Providing notifications to a user

• US 9,152,737 B1
• Filed: 05/08/2015
• Issued: 10/06/2015
• Est. Priority Date: 11/26/2014
• Status: Active Grant

• Current Assignee: Sense Labs, Inc.
• Original Assignee: Sense Labs, Inc.
• Inventors: Micali, Christopher M., Houlette, Ryan T., Phillips, Michael S., Choueiter, Ghinwa F.
• Primary Examiner(s): SHAW, PELING ANDREW
• Application Number:
  US14/707,738
• Time in Patent Office: 151 Days
• US Class Current: 1/1
• CPC Class Codes: G01R 21/133 by using digital technique
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: H02J 13/00 Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
• 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: 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: Y04S 20/20 End-user application control systems

Abstract

Electrical usage of devices in a building may be monitored to determine information about the operation of the devices in the building, and the information about the devices in the building may be used to provide notifications to a user. An electrical signal may be processed to determine a state change of a device. A notification score may then be determined using information about the state change of the device and a notification event model. A notification may then be sent to the user based at least in part on the notification event score.

Claims

1. A computer-implemented method for providing a notification to a user, the method comprising:

receiving an electrical signal from a building, wherein the electrical signal corresponds to a plurality of devices;

computing a plurality of features from the electrical signal;

selecting a first state change of first device in the building using the plurality of features and a first model;

computing a first notification score corresponding to a first notification event using a first notification event model and the first state change of the first device;

determining to send a first notification to the user using the first notification score, wherein the first notification corresponds to the first notification event;

causing the first notification to be sent to the user.

2. The method of claim 1, wherein the first notification indicates that the first device has been in a first state for longer than a period of time, that the first device is in the first state during a time of day, that the first device has completed an operation, or that the first device needs maintenance or repair.

3. The method of claim 1 further comprising:

determining that a mobile device is not present in the building; and

wherein determining to send a first notification to the user is further based at least in part on determining that the mobile device is not present in the building.

4. The method of claim 1, wherein causing the first notification to be sent to the user comprises causing a message to be sent to a mobile device of the user, causing the first notification to be presented on a web page, or causing the first notification to be displayed in an application running on a mobile device.

5. The method of claim 1 further comprising:

computing a first confidence score corresponding to the selection of the first state change of the first device; and

wherein computing a first notification score comprises using the first confidence score.

6. The method of claim 5 wherein the first confidence score is computed using at least one of a noise level of the electrical signal and an accuracy of the first model.

7. The method of claim 1, wherein the first notification event model comprises a neural network, a support vector machine, a decision tree, a random forest, or a Gaussian mixture model.

8. A system for providing a notification to a user, the system comprising:

one or more computing devices comprising at least one processor and at least one memory, the one or more computing devices configured to;

receive an electrical signal from a building, wherein the electrical signal corresponds to a plurality of devices;

compute a plurality of features from the electrical signal;

select a first state change of first device in the building using the plurality of features and a first model;

compute a first notification score corresponding to a first notification event using a first notification event model and the first state change of the first device;

determine to send a first notification to the user using the first notification score, wherein the first notification corresponds to the first notification event;

cause the first notification to be sent to the user.

9. The system of claim 8, wherein the one or more computing devices are further configured to receive user preferences indicating a request from the user to receive notifications corresponding to the first notification event.

10. The system of claim 8, wherein the one or more computing devices determine to send the first notification to the user by using information obtained via the Internet using an API or using information received on a local area network from another device.

11. The system of claim 8, wherein the first notification event model was trained using the electrical signal from the building and an indication from a user that a first notification event occurred at a first time or during a first time period.

12. The system of claim 8, wherein the one or more computing devices are further configured to:

receive information about a location of the user; and

determine to send a first notification to the user based at least in part on the location of the user.

13. The system of claim 12, wherein the one or more computing devices receive information about the location of the user from a mobile device of the user.

14. The system of claim 8, wherein the first notification event model comprises a neural network, a support vector machine, a decision tree, a random forest, or a Gaussian mixture model.

15. One or more non-transitory computer-readable media comprising computer executable instructions that, when executed, cause at least one processor to perform actions comprising:

receiving information about a first state change of first device in a building, wherein the first state change of the first device was determined by processing an electrical signal, and wherein the electrical signal corresponds to a plurality of devices;

computing a first notification score corresponding to a first notification event using a first notification event model and the first state change of the first device;

determining to send a first notification to the user using the first notification score, wherein the first notification corresponds to the first notification event;

causing the first notification to be sent to the user.

16. The one or more non-transitory computer-readable media of claim 15, wherein the computer executable instructions further cause the at least one processor to perform actions comprising:

determining a priority of the first notification; and

determining a time for delivery of the first notification using the priority.

17. The one or more non-transitory computer-readable media of claim 15, wherein determining to send the first notification to the user comprises using information obtained via the Internet using an API or using information received on a local area network from another device.

18. The one or more non-transitory computer-readable media of claim 15, wherein the computer executable instructions further cause the at least one processor to perform actions comprising:

computing a second notification score corresponding to a second notification event using a second notification event model and the first state change of the first device; and

determining not to send a second notification to the user using the second notification score.

19. The one or more non-transitory computer-readable media of claim 15 wherein the computer executable instructions further cause the at least one processor to perform actions comprising:

computing a first confidence score corresponding to the first notification score; and

determining to send the first notification to the user using the first confidence score.

20. The one or more non-transitory computer-readable media of claim 15, wherein the first notification event model comprises a neural network, a support vector machine, a decision tree, a random forest, or a Gaussian mixture model.