HVAC SCHEDULE ESTABLISHMENT IN AN INTELLIGENT, NETWORK-CONNECTED THERMOSTAT

• US 20140058567A1
• Filed: 03/15/2013
• Published: 02/27/2014
• Est. Priority Date: 11/19/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Nest Labs Incorporated (Alphabet Inc.)
• Inventors: Matsuoka, Yoky, Fadell, Anthony M., Rogers, Matthew L., Sloo, David, Lee, Eric A., Hales, Steven A., Stefanski, Mark D., Sharan, Rangoli
• Granted Patent: US 9,256,230 B2
• Time in Patent Office: Days
• US Class Current: 700/276
• 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 11/52 Indication arrangements, e.g. displays
• CPC Class Codes: F24F 11/526 giving audible indications
• CPC Class Codes: F24F 11/58 using Internet communication
• CPC Class Codes: F24F 11/59 for presetting
• CPC Class Codes: F24F 11/61 using timers
• 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 2110/00 Control inputs relating to air properties
• CPC Class Codes: F24F 2120/20 Feedback from users
• CPC Class Codes: G01R 22/10 using digital techniques
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/0423 Input/output
• CPC Class Codes: G05B 19/106 for selecting a programme, variable or parameter
• 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 23/1904 variable in time
• CPC Class Codes: G05D 23/1917 using digital means
• CPC Class Codes: H04L 12/2825 Reporting to a device located outside the home and the home network access arrangements H04L12/2856; for remote control or remote monitoring of applications H04L67/025; telephonic communication systems adapted for combination with telemetering systems H04M11/002
• CPC Class Codes: H04L 12/40013 : Details regarding a bus controller
• CPC Class Codes: H04L 2012/285 : Generic home appliances, e.g. refrigerators

Abstract

HVAC schedules may be programmed for a thermostat using a combination of pre-existing schedules or templates and automated schedule learning. For example, a pre-existing schedule may be initiated on the thermostat and the automated schedule learning may be used to update the pre-existing schedule based on users'"'"' interactions with the thermostat. The preexisting HVAC schedules may be stored on a device or received from a social networking service or another online service that includes shared HVAC schedules.

Claims

1. A method for programming an HVAC schedule for a thermostat, comprising:

generating one or more input options on a schedule interface;

receiving input corresponding to one or more responses to the one or more input options, wherein the input is received at the schedule interface;

selecting an HVAC schedule from one or more of a plurality of pre-existing HVAC schedules stored on the thermostat, wherein the selection of the HVAC schedule is based on the received input;

associating the thermostat with the selected HVAC schedule, wherein associating includes initiating the selected HVAC schedule on the thermostat;

receiving, during a time period subsequent to the association, input corresponding to one or more temperature control selections, wherein the input is received on a control interface;

generating an updated HVAC schedule based on the selected HVAC schedule and the one or more temperature control selections; and

associating the thermostat with the updated HVAC schedule, wherein associating includes initiating the updated HVAC schedule on the thermostat.

2. The method of claim 1, wherein the schedule interface is a web-based interface or provided at a display of the thermostat.

3. The method of claim 1, wherein the input option is visually or audibly generated.

4. The method of claim 1, wherein the received input is an audio input.

5. The method of claim 1, wherein the plurality of pre-existing HVAC schedules is stored on a server accessible by the thermostat.

6. The method of claim 1, wherein the input options correspond to inquiries, and wherein the received input can correspond to one or more of a plurality of pre-existing schedule paradigms, and wherein the plurality of pre-existing schedule paradigms correspond to one or more of the pre-existing HVAC schedules stored on the thermostat.

7. The method of claim 6, wherein the inquiries include one or more of the following:

“

Do children live at this residence?”

, “

Tell me about yourself.”

, and “

Is this business open on the weekends?”

.

8. The method of claim 6, wherein the plurality of preexisting schedule paradigms include one or more of the following:

working couple without kids, working spouse with stay-at-home spouse, young people with active nightlife who work from home, office building, and businesses open only on the weekdays.

9. The method of claim 6, wherein one or more of the input options is generated based on based on at least one of the one or more responses.

10. The method of claim 6, wherein the plurality of pre-existing HVAC schedules includes a null HVAC schedule, and wherein the null HVAC schedule is the selected HVAC schedule when the received input does not correspond to one or more of the plurality of pre-existing schedule paradigms.

11. The method of claim 10, wherein the HVAC schedule includes time intervals with temperature selections corresponding to each of the time intervals.

12. The method of claim 11, wherein generating the updated HVAC schedule based on the selected HVAC schedule and the one or more temperature control selections comprises:

processing the received one or more temperature control selections to detect one or more intended new temperature selections, the detected one or more intended new temperature selections corresponding to one of the time intervals;

replicating the detected one or more intended new temperature selections throughout the corresponding time intervals;

overlaying the replicated one or more intended new temperature selections and the detected one or more intended new temperature selections onto the selected HVAC schedule; and

mutually filtering the overlayed new temperature selections and temperature selections of the selected HVAC schedule according to a predetermined filtering algorithm to generate the updated schedule.

13. The method of claim 12, wherein processing the received one or more temperature control selections to detect the one or more new temperature selections for the time period comprises:

clustering temperature control selections of the received one or more temperature control selections into clusters, wherein each of the clusters corresponds to a temperature selection at a point in time within one of the time intervals, wherein each of the received one or more temperature control selections correspond to a point in time, and wherein the received one or more temperature control selections that occur at nearby points in time are clustered into the same cluster;

harmonizing the one or more temperature control selections of each of the one or more of the clusters according to predetermined harmonization rules to generate single candidate temperature selections representative of each one of the clusters;

comparing one or more of the single candidate temperature selections to others of the single candidate temperature selections that correspond to similar points of time within the times intervals to detect patterns of similar candidates over multiple time intervals; and

establishing one or more of the single candidate temperature selections as one or more of the one or more intended new temperature selections if a pattern-establishing threshold of a number of similar candidates is met.

14. The method of claim 13, wherein generating the updated HVAC schedule based on the selected HVAC schedule and the one or more temperature control selections is characterized by one or more of aggressive and steady state learning phases, the pattern-establishing threshold of the steady state learning phase being larger than the pattern-establishing threshold of the aggressive state learning phase, wherein, if the null schedule is the selected HVAC schedule, the aggressive state learning phase is applied before the steady state learning phase is applied, and wherein, if the null schedule is not the selected HVAC schedule, only the steady state learning phase is applied.

15. A method for programming an HVAC schedule for a thermostat, comprising:

receiving input corresponding to a selection of a pre-existing HVAC schedule, wherein the pre-existing HVAC schedule was shared on a social networking service,

associating the thermostat with the selected pre-existing HVAC schedule, wherein associating includes initiating the selected pre-existing HVAC schedule on the thermostat;

receiving, during a time period subsequent to the association, input corresponding to one or more temperature control selections, wherein the input is received on a control interface;

generating an updated HVAC schedule based on the selected pre-existing HVAC schedule and the one or more temperature control selections; and

associating the thermostat with the updated HVAC schedule, wherein associating includes initiating the updated HVAC schedule on the thermostat.

16. The method of claim 15, wherein the selection of the pre-existing HVAC schedule is based on one or more of the following:

a social profile corresponding to the pre-existing HVAC, a location where the pre-existing HVAC schedule was generated, one or more responses to one or more input options, and a metric of efficiency corresponding to the pre-existing HVAC schedule.

17. The method of claim 15, wherein the selected pre-existing HVAC schedule was included on a list of recommended pre-existing HVAC schedules, and wherein the list of recommended pre-existing HVAC schedules was generated based on one or more of the following:

a social profile corresponding to the pre-existing HVAC, a location where the pre-existing HVAC schedule was generated, one or more responses to one or more input options, and a metric of efficiency corresponding to the pre-existing HVAC schedule.

18. The method of claim 15, social networking service is an online gaming service.

19. The method of claim 15, further including sharing the updated HVAC schedule on a social network service.

20. The method of claim 15, wherein the selected pre-existing HVAC schedule includes time intervals with temperature selections corresponding to each of the time intervals.

21. The method of claim 20, wherein generating the updated HVAC schedule based on the selected pre-existing HVAC schedule and the one or more temperature control selections comprises:

processing the received one or more temperature control selections to detect one or more intended new temperature selections, the detected one or more intended new temperature selections corresponding to one of the time intervals;

replicating the detected one or more intended new temperature selections throughout the corresponding time intervals;

overlaying the replicated one or more intended new temperature selections and the detected one or more intended new temperature selections onto the selected pre-existing HVAC schedule; and

mutually filtering the overlayed new temperature selections and temperature selections of the selected pre-existing HVAC schedule according to a predetermined filtering algorithm to generate the updated schedule.

22. The method of claim 21, wherein processing the received one or more temperature control selections to detect the one or more new temperature selections for the time period comprises:

clustering temperature control selections of the received one or more temperature control selections into clusters, wherein each of the clusters corresponds to a temperature selection at a point in time within one of the time intervals, wherein each of the received one or more temperature control selections correspond to a point in time, and wherein the received one or more temperature control selections that occur at nearby points in time are clustered into the same cluster;

harmonizing the one or more temperature control selections of each of the one or more of the clusters according to predetermined harmonization rules to generate single candidate temperature selections representative of each one of the clusters;

comparing one or more of the single candidate temperature selections to others of the single candidate temperature selections that correspond to similar points of time within the times intervals to detect patterns of similar candidates over multiple time intervals; and

establishing one or more of the single candidate temperature selections as one or more of the one or more intended new temperature selections if a pattern-establishing threshold of a number of similar candidates is met.

23. The method of claim 22, wherein generating the updated HVAC schedule based on the selected HVAC schedule and the one or more temperature control selections is characterized by a steady state learning phase.