Granted Patent B1

US 11,488,077 · App. 15/885,320 · Granted Nov 1, 2022

Inventors: Jefferson Huhta Lyman (Alpine, UT); Janelle Kim Seegmiller (South Jordan, UT); Kyle Redfearn (Cedar Hills, UT)

Assignee: VIVINT, INC.

G06Q10/06311H04L12/2825G06Q10/1095

Abstract

Claims (80)

1. A method for smart sensing using a control panel of a home automation system, comprising:

determining, by a processor of the control panel of the home automation system, a parameter of a resource associated with a home;

monitoring the parameter of the resource based on sensor data captured by a plurality of sensors that are communicatively coupled to the control panel of the home automation system;

predicting, by the processor of the control panel of the home automation system, a future change in condition associated with the parameter satisfying a threshold as detected by a sensor, the predicting based at least in part on a machine learning model, the machine learning model trained on previously captured sensor data associated with the monitored parameter;

in response to predicting the future change in condition satisfies the threshold, performing a function that includes generating a first message, for display on a device of the individual associated with the home automation system, comprising selectable options, wherein the selectable options include a first option to display a set of recommended actions to perform by the home automation system based at least in part on the future change in condition and a second option to view a time-lapse of the resource associated with the monitored parameter, wherein the time-lapse is generated based on a detected change in an attribute across video frames;

transmitting the first message to the device of the individual and receiving selection of the first option;

in response to receiving selection of the first option, generating a second message with at least one recommended option that includes scheduling a service appointment;

receiving selection of the at least one recommended option and scheduling, by the processor of the control panel of the home automation system, a service personnel to perform a service associated with the resource based on the predicted future change in condition;

detecting, by the processor of the control panel of the home automation system, the service personnel at the home based on sensor data; and

actuating, by the processor of the control panel of the home automation system and in response to validating that the service personnel arrives at a time that is within a threshold time of a scheduled time for the service, an access point to the home to provide the service personnel access into the home for performing the service associated with the resource.

2. The method of claim 1 , wherein monitoring the parameter of the resource comprises:

receiving real-time usage data of the resource from the sensor; and

tracking real-time usage data based at least in part on the received real-time usage data,

wherein performing the function is based at least in part on tracking the real-time usage data.

3. The method of claim 1 , wherein the resource comprises a service or a product.

4. The method of claim 2 , further comprising:

identifying a service or a product, or both;

retrieving, from a database, historical usage data associated with the service or the product, or both based at least in part on the identifying; and

comparing the retrieved historical usage data with the real-time usage data to compute a usage model, wherein predicting the future change in condition associated with the parameter is based at least in part on the usage model.

5. The method of claim 1 , wherein the function is performed automatically based at least in part on a pre-configured setting of the home automation system.

6. The method of claim 5 , further comprising:

identifying that the resource is a service;

identifying schedule data of the individual associated with the home; and

automatically scheduling the service personnel to visit the home and perform an action associated with the service based at least in part on the schedule data of the individual.

7. The method of claim 6 , wherein automatically scheduling the service personnel comprises:

identifying a service provider associated with the service based at least in part on the pre-configured setting; and

transmitting, to a remote device of the service provider, a message indicating a service request, wherein the message comprises at least one of a payment information, a geolocation information of the home, a contact information of the individual, or any combination thereof.

8. The method of claim 7 , further comprising:

receiving, from the remote device, an acknowledgment message in response to the service request.

9. The method of claim 7 , wherein the validating comprises:

detecting the service personnel based at least in part on sensor data received from a second sensor;

identifying a time associated with the detecting; comparing the identified time to a scheduled service time;

validating that the identified time is within a threshold limit of the scheduled service time; and

providing, to a device of the service personnel, access information to the home based at least on the validating, wherein the access information comprises at least one of a random code, a personal identification number (PIN), or instructions for providing the service to a designated zone of the home, or any combination thereof,

wherein actuating the access point comprises providing to the device of the service personnel the access information to the home.

10. The method of claim 9 , further comprising:

operating a garage door opener based at least in part on the validating, wherein actuating the access point comprises operating the garage door opener.

11. The method of claim 3 , further comprising:

determining that the resource is a product comprising an apparatus;

identifying a usage rate of the apparatus based at least in part on a usage model of automatically requesting a maintenance order with a third-party enterprise to provide a maintenance service of the apparatus.

12. The method of claim 11 , further comprising: establishing a connection with the apparatus; and

retrieving specification information associated with the apparatus based at least in part on performing a scan using the established connection, wherein the specification information comprises warranty coverage information, appliance repair and support information, vendor information, an energy consumption and cost report of operating the apparatus, or any combination thereof.

13. The method of claim 1 , wherein the resource is a home management service or a personal service related to the individual associated with the home.

14. The method of claim 13 , wherein the home management service comprises at least one of a gardening and lawn care service, an internet-provider service, a housekeeping service, a laundry service, a plumbing service, a maintenance service, a termite and pest control service, a water softener service, or any combination thereof.

15. The method of claim 13 , wherein the personal service comprises at least one of a babysitting service, a nursing care service, a pet sitting service, a medical provider visit service, or any combination thereof.

16. An apparatus for smart sensing using a control panel of a home automation system, comprising:

a processor;

memory in electronic communication with the processor; and

instructions stored in the memory and executable by the processor to cause the apparatus to:

determine, by the processor of the control panel of the home automation system, a parameter of a resource associated with a home;

monitor the parameter of the resource based on sensor data captured by a plurality of sensors that are communicatively coupled to the control panel of the home automation system;

predict, by the processor of the control panel of the home automation system, a future change in condition associated with the parameter satisfying a threshold as detected by a sensors, the predicting based at least in part on a machine learning model, the machine learning model trained on previously captured sensor data associated with the monitored parameter;

in response to predicting the future change in condition satisfies the threshold, perform a function that includes generating a first message, for display on a device of the individual associated with the home automation system, comprising selectable options, wherein the selectable options include a first option to display a set of recommended actions to perform by the home automation system based at least in part on the future change in condition and a second option to view a time-lapse of the resource associated with the monitored parameter, wherein the time-lapse is generated based on a detected change in an attribute across video frames;

transmit the first message to the device of the individual and receiving selection of the first option;

in response to receiving selection of the first option, generate a second message with at least one recommended option that includes scheduling a service appointment;

receive selection of the at least one recommended option and scheduling, by the processor of the control panel of the home automation system, a service personnel to perform a service associated with the resource based on the predicted future change in condition;

detect, by the processor of the control panel of the home automation system, the service personnel at the home based on sensor data; and

actuate, by the processor of the control panel of the home automation system and in response to validating that the service personnel arrives at a time that is within a threshold time of a scheduled time for the service, an access point to the home to provide the service personnel access into the home for performing the service associated with the resource.

17. The apparatus of claim 16 , wherein monitoring the parameter of the resource comprises:

receiving real-time usage data of the resource from the sensor; and

tracking real-time usage data based at least in part on the received real-time usage data,

wherein performing the function is based at least in part on tracking the real-time usage data.

18. The apparatus of claim 16 , wherein the instructions are executable by the processor to cause the apparatus to:

identify a service or a product, or both;

retrieve, from a database, historical usage data associated with the service or the product, or both based at least in part on the identifying; and

compare the retrieved historical usage data with the real-time usage data to compute a usage model, wherein predicting the future change in condition associated with the parameter is based at least in part on the usage model.

19. A computer-program product for determining occupancy with user provided information, the computer-program product comprising a non-transitory computer-readable medium having instructions thereon, the instructions being executable by a processor to:

determine, by a processor of a control panel of the home automation system, a parameter of a resource associated with a home;

monitor the parameter of the resource based on sensor data captured by a plurality of sensors that are communicatively coupled to the control panel of the home automation system;

predict, by the processor of the control panel of the home automation system, a future change in condition associated with the parameter satisfying a threshold as detected by a sensors, the predicting based at least in part on a machine learning model, the machine learning model trained on previously captured sensor data associated with the monitored parameter excluding input from a set of occupants;

in response to predicting the future change in condition satisfies the threshold, perform a function that includes generating a first message, for display on a device of the individual associated with the home automation system, comprising selectable options, wherein the selectable options include a first option to display a set of recommended actions to perform by the home automation system based at least in part on the future change in condition and a second option to view a time-lapse of the resource associated with the monitored parameter, wherein the time-lapse is generated based on a detected change in an attribute across video frames;

transmit the first message to the device of the individual and receiving selection of the first option;

in response to receiving selection of the first option, generate a second message with at least one recommended option that includes scheduling a service appointment;

receive selection of the at least one recommended option and scheduling, by the processor of the control panel of the home automation system, a service personnel to perform a service associated with the resource based on the predicted future change in condition;

detect, by the processor of the control panel of the home automation system, the service personnel at the home based on sensor data; and

actuate, by the processor of the control panel of the home automation system and in response to validating that the service personnel arrives at a time that is within a threshold time of a scheduled time for the service, an access point to the home to provide the service personnel access into the home for performing the service associated with the resource.

20. The computer-program product of claim 19 , wherein monitoring the parameter of the resource comprises:

receiving real-time usage data of the resource from the sensor; and

tracking real-time usage data based at least in part on the received real-time usage data,

wherein performing the function is based at least in part on tracking the real-time usage data.

Assignments (10)

Cited By (6)

US 12,235,842 US 12,238,056 US 12,332,934 US 12,567,023 US 12,574,441 US 12,704,281