INTELLIGENT THERMOSTAT CONTROL SYSTEM

• US 20150159893A1
• Filed: 12/11/2013
• Published: 06/11/2015
• Est. Priority Date: 12/11/2013
• Status: Abandoned Application

• Current Assignee: Generac Power Systems Incorporated (Generac Holdings Incorporated)
• Original Assignee: International Business Machines Corporation
• Inventors: Li, Jenny S., Daubman, Michael S., Doherty, Jessica P., Schoonmaker, Maura K., Tarquinio, Tina M.
• Application Number:
  US14/103,270
• Publication Number:
  US 20150159893A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/56 Remote control
• CPC Class Codes: F24F 11/58 using Internet communication
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: F24F 11/65 for selecting an operating mode
• CPC Class Codes: F24F 11/67 Switching between heating and cooling modes
• CPC Class Codes: F24F 11/70 Control systems characterised by their outputs; Constructional details thereof
• CPC Class Codes: F24F 2110/00 Control inputs relating to air properties
• CPC Class Codes: F24F 2120/10 Occupancy
• CPC Class Codes: F24F 2120/12 Position of occupants
• CPC Class Codes: F24F 2120/14 Activity of occupants
• CPC Class Codes: G05B 13/0265 the criterion being a learning criterion
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G05D 23/1905 associated with tele control
• CPC Class Codes: H04L 12/2816 Controlling appliance services of a home automation network by calling their functionalities arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station; in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00
• CPC Class Codes: H04L 12/2823 Reporting information sensed by appliance or service execution status of appliance services in a home automation network device-related reporting H04L43/065; arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04M 1/72415 : for remote control of appliances
• CPC Class Codes: H04W 4/02 : Services making use of location information
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/33 : for indoor environments, e.g. buildings

Abstract

An intelligent thermostat control system for a building, such as a residential home, that automatically adjusts a thermostat setting in the home based on real-time data continually received from mobile devices and/or social media files associated with the residents. This allows the thermostat controller to override the explicit programmed settings with implicit settings based on activity analysis taking the actual locations and schedules of the residents into account. The intelligent thermostat controller may control different zones differently to take into account the schedules and locations of specific residents associated with specific zones. The temperature controller may also adaptively learn a number of parameters based on monitored data, such as travel times and heating/cooling times for the zones based, to determine times for adjusting the thermostats.

Claims

1. A thermostat control system, comprising:

an intelligent thermostat controller associated with a building operative to adjust at least one thermostat within the building; and

a thermostat control application associated with a mobile unit configured to communicate location information to the thermostat controller indicating a location of the mobile unit;

wherein the thermostat controller is operative to adjust the thermostat based on the location information received from the mobile unit.

2. The thermostat control system of claim 1, wherein the thermostat controller is further operative to adjust the thermostat based on activity analysis including a predicted travel time from the location of the mobile unit to the building.

3. The thermostat control system of claim 1, wherein the thermostat controller is further operative to adjust the thermostat based on an ambient temperature and a predicted heating/cooling response time for the building.

4. The thermostat control system of claim 1, wherein the thermostat controller is further operative to:

receive location information indicating locations of multiple mobile units;

perform activity analysis for multiple residents associated with the mobile units based on the locations of the mobile units;

determine an implicit thermostat setting based on the activity analysis for the multiple residents; and

adjust the thermostat to the implicit thermostat setting.

5. The thermostat control system of claim 1, wherein the thermostat controller is further operative to:

adjust multiple thermostats within the building, wherein each thermostat is associated with a different resident associated with a respective mobile unit;

determine an implicit thermostat setting for each zone based on activity analysis for one or more residents associated with the zone; and

adjust the thermostat for each zone to the implicit thermostat setting for the zone.

6. The thermostat control system of claim 1, wherein the thermostat controller is further operative to:

receive a direct thermostat setting;

adjust the thermostat setting to the direct thermostat setting;

hold the thermostat setting at the direct thermostat setting for a hold period;

conduct activity analysis to determine an implicit thermostat setting based on activity analysis after the hold period; and

adjust the thermostat setting to the implicit thermostat setting determined after the hold period.

7. The thermostat control system of claim 1, wherein the thermostat controller is further operative to:

adaptively learn a predicted travel time from a location of the mobile unit to the building based on experience monitoring travel times; and

adjust the thermostat based on the location information and the adaptively learned travel time.

8. The thermostat control system of claim 1, wherein the thermostat controller is further operative to:

adaptively learn a predicted heating/cooling time for the building based on experience monitoring heating/cooling times; and

adjust the thermostat based on the adaptively learned heating/cooling time.

9. An intelligent thermostat control system, comprising:

a thermostat controller associated with a building operative to adjust at least one thermostat within the building;

wherein the thermostat controller is operative to receive schedule information from a social media file associated with a resident of the building; and

wherein the thermostat controller is operative to adjust the thermostat based on the schedule information received from the social media file.

10. The thermostat control system of claim 9, wherein the thermostat controller is further operative to adjust the thermostat based on activity analysis including a predicted travel time based on the schedule information.

11. The thermostat control system of claim 9, wherein the thermostat controller is further operative to adjust the thermostat based on a predicted heating/cooling response time for the building.

12. The thermostat control system of claim 9, wherein the thermostat controller is further operative to:

receive schedule information associated with multiple residents;

perform activity analysis for the multiple residents based on the schedule information for the multiple residents;

determine an implicit thermostat setting based on the activity analysis for the multiple residents; and

adjust the thermostat to the implicit thermostat setting.

13. The thermostat control system of claim 9, wherein the thermostat controller is further operative to:

adjust multiple thermostats associated with different zones within the building, wherein each thermostat is associated one or more residents;

determine an implicit thermostat setting for each zone based on activity analysis for the residents associated with the zone; and

adjust the thermostat for each zone to the implicit thermostat setting for the zone.

14. The thermostat control system of claim 9, wherein the thermostat controller is further operative to:

receive a direct thermostat setting for a zone;

adjust the thermostat setting for the zone to the direct thermostat setting;

hold the thermostat setting at the direct thermostat setting for a hold period;

conduct activity analysis to determine an implicit thermostat setting based on activity analysis after the hold period; and

adjust the thermostat setting to the implicit thermostat setting determined after the hold period.

15. The thermostat control system of claim 9, wherein the thermostat controller is further operative to:

adaptively learn a predicted travel time from a scheduled activity to the building based on experience monitoring travel times; and

adjust the thermostat based on the schedule information and the adaptively learned travel time.

16. The thermostat control system of claim 9, wherein the thermostat controller is further operative to:

adaptively learn a predicted heating/cooling time for the building based on experience monitoring heating/cooling times; and

adjust the thermostat based on the adaptively learned heating/cooling time.

17. A method for operating an intelligent thermostat control system for a building, comprising:

receiving location information associated with a resident of the building;

receiving schedule information associated with the resident;

performing activity analysis to determine an implicit thermostat setting based on the location information and the schedule information; and

adjusting a thermostat setting in the building to the implicit thermostat setting.

18. The method of claim 17, further comprising:

receiving location information associated with multiple residents of the building;

receiving schedule information associated with the residents;

performing activity analysis to determine an implicit thermostat setting based on the location information and the schedule information for the multiple residents; and

adjusting a thermostat setting in the building to the implicit thermostat setting.

19. The method of claim 18, further comprising:

associating different residents with different zones of the building, wherein each zone has an associated thermostat setting;

determining an implicit thermostat setting for each zone based on the location and schedule data for one or more residents associated with the zone; and

adjusting a thermostat setting for each zone to an implicit thermostat setting determined for the respective zone.

20. The method of claim 17, further comprising:

adaptively learning a travel time and a heating/cooling time for the building based on monitored parameters; and

adjusting the thermostat settings to the implicit setting based on the adaptively learned travel and heating/cooling times.