Occupancy pattern detection, estimation and prediction
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-009/44
G06N-007/02
G06N-007/04
출원번호
US-0881430
(2010-09-14)
등록번호
US-8510255
(2013-08-13)
발명자
/ 주소
Fadell, Anthony Michael
Rogers, Matthew Lee
Rogers, Kipp Avery
Ishihara, Abraham K.
Ben-Menahem, Shahar
Sharan, Rangoli
출원인 / 주소
Nest Labs, Inc.
대리인 / 주소
Kilpatrick Townsend & Stockton LLP
인용정보
피인용 횟수 :
67인용 특허 :
40
초록▼
Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of
Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.
대표청구항▼
1. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermost
1. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, communication signals which indicate a likelihood of occupancy of the enclosure ranging from not occupied to occupied;revising the model of occupancy patterns based at least in part on the monitored communication signals; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored communication signals. 2. A method according to claim 1 wherein in the communication signals is one or more network connections and the monitoring includes monitoring for changes in network communications which indicate a likelihood of occupancy. 3. A method according to claim 2 wherein the one or more network connections include a network connection of a type selected from a group consisting of: wi-fi and email. 4. A method according to claim 2 wherein the changes in network communication includes monitoring changes in network traffic which indicate a likelihood of internet usage. 5. A method according to claim 1 wherein the communication signals are radio frequency communication signals. 6. A method according to claim 5 wherein the communication signals are mobile phone signals. 7. A method according to claim 1 wherein the enclosure is a single family dwelling. 8. A method according to claim 1 further comprising controlling an HVAC system for the enclosure based at least in part on the probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the pre-existing model of occupancy patterns. 9. A method according to claim 1 further comprising controlling an HVAC system for the enclosure based at least in part on the probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns. 10. A method according to claim 1 wherein the communication signals are monitored for patterns which indicate a likelihood of occupancy. 11. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, sound pressure information which indicates a likelihood of occupancy of the enclosure ranging from not occupied to occupied;revising the model of occupancy patterns based at least in part on the monitored pressure information; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored pressure information. 12. A method according to claim 11 wherein the sound pressure monitored is in the audible range. 13. A method according to claim 12 wherein the types of sounds monitored include one or more types selected from a group consisting of: footsteps, voices, and doors closing. 14. A method according to claim 11 wherein the sound pressure monitored is in the ultrasonic range. 15. A method according to claim 14 wherein the types of sounds monitored include one or more types selected from a group consisting of footsteps, and air movement due to human movement. 16. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, utility information for the enclosure which indicates a likelihood of occupancy of the enclosure ranging from not occupied to occupied;revising the model of occupancy patterns based at least in part on the monitored utility information; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored utility information. 17. A method according to claim 16 wherein the utility information is powerline information, and the powerline information is filtered to detect the use of electronic devices which indicate a likelihood of occupancy in the enclosure. 18. A method according to claim 16 wherein the utility information is obtained from a Smart Meter that tends to indicate a likelihood of occupancy in the enclosure. 19. A method according to claim 18 wherein pattern recognition is used to monitor changes in the utility information from a baseline to detect likelihoods of occupancy of the enclosure. 20. A method according to claim 16 wherein the enclosure is a dwelling. 21. A system for detecting occupancy of an enclosure comprising: a processing system adapted to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to the processing system at the time of installation of the processing system in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day; anda sensing system adapted to monitor, after installation of the sensing system in the enclosure, utility information for the enclosure which indicates a likelihood of occupancy of the enclosure ranging from not occupied to occupied;the processing system being further adapted to revise the model of occupancy patterns based at least in part on the monitored utility information by the sensing system, and to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored utility information. 22. A system according to claim 21 wherein the utility information is powerline information, and the powerline information is filtered to detect the use of electronic devices which indicate a likelihood of occupancy in the enclosure. 23. A system according to claim 21 wherein the utility information is obtained from a Smart Meter that tends to indicate a likelihood of occupancy in the enclosure. 24. A system according to claim 23 wherein pattern recognition is used by the processing system to monitor changes in the utility information from a baseline to detect likelihoods of occupancy of the enclosure. 25. A system according to claim 21 wherein the enclosure is a dwelling. 26. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, motion information from a sensor;revising the model of occupancy patterns based at least in part on the monitored motion information; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored motion information. 27. A method according to claim 26 wherein the sensor is an accelerometer and the motion information is acceleration information monitored within one meter of the sensor. 28. A method according to claim 26, further comprising preparing a device for interaction with a user based on the monitored motion information. 29. A method according to claim 26 wherein the enclosure is a small dwelling. 30. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, infrared signals within the enclosure which indicate operation of one or more infrared controllable devices;revising the model of occupancy patterns of the enclosure based at least in part on the monitored infrared signals; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored infrared signals. 31. A method according to claim 30 wherein the infrared signals indicate remote control of one or more electronic devices by an occupant. 32. A method according to claim 30 wherein the enclosure is a dwelling. 33. A system for detecting occupancy of an enclosure comprising: a processing system adapted to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to the processing system at the time of installation of the processing system in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day; andan infrared sensor adapted to monitor, after installation of the infrared sensor in the enclosure, infrared signals within the enclosure which indicate operation of one or more infrared controllable devices;the processing system being further adapted to revise the model of occupancy patterns based at least in part on the monitored infrared signals by the infrared sensor, and to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored infrared signals. 34. A system according to claim 33 wherein the infrared signals indicate remote control of one or more electronic devices by an occupant. 35. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, pressure information within the enclosure which indicates occupancy of the enclosure;revising the model of occupancy patterns based at least in part on the monitored pressure information; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored pressure information. 36. A method according to claim 35 wherein the pressure information includes change in atmospheric pressure in the enclosure that indicate opening of doors and/or windows. 37. A method according to claim 35 wherein the enclosure is a dwelling. 38. A system for detecting occupancy of an enclosure comprising: a processing system adapted to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to the processing system at the time of installation of the processing system in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day; anda pressure sensor adapted to monitor, after installation of the pressure sensor in the enclosure, pressure information within the enclosure which indicates occupancy of the enclosure;the processing system being further adapted to revise the model of occupancy patterns based at least in part on the monitored pressure information by the pressure sensor, and to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored pressure information. 39. A system according to claim 38 wherein the pressure information includes change in atmospheric pressure in the enclosure that indicate opening of doors and/or windows. 40. A method for detecting occupancy of an enclosure comprising: determining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to a thermostat at the time of installation of the thermostat in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day;monitoring, by the thermostat after installation of the thermostat in the enclosure, ambient light information within the enclosure which indicates occupancy of the enclosure;revising the model of occupancy patterns based at least in part on the monitored ambient light information; anddetermining a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored ambient light information. 41. A method according to claim 40 wherein the ambient light information includes rapid changes in ambient light in the enclosure that tends to indicate switching on and off of lights or sudden opening or closing of blinds and/or curtains. 42. A method according to claim 40 wherein the ambient light information includes wavelength composition of incident light that tends to indicate whether the light source is artificial or natural. 43. A method according to claim 40 wherein the enclosure is a dwelling. 44. A system for detecting occupancy of an enclosure comprising: a processing system adapted to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on a pre-existing model of occupancy patterns, the pre-existing model being available to the processing system at the time of installation of the processing system in the enclosure, the model being indicative of a probability that occupants of the enclosure will depart from and arrive at the enclosure at certain times over the course of a day; andan ambient light sensor adapted to monitor, after installation of the ambient light sensor in the enclosure, ambient light information within the enclosure which indicates occupancy of the enclosure;the processing system being further adapted to revise the model of occupancy patterns based at least in part on the monitored ambient light information by the ambient light sensor, and to determine a probability that occupants of the enclosure will depart from or arrive at the enclosure at a certain time of the day based on the revised model of occupancy patterns,wherein the pre-existing model is generated based on a type of information other than the monitored ambient light information. 45. A system according to claim 44 wherein the ambient light information includes rapid changes in ambient light in the enclosure that tends to indicate turning on and off of lights or opening and closing of blinds and/or curtains. 46. A system according to claim 44 wherein the ambient light information includes whether ambient light is from artificial source that tends to indicate presence of occupants in certain structure types.
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이 특허에 인용된 특허 (40)
Dewolf Thomas L. (8139 Portobello Way Liverpool NY 13090) Phillips Thomas R. (6108 Gaspe La. Cicero NY 13041) Bench Ronald W. (8535 Farmgate Path Cicero NY 13041), Active anticipatory control.
Levine Michael R. (Ann Arbor MI), Analog to digital conversion employing the system clock of a microprocessor, the clock frequency varying with analog inp.
Berglund Ulf Stefan,SEX ; Lundberg Bjorn Henry,SEX, Comfort control system incorporating weather forecast data and a method for operating such a system.
Michael Lee Simmons ; Dominick J. Gibino, Energy-saving occupancy-controlled heating ventilating and air-conditioning systems for timing and cycling energy within different rooms of buildings having central power units.
Williams Christopher D. ; Goldschmidt Iti Jean M. ; Shah-Nazaroff Anthony A. ; Watts E. Michael ; Moore Kenneth Alan ; Hackson David N., Method and apparatus for automatically configuring a system based on a user's monitored system interaction and preferre.
Chapman, Jr.,John Gilman; Ashworth,Nicholas; Burt,Robert; Wallaert,Timothy E.; Rao,Joseph P., System and method for controlling appliances and thermostat for use therewith.
Cheung, Leo; Hublou, Scott Douglas; Steinberg, John Douglas, System and method for using ramped setpoint temperature variation with networked thermostats to improve efficiency.
Peterson, Kevin Charles; Le Guen, Sophie; Veron, Maxime; Modi, Yash; Au, Lawrence; Malhotra, Mark Rajan; DeIuliis, Julia, Alarm arming with open entry point.
Peterson, Kevin Charles; Le Guen, Sophie; Veron, Maxime; Modi, Yash; Au, Lawrence; Malhotra, Mark Rajan; Deluliis, Julia, Alarm arming with open entry point.
Kinney, Abraham Joseph; Kerzner, Daniel Todd; Hutz, David James, Detection of authorized user presence and handling of unauthenticated monitoring system commands.
Angle, Colin; Snelling, David; O'Dea, Melissa; Farlow, Timothy S.; Duffley, Samuel; Mammen, Jeffrey W.; Halloran, Michael J., Environmental management systems including mobile robots and methods using same.
Angle, Colin; Snelling, David; O'Dea, Melissa; Farlow, Timothy S.; Duffley, Samuel; Mammen, Jeffrey W.; Halloran, Michael J., Environmental management systems including mobile robots and methods using same.
Fadell, Anthony Michael; Rogers, Matthew Lee; Matsuoka, Yoky; Sloo, David; Honjo, Shigefumi; McGaraghan, Scott A.; Plitkins, Michael; Veron, Maxime; Guenette, Isabel, Environmental sensing with a doorbell at a smart-home.
Fadell, Anthony Michael; Matsuoka, Yoky; Sloo, David; Plitkins, Michael; Matas, Michael James; Rogers, Matthew Lee; Fisher, Evan J., HVAC control system encouraging energy efficient user behaviors in plural interactive contexts.
Fadell, Anthony Michael; Rogers, Matthew Lee; Matsuoka, Yoky; Sloo, David; Honjo, Shigefumi; McGaraghan, Scott A.; Plitkins, Michael; Veron, Maxime; Guenette, Isabel, Handling visitor interaction at a smart-home in a do not disturb mode.
Fadell, Anthony Michael; Rogers, Matthew Lee; Matsuoka, Yoky; Sloo, David; Honjo, Shigefumi; McGaraghan, Scott A.; Plitkins, Michael; Veron, Maxime; Guenette, Isabel, Initially detecting a visitor at a smart-home.
Warren, Daniel Adam; Fiennes, Hugo; Dutra, Jonathan Alan; Bell, David; Fadell, Anthony Michael; Rogers, Matthew Lee; Smith, Ian C.; Satterthwaite, Jr., Edwin H.; Palmer, Joseph E.; Erickson, Grant M.; Mucignat, Andrea; Sloo, David, Installation of thermostat powered by rechargeable battery.
Warren, Daniel Adam; Fiennes, Hugo; Dutra, Jonathan Alan; Bell, David; Fadell, Anthony Michael; Rogers, Matthew Lee; Smith, Ian C.; Satterthwaite, Jr., Edwin H.; Palmer, Joseph E.; Erickson, Grant M.; Mucignat, Andrea; Sloo, David, Installation of thermostat powered by rechargeable battery.
Sinha, Sudhi; Ribbich, Joseph R.; Ribbich, Michael L.; Gaidish, Charles J.; Cipolla, John P., Multi-function thermostat with emergency direction features.
Warren, Daniel Adam; Fiennes, Hugo; Dutra, Jonathan Alan; Bell, David; Fadell, Anthony Michael; Rogers, Matthew Lee; Smith, Ian C.; Satterthwaite, Edwin H.; Palmer, Joseph E.; Erickson, Grant M.; Mucignat, Andrea, Power management in energy buffered building control unit.
Fadell, Anthony M.; Rogers, Matthew L.; Sloo, David; Plitkins, Michael; Honjo, Shigefumi; Filson, John B.; Matas, Michael J.; Bould, Fred; Huppi, Brian, Round thermostat with flanged rotatable user input member and wall-facing optical sensor that senses rotation.
Alberte, Jr., Robert J.; Friedman, Bruce A.; Brozowski, Paul R., System and method for proactive communication network management based upon area occupancy.
Sloo, David; Fadell, Anthony Michael; Rogers, Matthew Lee; Plitkins, Michael; Matas, Michael James; Hales, IV, Steven A., Systems and methods for a graphical user interface of a controller for an energy-consuming system having spatially related discrete display elements.
Shetty, Pradeep; Foslien, Wendy; Curtner, Keith; Mangsuli, Prunaprajna R.; Kolavennu, Soumitri, Systems and methods for managing a programmable thermostat.
Shetty, Pradeep; Foslien, Wendy; Curtner, Keith; Mangsuli, Purnaprajna R.; Kolavennu, Soumitri, Systems and methods for managing a programmable thermostat.
Fadell, Anthony Michael; Rogers, Matthew Lee; Rogers, Kipp Avery; Ishihara, Abraham K.; Ben-Menahem, Shahar; Sharan, Rangoli, Thermodynamic modeling for enclosures.
Warren, Daniel Adam; Fiennes, Hugo; Dutra, Jonathan Alan; Bell, David; Fadell, Anthony Michael; Rogers, Matthew Lee, Thermostat circuitry for connection to HVAC systems.
Fadell, Anthony M.; Rogers, Matthew L.; Sloo, David; Plitkins, Michael; Honjo, Shigefumi; Filson, John B.; Matas, Michael J.; Bould, Fred; Huppi, Brian, Thermostat user interface.
Ribbich, Joseph R.; Diptee, Vinosh C.; Abdala, Juilio A.; Ribeiro, Claudio Santiago; Gaidish, Charles J.; Kornacki, Michael F.; Cipolla, John P.; Sinha, Sudhi; Ribbich, Michael L., User control device with cantilevered display.
Fadell, Anthony Michael; Rogers, Matthew Lee; Matsuoka, Yoky; Sloo, David; Honjo, Shigefumi; McGaraghan, Scott A.; Plitkins, Michael; Veron, Maxime; Guenette, Isabel, Visitor feedback to visitor interaction with a doorbell at a smart-home.
Fadell, Anthony Michael; Rogers, Matthew Lee; Matsuoka, Yoky; Sloo, David; Honjo, Shigefumi; McGaraghan, Scott A.; Plitkins, Michael; Veron, Maxime; Guenette, Isabel, Visitor options at an entryway to a smart-home.
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