connection device 542.
In certain embodiments, end user 580 includes a programming and/or
monitoring unit 520, which may be accessible through wired or
wireless communication. For example, the unit 520 may be accessible
externally via the internet, or through a control device local to
the end user 580. The devices described above may communicate with
the FODD, or each other, via a wireless or wired network.
Water Distribution System
[0068] There is an acute water shortage in many parts of the world.
Population growth and the projected climate changes are likely to
exacerbate these shortages. More sophisticated methods are needed
to make certain that water is not wasted.
[0069] Similar to the electrical grid system, a Flow Optimizer
Decision Device (FODD) may be used to optimize and coordinate water
flow. For example, FODD may be used in large scale applications
such as the water system for a particular state or country. It may
also be used in a smaller scale for farms and even individual homes
and businesses.
[0070] On a large scale, a FODD may be used to monitor reservoirs,
dams, etc. and assist in water distribution. The criterion on how
water is to be distributed may be complex, particularly during
periods of drought. Therefore, how water is disseminated may depend
on complex criterion matrices. These rules or criterions may even
be legal in nature due to water rights. In addition to criterion
requirements on reservoir management, in certain embodiments, a
FODD receives information from weather forecast facilities or other
sources such as the USGS National Water Information System; USGS
posts and disseminates real-time water conditions (surface, ground,
and water quality). In addition to these information sources, a
FODD may receive information from water quality sensors and make
decisions as to shut the offending water supply down or dilute it
with other sources to bring the levels to acceptable levels. These
decisions may be governed by criterion matrices that are downloaded
to the FODD.
[0071] On a smaller scale, a FODD can be used to make irrigation
decisions. FIG. 6 illustrates a water management system 600
incorporating a FODD 660. In certain embodiments, the FODD 660
manages the distribution of water from one or more water supplies
610-616 to one or more crop regions 680-686, or other water
consumption points. FODD 660 may determine how water from supply
sources should be distributed based on information from one or more
criterion matrices 650. Criterion matrices 650 may contain rules
for irrigating various crops, wherein such rules relate to, for
example, costs associated with water from one or more particular
water sources, or other factors. In certain embodiments, a FODD
criterion matrix 650 accounts for one or more parameters related to
water distribution, such as weather forecast information, crop
type, growing season, input from ground moisture sensors, etc. For
example, based on the growing season and the type of crop, relative
humidity, temperature, ground moisture, etc. The FODD 660 may
direct a sprinkler system to discontinue irrigation or
sub-irrigation prior to an expected rainfall. As another example,
the FODD 660 may selectively irrigate moisture sensitive crops. In
certain embodiments, the criterion matrix is automatically updated
to reflect "learned" water consumption/distribution preferences,
behaviors, rules, etc.
[0072] The following example is provided for illustrative purposes
only, and does not limit or define the scope of any terms or
concepts disclosed herein: In a certain embodiment a homeowner has
a sprinkler system. During periods when rain is falling, the
homeowner may wish to turn off the sprinkler system. A FODD may be
configured to consider weather forecasts, soil moisture
information, or other factors or parameters, and may cause the
sprinkler system to be turned off, or recommend turning off the
sprinkler system. In certain embodiments, the FODD may cause or
recommend that certain zones or regions (discussed in further
detail below). The FODD may cause reactivation under certain
conditions as well. Such a FODD may be equipped with a default
program for a particular area or vegetation profile. In certain
embodiments, programming changes may be implemented via a computer,
cell phone, or other media device.
[0073] In certain embodiments, the FODD 660 can handle different
zones dynamically. For example, if zone A has plants that require a
significant moisture and Zone B has fruit trees that require low
moisture, a soil sensor may read the ground moisture of Zones A
and/or B. This information, together with other information such as
the weather forecast, may dictate on how to irrigate Zone A and/or
B. Moreover, the system may be programmed concerning, or "learn,"
irrigation patterns conducive to healthy plant/crop growth over a
period of time and/or for various seasons.
Medication Distribution System
[0074] A Flow Optimizer Decision Device (FODD) may be used to
optimize and/or coordinate monitoring and delivery of medication to
a patient. FIG. 13 illustrates an embodiment of a medication
distribution system in the context of treatment of a diabetic
patient 1310. However, references to diabetes-related monitoring
and distribution are made solely to aid in the understanding of
broader concepts discussed herein. It should, therefore, be
understood that a FODD-based medication distribution system may be
used for any suitable medication or medical intervention. For
example, a FODD may be used in connection with the monitoring and
delivery of chemotherapy medications, to assist in preventing the
application of too much or too little medication and/or
therapy.
[0075] With reference to FIG. 13, a monitoring device 1320 provides
information relating to one or more physiological parameters of a
patient 1310, such as blood glucose level. The system 1300 includes
a FODD 1360 in communication with the monitoring device 1320 (e.g.,
a glucose monitoring device). Communication between the monitoring
device 1320 and the FODD 1360 may be effected via a secure
authentication system. In certain embodiments, information is
uploaded from the monitoring device 1320 to the FODD via a secure
authentication system. Information may be uploaded from the
monitoring device 1320 to the FODD in real-time.
[0076] In certain embodiments, information provided by monitoring
device 1320 may be used by the FODD 1360, in connection with a
criterion matrix 1350 relating to medication adjustment, to
perform, or cause to be performed, any or all of the following
functions: Generate a report with suggestions or recommendations to
a physician or other person or device relating to adjustment or
maintenance of medication level. In certain embodiments, a
physician may make adjustments, or provide authorization to make
adjustment to medication levels. For example, once a physician
approves adjustment or maintenance of medication level, such
information may be communicated to a pharmacy or to the patient
1310. In the case of a wireless drug delivery implant system (e.g.,
an Insulin Release Device (IRD) 1330), medication may be
automatically adjusted based on a preapproved matrix. In certain
embodiments, medication adjustment or maintenance is authorized via
a physician's secure electronic signature.
[0077] The information being transmitted may relate to one
parameter or metric, such as blood glucose, or several, such as
blood pressure, heart rate, etc. In certain embodiments, the FODD
1360 securely adjusts (or recommends adjustment of) medication
levels with or without physician override. Medication levels may be
checked against information relating to possible adverse side
effects and/or interactions with other medications.
[0078] FODD 1360 may be used for adjusting medication in cases
where a monitoring system is hard-wired into the patient 1310, at a
hospital, residence, or other location. FODD 1360 may be local to
the patient 1310, or may operate remotely.
[0079] What makes the FODD so unique is that for the first time,
medications could be adjusted in real-time. In the case of the
insulin example, the insulin would be released very close to how
the natural body would react to rise in blood sugar, mimicking the
patient's own pancreas. In certain embodiments, a FODD acts as an
artificial pancreas, or other artificial organ. This has the
potential to improve patient's lives and adherence to
medication
[0080] With further reference to FIG. 13, in certain embodiments,
medication distribution device 1330 is an insulin releasing device.
Such a device may be configured to receive commands (e.g. wireless
communication via a network or through a device carried by the user
such as a cell phone, or via a wired transmission, etc.) relating
to adjustment or maintenance of insulin. In certain embodiments,
device 1330 is configured to remove harmful substance from the
body, either in addition to, or in place of, medication
distribution functionality.
[0081] In certain embodiments, monitoring device 1320 is a glucose
monitoring device. Such a device may measure blood glucose levels,
possibly in addition to other parameters or metrics, such as blood
pressure, heart rate, or other physiological parameters relating to
the patient 1310. A glucose monitoring device may be an implanted
device, and may obtain information relating to one or more
physiological parameter in intervals, and transmit such information
the FODD 1360. In certain embodiments, monitoring device 1320 is a
measuring device that the patient 1310 can use to manually record
information such as blood glucose or blood pressure, etc. The data
may be transmitted directly by the device, through a wireless
network, through an intermediary device such as a cell phone
carried by the patient, or in any other suitable manner.
[0082] In certain embodiments, the FODD 1360 makes decisions with
or without doctor or nurse approval override. Alternatively, it
could make recommendations as to the correct course of action to be
taken, such as an adjustment to medication delivery. Adjustment to
the medication may be performed automatically (e.g., via the
medication distribution device 1330) or prescription may be
faxed/emailed/transmitted electronically to a pharmacy and/or
patient. Feedback information from the medication delivery device
1330 may be transmitted 1334 to the FODD 1360. Such information may
be helpful in confirming the actual amount or rate of insulin
released to the patient 1310.
[0083] The FODD 1360 may transmit information 1332 to the insulin
release device 1330 relating to the amount of insulin to be
released. Such information transmission may be performed, for
example, a) automatically by FODD 1360 via the criterion matrix
1350 or b) manually set by a physician via the FODD 1360, or c) a
combination of (a) and (b) whereby the FODD 1360 may make a
recommendation as to the amount of insulin to be released; the
physician may then accept, reject or modify the recommended amount.
In certain embodiments, information is transmitted or downloaded
1324 to the FODD 1360 from the glucose monitoring device 1320. Such
information may include information relating to blood glucose
and/or other parameters, such as heart rate, blood pressure, etc.
In certain embodiments, the physician may instruct 1322 the FODD
1360 to add or remove parameters to or from the glucose monitoring
device 1320. For example, in certain embodiments, if the physician
desires to receive information relating to a particular parameter
that the monitoring device 1320 is equipped to monitor, such as the
amount of the actual insulin in the blood, such parameter may be
added to the monitoring device 1320 and the criterion matrix 1350.
In certain embodiments, the criterion matrix is automatically
updated to reflect "learned" medication distribution or harmful
substance removal preferences, behaviors, rules, etc.
[0084] Decisions made by the FODD 1360 may be made in any desired
time increment (e.g., seconds, minutes, etc), or they may be made
in real time. Decisions may be made with or without physician
approval. In certain embodiments, the FODD 1360 bases decisions on
the criterion matrix 1350. The criterion matrix 1350 may be made of
individual functions, which take into account, for example,
information such as blood glucose level, blood pressure, heart
rate, etc. Moreover, the functions may include rules and/or limits
on how medications should be adjusted based on the information
received.
[0085] The FODD 1360 may be located remotely at any suitable
location, at a physician's office, at the patient's residence, or
may be a portable device, such as a device carried by, or implanted
in, the patient 1310. In certain embodiments, one or more of the
components 1320, 1330, 1360 and 1350 are incorporated into a single
physical unit. The physical unit may be implanted into the patient
as a single device.
[0086] The following example scenarios relating to the medication
delivery system 1300 are discussed for explanation purposes only,
and do not serve to limit or define terms used herein in any way.
In a first example, a patient 1310 eats large meal, causing his or
her blood glucose level to elevate. The glucose monitoring device
may transmit information indicating the elevation in blood glucose
level information to a FODD 1360. Based on a criterion matrix 1350
(the criteria of which may have been specified by a physician, or
may be in accordance with certain medical guidelines), the FODD
1360 may adjust or cause to be adjusted the release of insulin to
the patient 1310. This may be done by sending commands to an
insulin release device 1330. The insulin release device may then
release the appropriate amount of the insulin. In certain
embodiments, this release of insulin is done without physician
approval. In certain embodiments, physician approval or
authorization is required. In certain embodiments, physician
approval may be required in certain circumstances, while other
circumstances do not require such approval. A report of activity
relating to the monitoring and/or distribution of insulin (or other
medication) may be logged or sent to a physician, or otherwise
saved or transmitted.
[0087] In a second example, a patient 1310 eats large meal.
However, the patient's blood glucose level does not elevate due to
prior diet or exercise. A glucose monitoring device 1320 may
transmit this information to a FODD 1360. Based on a criterion
matrix 1350 (the criteria of which may have been specified by a
physician, or may be in accordance with certain medical guidelines,
etc.), the FODD 1360 may determine that no additional insulin is
required. In certain embodiments the FODD 1360 may transmit such
information to an insulin release device 1330, which, in turn, may
fail to release additional insulin to the patient 1310.
[0088] In the two examples detailed above, the blood glucose
monitoring device may be an implant. However, in certain
embodiments, the monitoring device may be a unit that is not
implanted, and may be manually operable by the patient, or another
user. The information may be uploadable to the FODD 1360. Moreover,
the medication release device 1330 may simply be a prescription or
information that is sent to a patient or other person (e.g., via
email or text) indicating how medication should be taken or
adjusted.
Partner Cash Flow Analysis
[0089] A Flow Optimizer Decision Device (FODD) can be used to
analyze very complex partnership structures it many industries such
as real estate, the movie industry, the stock market, the insurance
industry, banking, etc. A FODD may be used in any industry or
scenario that requires investment with more than one person or
entity. Moreover, a FODD may be used in situations involving a
single investor.
[0090] With an advanced FODD algorithm, as described herein (see
FIGS. 9-12 and corresponding discussion), one can analyze many
complex investment scenarios automatically. In certain embodiments
FODD algorithms are not limited by the number of investors,
periods, or types of criterion requirements. A FODD algorithm,
therefore, may help a partner decide on the best "deal structure"
to maximize investment return and minimize risk, or otherwise
achieve desired investment outcomes. Furthermore, as discussed
above, FODD algorithms may be applicable to any system, method, or
device relating to the regulation or management of flow, such as,
for example, a Smart Power Strip, as discussed above.
[0091] FIG. 7 illustrates an embodiment of a cash flow management
system. For illustration purposes only, references are made herein
to cash flow systems. However, it should be understood that
embodiments and concepts disclosed herein are applicable any
relevant type of flow. The system 700 may include one or more
partners 710, 780 and/or one or more projects 712, 782. In FIG. 7,
the total input of funds 715 in the system 700 is represented by
the partner 710 and project 712 modules labels "Source of Funds."
Initially project(s) 782 may need cash, and therefore the source of
funds from projects 712 may be zero, or marginal; in such a case,
the partners 710 may put up most or all of the cash. In later
months, this dynamic may be reversed to some extent, whereby the
partners 780 receive most of the cash and the project(s) 712
provide a substantial source of funds.
[0092] FIG. 8 provides a simplified representation of an embodiment
of a cash flow management system, wherein net negative cash flows
are considered sources of funds (i.e., investments) and net
positive cash flows are considered uses of funds (i.e., returns).
The terms "negative" and "positive" are used herein for
illustration purposes only, and each of these terms may be subject
to different meanings or understandings in certain systems,
scenarios or circumstances. On examination, one can see that FIG. 8
shares some abstract structural similarity with the representation
of a system for managing electricity flow depicted in FIG. 4.
[0093] With respect to cash flow analysis, or any other flow
regulation analysis, a FODD may use an algorithm similar to that
depicted in FIGS. 9-12 to determine the percent distribution of
each partner based on a criterion matrix 750, 850. FIGS. 9-12
illustrate flow charts representing a particular embodiment of an
algorithm that may be used in association with certain embodiments
of a FODD as described herein. FIG. 12 provides a summary of an
example algorithm represented by FIGS. 9-11. The following notes
provide explanation relating to the meaning of terms and variables
used in the flow charts of FIGS. 9-12 and are provided solely to
aid in the understanding of the flow charts, and in no way define
or limit the terms or variables used therein: [0094] Result Array:
May begins with a zero values in the array and be filled during the
process. When the process ends it contains the final result of the
calculation [0095] Criterions: Milestones based on various targets
calculated by various functions at each stage of the distribution.
Once particular criterion hurdles are met, a flow chart may proceed
to the next distribution in the sequence. [0096] Functions: May be
simple linear, non-linear or even very complex functions that
require complex iterations to determine their values. [0097]
Parameter (Function Parameters): Parameters that describe the
function, e.g., function name, constants in the function, etc.
[0098] Period: Indicates the period of calculation; when one period
is finished, a flow chart may proceed to the next period. A period
may be years, months, hours, seconds, millisecond, nanosecond, etc.
A period may also be in real time, whereby samples are taken in
real time and analyzed. [0099] SplitLevel: SplitLevel 0 identifies
the first set of criterions and split values. When one set of
Criterion requirements are satisfied, a flow chart may proceed to
the next SplitLevel and the next set of Criterions and SplitLevels
will be used. Each split level may have its own sets of criterion
matrix, unique function matrix, parameter matrix, etc. [0100]
Iteration: Iterate of calculating criterions and splits until the
criterions converges. There may be a limit on the number of
iterations. This may be a very large number. However, a number as
small as 100 for the maximum iteration should suffice. Generally
convergence occurs in 20-30 iterations. [0101] CriterionCheck: Aids
in determining the status of the current criterion calculation.
[0102] 1--A value of 1 means that the calculated value is greater
than the expected value. [0103] 2--A value of 0 means the
calculation equals the expected value. [0104] 3--A value of -1
means that the calculated value is less than the expected value.
[0105] 4--A Value of -2 means that there are no more criterion to
calculate. [0106] Negstatus: Flag that helps deal with negative
flows. There may be total positive flows as well as total negative
flows. In case of negative flows we can have unique/separate
matrices for function, parameters, split levels, etc. Negative
flows can be treated with different rules. This allows the Flow
Optimizer Decision Device (FOOD) to analyze bi-directional flows.
[0107] iConditionType: There are two ways to check to see if the
criterion is met: (1) ALL the conditions must be met, in this case
iContitionType=O. Alternatively, (2) only one of the conditions
must be met, in this case iConditionType=1. In summary, if all the
conditions much be met (e.g. Condition 1 AND Condition 2, And . . .
), then iConditionType=O; if any condition will do (e.g. Condition
1 OR Condition 2, OR,), then iConditionType=1. [0108] In cases
where both AND and OR are used (e.g. Condition 1 AND Condition 2 OR
Condition 3 etc.), use of additional split levels may help
accomplish this. [0109] SD: Source or Destination of the Flow. When
a flow is generated, it is from the source. The flow output/result
is the Destination. The sum of all the Source of the Flow should
equal the sum of all the Destinations of the flow. Some or all of
the Source of the Flow may be the same as the destination of the
Flow. In this way a Source may be the same as a destination. One
Source of the flow may be zero and receive most of the flow
(Destination) or it could be the majority of the source of the flow
and receive little or nothing. The flow may be positive or
negative.
[0110] As discussed above, the FODD can be used in many scenarios,
such as, for example, electrical distribution systems. For
illustration purposes only, some of the discussion herein relates
specifically to real estate development. The following example may
be helpful in demonstrating the implementation of such a
FODD/algorithm: Assume a real estate development project with three
partners, each being associated with his or her own risk aversion
utility curve. In this example, Partner A may be very risk averse,
Partner B may be less risk averse than Partner A, and Partner C may
not contribute much cash and may instead be charged with the
development of the project. As a developer, Partner C may be
willing to take more risk as well.
[0111] The following example characteristics or rules may be
included in a criterion matrix associated with a FODD suitable for
regulation of cash flow between and among Partners A, B and C:
[0112] distribute 90% of the initial positive cash flow to partner
A, 10% of the initial positive cash flow to partner B, and 0% to
the developer (partner C) UNTIL THE FOLLOWING CONDITIONS ARE
SATISFIED: [0113] i) Partner A gets all of initial investment back
AND ii) Partner A gets a 4% Internal Rate of Return (IRR) on his
money OR he gets a Net Present Value (NPV) equal to 120% of his
initial investment at a 6% discount rate. [0114] Once the above
criterion are satisfied, then distribute 10% to partner A, 50% to
partner B, and 40% to partner C (Developer) UNTIL THE FOLLOWING
CONDITIONS ARE SATISFIED: i) Partner B gets 60% of his initial
investment back AND a 12% IRR AND ii) Partner C (Developer) gets
back 50% of his developer's fee (some predetermined amount perhaps)
AND iii) Partner A not only gets all his money back (as dictated in
the previous step) but he also gets a 12% IRR. [0115] Once the
above conditions are satisfied, distribute the cash flows equally
between Partner B and C (Developer) until the sale / disposition of
the property (the disposition would have its own criterion matrix
similar to the above).
[0116] The above example may also be much more complex. More
complex matrices may have many more steps with complex AND/OR
Boolean logic. Moreover, negative cash flow may likewise require
separate handling. The following issues may arise: If there were
negative cash flows (project is losing money) who would put up the
shortfall? In our example above, perhaps the developer (Partner C)
or Partner B would put up the funds. The FODD 760, 860 may handle
negative cash flow situations by including a separate negative flow
criterion matrix. In this way, a FODD may be able to handle
bi-directional flow, having separate rules for negative flows. This
negative criterion matrix may be part of a main criterion matrix
750, 850.
[0117] The FODD 750, 850 may analyze the example scenario discussed
above, and distribute cash flow for the particular period. Another
unique feature of the FODD is that it may be capable of handling
both of the following scenarios: 1) Full-period distributions as
well as 2) mid-period distribution.
[0118] If, for example, the period unit under consideration is
months, for a full-period distribution, the percent distribution
would not be changed until the following month. In our example
above, a criterion hurdle could be reached in the first week of the
month (period). However, in this example, the percentage
distribution would not change until the next month for a
full-period distribution.
[0119] For a mid-period distribution, the FODD may provide an exact
analysis. With reference to the example above, once the criterions
(such as IRR, etc.) reach an exact figure (within tolerance
parameter in the criterion matrix), then the FODD may proceed to
the next level of distribution. Such FODD embodiments may be very
accurate, since an IRR hurdle, for example, could be reached in the
3rd day of a particular month.
More Complex Situations And Sensitivity Analysis
[0120] It may also be desirable to analyze various cash flow
scenarios with different partner structures. It may, therefore, be
desirable to analyze various cash flow scenarios (e.g., cash flow
scenarios 1, 2, 3, etc.) with various partners (e.g., Partners A,
B, C, etc.), each being associated with a complex criterion matrix.
In certain embodiments, a FODD may be used multiple times, using
different criterion matrix inputs for each deal structure, to find
an optimal solution.
FODD Used In A Partner Cash Flow Analysis Situation--Business
Model
[0121] In case of use in partner cash flow analysis, a FODD may be
used as a subscription service over the internet. For example, it
may be used in any industry where some kind of partnership is
desirable. Such industries include, but are not limited to:
[0122] Real Estate Transactions, Development, Brokerage
[0123] Advertising
[0124] Transportation
[0125] Oil, Gas, mining
[0126] Agriculture
[0127] Entertainment, Hollywood
[0128] Medical, Hospitals, Pharmaceuticals
[0129] Insurance Industry
[0130] Internet, E-Commerce, computer manufacturing, software
[0131] Communication such as telecom and wireless
telecommunication
[0132] Manufacturing
[0133] Automotive
[0134] Construction
[0135] Utility companies and Energy ventures
[0136] Financial services where partners are involved such as
banking
[0137] Food industry
[0138] A specific website may be developed for each of the target
industries. However, in each case, a FODD engine might be used to
calculate the partner cash flow analysis.
[0139] There are at least four ways this business model may
generate revenue:
[0140] 1. As a subscription service. People/companies would pay to
use it.
[0141] 2. Sell advertisement targeted for the particular industry
and audience.
[0142] 3. Sell products or services for the targeted audience.
[0143] 4. Put people together (collaboration) who are interested in
a particular investment vehicle and collect a fee.
[0144] For example, a website might facilitate management of funds
for partners or service providers who are interested in investing
in a particular industry and/or in a certain geographical region.
If a land owner wishes to sell his property, he might put his
property up on a website. He could answer some questions on the
website--thereby establishing a preliminary criterion
requirement.
[0145] Another example may involve an apartment developer who
wishes to use a website to input his cash flow requirements and a
rough construction estimate. A general contractor who wishes to
build the project and put his fee as an investment might also use
the site to put a more detailed construction estimate. Investors
and/or partners may also use the website to input their
requirements on the project.
[0146] The various illustrative logical blocks, modules, and
processes described herein may be implemented as electronic
hardware, computer software, or combinations of both. To clearly
illustrate this interchangeability of hardware and software,
various illustrative components, blocks, modules, and states have
been described above generally in terms of their functionality.
However, while the various modules are illustrated separately, they
may share some or all of the same underlying logic or code. Certain
of the logical blocks, modules, and processes described herein may
instead be implemented monolithically.
[0147] The various illustrative logical blocks, modules, and
processes described herein may be implemented or performed by a
machine, such as a computer, a processor, a digital signal
processor (DSP), an application specific integrated circuit (ASIC),
a field programmable gate array (FPGA) or other programmable logic
device, discrete gate or transistor logic, discrete hardware
components, or any combination thereof designed to perform the
functions described herein. A processor may be a microprocessor, a
controller, microcontroller, state machine, combinations of the
same, or the like. A processor may also be implemented as a
combination of computing devices, e.g., a combination of a DSP and
a microprocessor, a plurality of microprocessors or processor
cores, one or more graphics or stream processors, one or more
microprocessors in conjunction with a DSP, or any other such
configuration.
[0148] The blocks or states of the processes described herein may
be embodied directly in hardware, in a software module executed by
a processor, or in a combination of the two. For example, each of
the processes described above may also be embodied in, and fully
automated by, software modules executed by one or more machines
such as computers or computer processors. A module may reside in a
computer-readable storage medium such as RAM memory, flash memory,
ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a
removable disk, a CD-ROM, memory capable of storing firmware, or
any other form of computer-readable storage medium known in the
art. An exemplary computer-readable storage medium can be coupled
to a processor such that the processor can read information from,
and write information to, the computer-readable storage medium. In
the alternative, the computer-readable storage medium may be
integral to the processor. The processor and the computer-readable
storage medium may reside in an ASIC.
[0149] Depending on the embodiment, certain acts, events, or
functions of any of the processes or algorithms described herein
can be performed in a different sequence, may be added, merged, or
left out all together. Thus, in certain embodiments, not all
described acts or events are necessary for the practice of the
processes. Moreover, in certain embodiments, acts or events may be
performed concurrently, e.g., through multi-threaded processing,
interrupt processing, or via multiple processors or processor
cores, rather than sequentially.
[0150] Conditional language used herein, such as, among others,
"can," "could," "might," "may," "e.g.," and from the like, unless
specifically stated otherwise, or otherwise understood within the
context as used, is generally intended to convey that certain
embodiments include, while other embodiments do not include,
certain features, elements and/or states. Thus, such conditional
language is not generally intended to imply that features, elements
and/or states are in any way required for one or more embodiments
or that one or more embodiments necessarily include logic for
deciding, with or without author input or prompting, whether these
features, elements and/or states are included or are to be
performed in any particular embodiment.
[0151] While the disclosure describes, and points out novel
features as applied to various embodiments, it will be understood
that various omissions, substitutions, and changes in the form and
details of the logical blocks, modules, and processes illustrated
may be made without departing from the spirit of the disclosure. As
will be recognized, certain embodiments of the inventions described
herein may be embodied within a form that does not provide all of
the features and benefits set forth herein, as some features may be
used or practiced separately from others.
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