DEVICES, METHODS, AND SYSTEMS FOR OCCUPANCY DETECTION

• US 20130030732A1
• Filed: 07/27/2011
• Published: 01/31/2013
• Est. Priority Date: 07/27/2011
• Status: Active Grant

• Current Assignee: Ademco Inc. (Resideo Technologies, Inc.)
• Original Assignee: Honeywell International Inc.
• Inventors: Shetty, Pradeep, Foslien, Wendy, Curtner, Keith, Mangsuli, Purnaprajna R., Kolavennu, Soumitri
• Granted Patent: US 9,157,764 B2
• Time in Patent Office: Days
• US Class Current: 702/62
• 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 11/62 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 2120/10 Occupancy
• CPC Class Codes: F24F 2140/60 Energy consumption
• CPC Class Codes: G01D 2204/14 Displaying of utility usage with respect to time, e.g. for monitoring evolution of usage or with respect to weather conditions
• CPC Class Codes: G01D 4/002 Remote reading of utility meters
• CPC Class Codes: G01R 21/133 by using digital technique
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y04S 20/244 the home appliances being or involving heating ventilating and air conditioning [HVAC] units
• CPC Class Codes: Y04S 20/30 Smart metering, e.g. specially adapted for remote reading

Abstract

Devices, methods, and systems for occupancy detection are described herein. One device embodiment includes a memory and a processor coupled to the memory. The processor is configured to execute executable instructions stored in the memory to determine energy consumption data associated with a structure at a point in time, and determine whether the structure is occupied at the point in time based, at least in part, on the determined energy consumption data.

Claims

1. A computing device for occupancy detection, comprising:

a memory; and

a processor coupled to the memory, wherein the processor is configured to execute executable instructions stored in the memory to;

determine energy consumption data associated with a structure at a point in time; and

determine whether the structure is occupied at the point in time based, at least in part, on the determined energy consumption data.

2. The computing device of claim 1, wherein the processor is configured to execute executable instructions stored in the memory to:

determine whether a first portion of the determined energy consumption data meets or exceeds a threshold for the first portion of the determined energy consumption data stored in the memory; and

determine whether a second portion of the determined energy consumption data meets or exceeds a threshold for the second portion of the determined energy consumption data stored in the memory if the first portion of the determined energy consumption data meets or exceeds the first threshold, wherein the structure is occupied at the point in time if the second portion of the determined energy consumption data meets or exceeds the second threshold.

3. The computing device of claim 2, wherein the processor is configured to execute executable instructions stored in the memory to send a communication to a mobile device if the first portion of the determined energy consumption data meets or exceeds the threshold for the first portion of the determined energy consumption data stored in the memory.

4. The computing device of claim 1, wherein the energy consumption data includes a peak current and a rate of change of a current.

5. The computing device of claim 1, wherein the processor is configured to execute executable instructions stored in the memory to send a communication to a programmable thermostat if the structure is occupied at the point in time.

6. The computing device of claim 1, wherein the structure is not occupied at the point in time if the second portion of the determined energy consumption data does not meet or exceed the second threshold.

7. A computer-implemented method for occupancy detection, comprising:

determining energy consumption data associated with a structure at a point in time;

determining whether an anomaly exists within the energy consumption data by comparing a first portion of the energy consumption data to a historical threshold for the first portion of the energy consumption data, wherein an anomaly exists within the energy consumption data if the first portion of the energy consumption data meets or exceeds the historical threshold;

determining, if an anomaly exists within the energy consumption data, whether the anomaly is an anomaly of interest by comparing a second portion of the energy consumption data to a historical threshold for the second portion of the energy consumption data, wherein the anomaly is an anomaly of interest if the second portion of the energy consumption data meets or exceeds the historical threshold for the second portion of the energy consumption data; and

determining whether the structure is occupied at the point in time based, at least in part, on whether the anomaly is an anomaly of interest.

8. The method of claim 7, wherein:

The structure is occupied at the point in time if the anomaly is an anomaly of interest; and

The structure is not occupied at the point in time if the anomaly is not an anomaly of interest.

9. The method of claim 7, wherein the method includes determining whether the structure is occupied at the point in time based, at least in part, on feedback received from a user.

10. The method of claim 7, wherein the method includes determining whether the structure is occupied at the point in time based, at least in part, on GPS data associated with a user.

11. The method of claim 10, wherein the GPS data associated with the user includes:

a GPS location of the user; and

a predicted return time of the user to the structure determined based on the GPS location of the user.

12. The method of claim 7, wherein the method includes determining whether the structure is occupied at the point in time based, at least in part, on a particular day of a week.

13. The method of claim 7, wherein the method includes determining whether the structure is occupied at the point in time based, at least in part, on a particular season of a year.

14. A system for occupancy detection, comprising:

a data acquisition subsystem configured to acquire energy consumption data associated with a structure at a point in time; and

an occupancy determination subsystem configured to;

receive the energy consumption data from the data acquisition subsystem; and

determine whether the structure is occupied at the point in time based, at least in part, on the energy consumption data.

15. The system of claim 14, wherein the data acquisition subsystem is configured to acquire a stepped-down current from a current of the structure, wherein the current of the structure is stepped down by a number of current sensor coils.

16. The system of claim 14, wherein the occupancy determination subsystem is configured to determine whether the structure is occupied at the point in time based, at least in part, on an input from a user at a security system panel associated with the structure.

17. The system of claim 14, wherein the occupancy determination subsystem is configured to determine whether the structure is occupied at the point in time based, at least in part, on an input from an occupancy sensing device.

18. The system of claim 14, wherein the occupancy determination subsystem is configured to communicate with an electronic calendar associated with a user to determine a predicted return time of the user to the structure.

19. The system of claim 14, wherein the occupancy determination subsystem is configured to:

determine a portion of the energy consumption data associated with an occupancy state; and

determine whether the structure is occupied at the point in time based, at least in part, on the portion of the energy consumption data.

20. The system of claim 14, wherein the energy consumption data acquisition subsystem is configured to communicate with an electric service panel of the structure.