(12) United States Patent
`Steinberg et al.
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,596,550 B2
`Dec. 3, 2013
`
`US008596550B2
`
`(54) SYSTEM, METHOD AND APPARATUS FOR
`IDENTIFYING MANUAL INPUTS TO AND
`ADAPTIVE PROGRAMMING OFA
`THERMOSTAT
`(75) Inventors: John Douglas Steinberg, Millbrae, CA
`(US); Scott Douglas Hublou, Redwood
`City, CA (US); Leo Cheung, Sunnyvale,
`CA (US)
`(73) Assignee: EcoFactor, Inc., Millbrae, CA (US)
`(*) Notice:
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 866 days.
`
`(21) Appl. No.: 12/778,052
`(22) Filed:
`May 11, 2010
`
`(65)
`
`Prior Publication Data
`US 2010/0308119A1
`Dec. 9, 2010
`
`Related U.S. Application Data
`(60) typal application No. 61/215.999, filed on May
`
`(51) Int. Cl.
`G05D 23/00
`(52) U.S. Cl.
`USPC ................. 236/1 C: 236/51; 236/94; 62/161;
`700/278
`
`(2006.01)
`
`(58) Field of Classification Search
`USPC .............. 236/1 C, 46 R, 51, 94; 62/161, 163;
`700/276, 278
`See application file for complete search history.
`
`(56)
`
`References Cited
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`
`4,136,732 A
`4,341,345 A
`
`1/1979 Demaray et al.
`7, 1982 Hammer et al.
`
`9, 1983 Hebert
`4,403,644 A
`g 3. East et al.
`1398, A
`aO
`6/1987 Beckey
`4,674,027 A
`1/1990 Cler .............................. 7OO/276
`4,897,798 A *
`9, 1993 Jefferson et al.
`5,244,146 A
`5,270,952 A 12/1993 Adams et al.
`5,314,004 A
`5/1994 Strand et al.
`(Continued)
`
`FOREIGN PATENT DOCUMENTS
`
`EP
`KR
`KR
`
`3, 1991
`O415747
`8. 1994
`10-1994-001 1902
`10, 2000
`10-2000-0059.532
`OTHER PUBLICATIONS
`
`Honeywell, W7600/W7620 Controller Reference Manual,
`HWO021207, Oct. 1992.
`
`(Continued)
`
`Primary Examiner — Marc Norman
`(74) Attorney, Agent, or Firm — Knobbe, Martens, Olson &
`Bear, LLP
`ABSTRACT
`(57)
`Systems and methods are disclosed for incorporating manual
`changes to the setpoint for athermostatic controller into long
`term programming of the thermostatic controller. For
`example, one or more of the exemplary systems compares the
`actual setpoint at a given time for the thermostatic controller
`to an expected setpoint for the thermostatic controller in light
`of the scheduled programming. A determination is then made
`as to whether the actual setpoint and the expected setpoint are
`the same or different. Furthermore, a manual change to the
`actual setpoint for the thermostatic controller is compared to
`previously recorded setpoint data for the thermostatic con
`troller. At least one rule is then applied for the interpretation
`of the manual change in light of the previously recorded
`setpoint data.
`
`23 Claims, 11 Drawing Sheets
`
`
`
`fo
`
`Retrieve actual
`andscheded
`setpoint data
`current and
`Immediately prior)
`
`faif
`
`Reeve
`scheduled
`algorithmic
`changes
`
`fé
`\
`
`calculate actual
`setpoint differencs
`(A) (current and
`immediately prior
`
`f^2| Calculate scheduled
`M setpoint difference
`(ds) (cument and
`Immediately prior)
`
`Log Tatual
`overdice to
`database
`
`
`
`Sum scheduled
`
`N E. changes (sc)
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`US 8,596,550 B2
`Page 2
`
`(56)
`
`References Cited
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`U.S. PATENT DOCUMENTS
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`
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`8, 180,492 B2
`8,340,826 B2 12/2012 Steinberg
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`2010/0282857 A1 1 1/2010 Steinberg
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`9, 2011 Imes et al.
`2011/0246898 A1 10, 2011 Imes et al.
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`12/2011 Imes et al.
`2011/0307103 Al 12/2011 Cheung et al.
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`4/2012 Steinberg
`2012/0093141 A1
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`2012fO221294 A1
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`8, 2012 Imes et al.
`2012fO252430 A1 10, 2012 Imes et al.
`2012/0324119 A1 12/2012 Imes et al.
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`3/2013 Imes et al.
`2013, O144453 A1
`6, 2013 Subbloie
`2013/0167035 A1
`6, 2013 Imes et al.
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`US 8,596,550 B2
`Page 3
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`OTHER PUBLICATIONS
`
`Wetter, et al. A comparison of deterministic and probabilistic opti
`mization algorithms for nonsmooth simulation-based optimization.
`Building and Environment 39, 2004, pp. 989-999.
`U.S. Appl. No. 13/523,697, filed Jun. 14, 2012, Hublou, et al.
`U.S. Appl. No. 13/725,447, filed Dec. 21, 2012, Steinberg, John
`Douglas.
`Bourhan, et al., “Dynamic model of an HVAC system for control
`analysis”. Elsevier 2004.
`Emerson Climate Technologies, “Network Thermostat for E2 Build
`ing Controller Installation and Operation Manual”. 2007.
`Johnson Controls, “T600HCX-3 Single-Stage Thermostats', 2006.
`Written Opinion and Search Report for PCT/US2011/032537, dated
`Dec. 12, 2011.
`Comverge SuperStat Flyer, prior to Jun. 28, 2007.
`Control4 Wireless Thermostat Brochure, 2006.
`Cooper Power Systems Web Page, 2000-2009.
`Enernoc Web Page, 2004-2009.
`Enerwise Website, 1999-2009.
`Honeywell Programmable Thermostat Owner's Guide, www.
`honeywell.com/yourhome, 2004.
`Pier, Southern California Edison, Demand Responsive Control of Air
`Conditioning via Programmable Communicating; Feb. 14, 2006.
`Proliphix. Thermostat Brochure, prior to Jun. 2007.
`
`Arens, et al., “How Ambient Intelligence Will Improve Habitability
`and Energy Efficiency in Buildings”, 2005, research paper, Centerfor
`the Built Environment, Controls and Information Technology.
`Johnson Controls, Touch4 building automation system brochure,
`2007.
`Kilicotte, et al., “Dynamic Controls for Energy Efficiency and
`Demand Response: Framework Concepts and a New Construction
`Study Case in New York”. Proceedings of the 2006 ACEEE Summer
`Study of Energy Efficiency in Buildings, Pacific Grove. CA, Aug.
`13-18, 2006.
`Lin, et al., “Multi-Sensor Single-Actuator Control of HVAC Sys
`tems', 2002 Communicating Thermostats Draft Report.
`Wang, et al., “Opportunities to Save Energy and Improve Comfort by
`Using Wireless Sensor Networks in Buildings.” (2003), Center for
`Environmental Design Research.
`Wetter, et al., “A comparison of deterministic and probabilistic opti
`mization algorithms for nonsmooth simulation-based optimization'.
`Building and Environment 39, 2004, pp. 989-999.
`Brush, et al., Preheat—Controlling Home Heating with Occupancy
`Prediction, 2013.
`Gupta, et al., A Persuasive GPS-Controlled Thermostat System, MIT,
`2008.
`Gupta, Adding GPS-Control to Traditional Thermostats: An Explo
`ration of Potential Energy Savings and Design Challenges, MIT,
`2009.
`Krumm, et al., Learning Time-Based Presence Probabilities, Jun.
`2011.
`Scott, et al., Home Heating Using GPS-Based Arrival Prediction,
`2010.
`
`* cited by examiner
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`U.S. Patent
`
`Dec. 3, 2013
`Dec, 3, 2013
`
`Sheet 1 of 11
`Sheet 1 of 11
`
`US 8,596,550 B2
`US 8,596,550 B2
`
`
`
`
`
`
`
`
`
`
`
`
`BS97,
`
`
`
`MYOMLAN
`
`
`
`FOL
`
`
`
`
`
`
`POL
`
`PETITIONER ECOBEE
`EX. 1001
`
`PETITIONER ECOBEE
`EX. 1001
`
`
`
`
`
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 2 of 11
`
`US 8,596,550 B2
`
`
`
`FIG 2
`
`UTILITY
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`US 8,596,550 B2
`
`Hiiiiiiii?
`
`
`
`
`
`HOd Xeu Joy dnuôIS
`
`Áuenuep
`
`90°
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`US 8,596,550 B2
`
`2,927
`
`XV/TER]
`
`9927
`
`
`
`SSETERHINW
`
`WEICJOW
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 5 of 11
`
`US 8,596,550 B2
`
`32/7
`
`467/7
`
`52(2
`
`4262
`
`7207
`
`3207
`
`92/2
`
`
`
`TEMPERATURE
`
`THERMOSTAT SETTINGS
`
`HVAC HARDWARE
`
`TRANSACTION
`PRODUCT & SERVICE
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 6 of 11
`
`US 8,596,550 B2
`US 8,596,550 B2
`
`fe
`(w-
`fo
`
`
`
`
`
`
`
`
`
`
`
`
`
`FIG.6A
`
`
`
`
`
`
`
`
`
`XL|EE_LAMW 2
`N \NN
`
`
`ASSSSS =
`
`
`
`
`RSsws
`
`PETITIONER ECOBEE
`EX. 100
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec.3, 2013
`
`Sheet 7 of 11
`
`US 8,596,550 B2
`
`
`
`
`
`Uy
`
`
`
`RSSSQW
`
`
`FIG.6B
`
`PETITIONER ECOBEE
`EX. 100
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 8 of 11
`
`US 8,596,550 B2
`
`7/774
`
`Yes
`
`
`
`Log manual
`OVerride to
`database
`
`
`
`
`
`Retrieve actual
`and Scheduled
`setpoint data
`(current and
`immediately prior)
`
`
`
`
`
`7(2/22
`
`
`
`Retrieve
`Scheduled
`algorithmic
`changes
`
`7(7/76
`
`Calculate actual
`setpoint difference
`(dA) (current and
`immediately prior)
`
`7/7(25
`
`Calculate Scheduled
`setpoint difference
`(dS) (current and
`immediately prior)
`
`Sum Scheduled
`algorithmic
`changes (SC)
`
`7/7/7
`
`7(7/2
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 9 of 11
`
`US 8,596,550 B2
`
`//(22
`
`77/24
`
`77/76
`
`77/25
`
`777/7
`
`Detect
`manual
`Override
`
`Retrieve
`rules
`
`Retrieve
`Contextual
`data
`
`Retrieve recent
`historical
`Override data
`
`Interpret
`OVerride
`
`
`
`77/2
`
`Revise
`Current
`settings?
`
`No
`
`Revise
`thermostat
`settings
`
`Log
`setting
`change
`
`
`
`
`
`
`
`
`
`
`
`
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`
`Dec. 3, 2013
`
`Sheet 10 of 11
`
`US 8,596,550 B2
`
`72/22
`
`
`
`72/72
`
`72/74
`
`7225
`
`Retrieve
`rules and
`programming
`
`Retrieve recent
`OVerride data
`
`Retrieve
`COntextual
`data
`
`Interpret
`Overrides
`
`No
`
`Change
`rules?
`
`
`
`Revise
`stored rules
`
`
`
`
`
`
`
`
`
`72/4
`
`Setback
`Schedule change
`recommended?
`
`Automatic
`changes
`authorized?
`
`
`
`
`
`
`
`Revise
`Setback
`Schedule
`
`Suggest
`change to
`Customer
`
`FIG. O
`
`PETITIONER ECOBEE
`EX. 1001
`
`

`

`U.S. Patent
`U.S. Patent
`
`Dec. 3, 2013
`Dec, 3, 2013
`
`Sheet 11 of 11
`Sheet 11 of 11
`
`US 8,596,550 B2
`US 8,596,550 B2
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`
`
`
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`PETITIONER ECOBEE
`EX. 1001
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`PETITIONER ECOBEE
`EX. 1001
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`US 8,596,550 B2
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`1.
`SYSTEM, METHOD AND APPARATUS FOR
`IDENTIFYING MANUAL INPUTS TO AND
`ADAPTIVE PROGRAMMING OFA
`THERMOSTAT
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`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`This application claims priority to Provisional Application
`No. 61/215,999, filed May 12, 2009, the entirety of which is
`incorporated herein by reference and is to be considered part
`of this specification.
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`BACKGROUND OF THE INVENTION
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`Field of the Invention
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`Programmable thermostats have been available for more
`than 20 years. Programmable thermostats offer two types of
`advantages as compared to non-programmable devices. On
`the one hand, programmable thermostats can save energy in
`large part because they automate the process of reducing
`conditioning during times when the space is unoccupied, or
`while occupants are sleeping, and thus reduce energy con
`Sumption.
`On the other hand, programmable thermostats can also
`enhance comfort as compared to manually changing setpoints
`using a non-programmable thermostat. For example, during
`the winter, a homeowner might manually turn down the ther
`mostat from 70 degrees F. to 64 degrees when going to sleep
`and back to 70 degrees in the morning. The drawback to this
`approach is that there can be considerable delay between the
`adjustment of the thermostat and the achieving of the desired
`change in ambient temperature, and many people find getting
`out of bed, showering, etc. in a cold house unpleasant. A
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`programmable thermostat allows homeowners to anticipate
`the desired result by programming a pre-conditioning of the
`home. So, for example, if the homeowner gets out of bed at 7
`AM, setting the thermostat to change from the overnight
`setpoint of 64 degrees to 70 at 6 AM can make the house
`comfortable when the consumergets up. The drawback to this
`approach is that the higher temperature will cost more to
`maintain, so the increase in comfort is purchased at the cost of
`higher energy usage.
`But all of the advantages of a programmable thermostat
`depend on the match between the preferences of the occu
`pants and the actual settings employed. If, for example, the
`thermostat is set to warm up the house on winter mornings at
`7AM, but the homeowner gets up at 5:30, the homeowner is
`likely to be dissatisfied. If a homeowner has programmed her
`thermostat to cool down the house at 5 PM each afternoon
`based on the assumption that she will come home at 6 PM, but
`her schedule changes and she begins to arrive home at 4:30
`each day, she is likely to be uncomfortable and either make
`frequent manual changes or go through the generally non
`intuitive process of reprogramming the thermostat to match
`her new schedule. Because the limited interface on most
`thermostats, that process may take considerable effort, which
`leads many users to avoid reprogramming their thermostats
`for long periods or even to skip doing so entirely.
`But even if a homeowner is able to align her schedule with
`the programming of her thermostat, there are additional dif
`ficulties associated with choosing proper temperatures at
`those times. If the temperatures programmed into a thermo
`stat do not accurately reflect the preferences of the occupants,
`those occupants are likely to resort to manual overrides of the
`programmed settings. The need to correct the “mistakes of
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`the thermostat is likely to annoy many users. And because
`people tend to overshoot the desired temperature when they
`make Such manual changes, these overrides are likely to result
`in excessive heating and cooling, and thus unnecessary
`energy use. That is, if a person feels uncomfortable on a
`Summer afternoon when the setting is 73 degrees, they are
`likely to change it to 68 or 69 rather than 71 or 72 degrees,
`even if 72 degrees might have made enough of a difference.
`It would therefore be advantageous to have a means for
`adapting to signaling from occupants in the form of manual
`temperature changes and incorporating the information con
`tained in Such gestures into long-term programming. It would
`also be desirable to take into account both outside weather
`conditions and the thermal characteristics of individual
`homes in order to improve the ability to dynamically achieve
`the best possible balance between comfort and energy sav
`1ngS.
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`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 shows an example of an overall environment in
`which an embodiment of the invention may be used.
`FIG. 2 shows a high-level illustration of the architecture of
`a network showing the relationship between the major ele
`ments of one embodiment of the subject invention.
`FIG. 3 shows an embodiment of the website to be used as
`part of the subject invention.
`FIG. 4 shows a high-level schematic of the thermostat used
`as part of the Subject invention.
`FIG. 5 shows one embodiment of the database structure
`used as part of the Subject invention.
`FIG. 6 shows how comparing inside temperature against
`outside temperature and other variables permits calculation
`of dynamic signatures.
`FIG. 7 shows how manual inputs can be recognized and
`recorded by the subject invention.
`FIG. 8 shows how the subject invention uses manual inputs
`to interpret manual overrides and make short-term changes in
`response thereto.
`FIG.9 shows how the subject invention uses manual inputs
`to alter long-term changes to interpretive rules and to setpoint
`scheduling.
`FIG. 10 shows an example of some of the contextual data
`that may be used by the server in order to interpret manual
`overrides.
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`DETAILED DESCRIPTION OF THE PREFERRED
`EMBODIMENT
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`FIG. 1 shows an example of an overall environment 100 in
`which an embodiment of the invention may be used. The
`environment 100 includes an interactive communication net
`work 102 with computers 104 connected thereto. Also con
`nected to network 102 are one or more server computers 106,
`which store information and make the information available
`to computers 104. The network 102 allows communication
`between and among the computers 104 and 106.
`Presently preferred network 102 comprises a collection of
`interconnected public and/or private networks that are linked
`to together by a set of standard protocols to form a distributed
`network. While network 102 is intended to refer to what is
`now commonly referred to as the Internet, it is also intended
`to encompass variations which may be made in the future,
`including changes additions to existing standard protocols.
`One popular part of the Internet is the World Wide Web.
`The World WideWeb contains a large number of computers
`104 and servers 106, which store HyperText Markup Lan
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`PETITIONER ECOBEE
`EX. 1001
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`US 8,596,550 B2
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`guage (HTML) and other documents capable of displaying
`graphical and textual information. HTML is a standard cod
`ing convention and set of codes for attaching presentation and
`linking attributes to informational content within documents.
`The servers 106 that provide offerings on the World Wide
`Web are typically called websites. A website is often defined
`by an Internet address that has an associated electronic page.
`Generally, an electronic page is a document that organizes the
`presentation of text graphical images, audio and video.
`In addition to the Internet, the network 102 can comprise a
`wide variety of interactive communication media. For
`example, network 102 can include local area networks, inter
`active television networks, telephone networks, wireless data
`systems, two-way cable systems, and the like.
`Network 102 can also comprise servers 106 that provide
`services other than HTML documents. Such services may
`include the exchange of data with a wide variety of "edge'
`devices, some of which may not be capable of displaying web
`pages, but that can record, transmit and receive information.
`In one embodiment, computers 104 and servers 106 are
`conventional computers that are equipped with communica
`tions hardware such as modem or a network interface card.
`The computers include processors such as those sold by Intel
`and AMD. Other processors may also be used, including
`general-purpose processors, multi-chip processors, embed
`ded processors and the like.
`Computers 104 can also be handheld and wireless devices
`Such as personal digital assistants (PDAs), cellular telephones
`and other devices capable of accessing the network.
`Computers 104 may utilize a browser configured to interact
`with the World Wide Web. Such browsers may include
`Microsoft Explorer, Mozilla, Firefox, Opera or Safari. They
`may also include browsers used on handheld and wireless
`devices.
`The storage medium may comprise any method of storing
`information. It may comprise random access memory
`(RAM), electronically erasable programmable read only
`memory (EEPROM), read only memory (ROM), hard disk,
`floppy disk, CD-ROM, optical memory, or other method of
`storing data.
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`Computers 104 and 106 may use an operating system such
`as Microsoft Windows, Apple Mac OS, Linux, Unix or the
`like.
`Computers 106 may include a range of devices that provide
`information, Sound, graphics and text, and may use a variety
`of operating systems and software optimized for distribution
`of content via networks.
`FIG. 2 illustrates in further detail the architecture of the
`specific components connected to network 102 showing the
`relationship between the major elements of one embodiment
`of the subject invention. Attached to the network are thermo
`stats 108 and computers 104 of various users. Connected to
`thermostats 108 are HVAC units 110. The HVAC units may be
`conventional air conditioners, heat pumps, or other devices
`for transferring heat into or out of a building. Each user may
`be connected to server 106 via wired or wireless connection
`such as Ethernet or a wireless protocol such as IEEE 802.11,
`and router and/or gateway or wireless access point 112 that
`connects the computer and thermostat to the Internet via a
`broadband connection such as a digital subscriber line (DSL)
`or other form of broadband connection to the World Wide
`Web. In one embodiment, thermostat management server 106
`is in communication with the network 102. Server 106 con
`tains the content to be served as web pages and viewed by
`computers 104, as well as databases containing information
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`used by the servers, and applications used to remotely man
`age thermostats 108.
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`In the currently preferred embodiment, the website 200
`includes a number of components accessible to the user, as
`shown in FIG. 3. Those components may include a means to
`store temperature settings 202, a means to enter information
`about the user's home 204, a means to enter the user's elec
`tricity bills 206, and means to elect to enable the subject
`invention 208.
`FIG. 4 shows a high-level block diagram of thermostat 108
`used as part of the subject invention. Thermostat 108 includes
`temperature sensing means 252, which may be a thermistor,
`thermal diode or other means commonly used in the design of
`electronic thermostats. It includes a microprocessor 254,
`memory 256, a display 258, a power source 260, and at least
`one relay 262, which turns the HVAC system on and off in
`response to a signal from the microprocessor, and contacts by
`which the relay is connected to the wires that lead to the
`HVAC system. To allow the thermostat to communicate bi
`directionally with the computer network, the thermostat also
`includes means 264 to connect the thermostatto a local com
`puter or to a wired or wireless network. Such means could be
`in the form of Ethernet, wireless protocols such as IEEE
`802.11, IEEE 802.15.4, Bluetooth, or other wireless proto
`cols. The thermostat may be connected to the computer net
`work directly via wired or wireless Internet Protocol connec
`tion. Alternatively, the thermostat may connect wirelessly to
`a gateway Such as an IP-to-Zigbee gateway, an IP-to-Z-wave
`gateway, or the like. Where the communications means
`enabled include wireless communication, antenna 266 will
`also be included. The thermostat 250 may also include con
`trols 268 allowing users to change settings directly at the
`thermostat, but such controls are not necessary to allow the
`thermostatto function.
`The data used to generate the content delivered in the form
`of the website and to automate control of thermostat 108 is
`stored on one or more servers 106 within one or more data
`bases. As shown in FIG. 5, the overall database structure 300
`may include temperature database 400, thermostat settings
`database 500, energy bill database 600, HVAC hardware data
`base 700, weather database 800, user database 900, transac
`tion database 1000, product and service database 1100 and
`Such other databases as may be needed to Support these and
`additional features.
`The website will allow users of connected thermostats 108
`to create personal accounts. Each user's account will store
`information in database 900, which tracks various attributes
`relative to users. Such attributes may include the make and
`model of the specific HVAC equipment in the user's home;
`the age and square footage of the home, the Solar orientation
`of the home, the location of the thermostat in the home, the
`user's preferred temperature settings, etc.
`As shown in FIG.3, the website 200 will permit thermostat
`users to perform through the web browser substantially all of
`the programming functions traditionally performed directly
`at the physical thermostat, such as temperature set points, the
`time at which the thermostat should be at each set point, etc.
`Preferably the website will also allow users to accomplish
`more advanced tasks Such as allow users to program in Vaca
`tion settings for times when the HVAC system may be turned
`off or run at more economical settings, and set macros that
`will allow changing the settings of the temperature for all
`periods with a single gesture Such as a mouse click.
`In addition to using the system to allow better signaling and
`control of the HVAC system, which relies primarily on com
`munication running from the server to the thermostat, the
`bi-directional communication will also allow the thermostat
`108 to regularly measure and send to the server information
`about the temperature in the building. By comparing outside
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`PETITIONER ECOBEE
`EX. 1001
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`

`5
`temperature, inside temperature, thermostat settings, cycling
`behavior of the HVAC system, and other variables, the system
`will be capable of numerous diagnostic and controlling func
`tions beyond those of a standard thermostat.
`For example, FIG. 6a shows a graph of inside temperature,
`outside temperature and HVAC activity for a 24-hour period.
`When outside temperature 302 increases, inside temperature
`304 follows, but with some delay because of the thermal mass
`of the building, unless the air conditioning 306 operates to
`counteract this effect. When the air conditioning turns on, the
`inside temperature stays constant (or rises at a much lower
`rate or even falls) despite the rising outside temperature. In
`this example, frequent and heavy use of the air conditioning
`results in only a very slight temperature increase inside the
`house of 4 degrees, from 72 to 76 degrees, despite the increase
`in outside temperature from 80 to 100 degrees.
`FIG. 6b shows a graph of the same house on the same day,
`but assumes that the air conditioning is turned off from noon
`to 7 PM. As expected, the inside temperature 304a rises with
`increasing outside temperatures 302 for most of that period,
`reaching 88 degrees at 7 PM. Because server 106 logs the
`temperature readings from inside each house (whether once
`per minute or over Some other interval), as well as the timing
`and duration of air conditioning cycles, database 300 will
`contain a history of the thermal performance of each house.
`That performance data will allow server 106 to calculate an
`effective thermal mass for each such structure—that is, the
`speed with the temperature inside a given building will
`change in response to changes in outside temperature.
`Because the server will also log these inputs against other
`inputs including time of day, humidity, etc. the server will be
`able to predict, at any given time on any given day, the rate at
`which inside temperature should change forgiven inside and
`outside temperatures.
`The ability to predict the rate of change in inside tempera
`ture in a givenhouse under varying conditions may be applied
`by in effect holding the desired future inside temperature as a
`constraint and using the ability to predict the rate of change to
`determine when the HVAC system must be turned on in order
`to reach the desired temperature at the desired time.
`In order to adapt programming to take into account the
`manual overrides entered into the thermostat, it is first neces
`sary to determine when a