Smart-home system facilitating insight into detected carbon monoxide levels

Patent metadata

Field	Value
Publication number	US-10546469-B2
Application number	US-201414508777-A
Country	US
Kind code	B2
Filing date	Oct 7, 2014
Priority date	Oct 7, 2013
Publication date	Jan 28, 2020
Grant date	Jan 28, 2020

Abstract

In an embodiment, a method determines one or more sources of carbon monoxide (CO) in a smart-home environment that includes a plurality of smart devices that have at least measurement and communication capabilities. The method includes measuring a level of CO in the smart-home environment to generate a CO measurement, and providing the CO measurement and one or more current characteristics of the smart-home environment, from one or more of the smart devices to an analyzing device. The method further includes evaluating, by the analyzing device and with the CO measurement and the current characteristics of the smart-home environment, a set of CO correlation scenarios that attribute generation of CO to a corresponding one of a set of specific sources, and selecting one or more of the specific sources as the most likely source of the CO, by aggregating results of the correlation scenarios.

First claim

What is claimed is:

1. A method for determining one or more sources of carbon monoxide (CO) in a smart-home environment, the smart-home environment including a plurality of smart-home devices that have at least measurement and communication capabilities, the method comprising:
linking each smart-home device of the plurality of smart-home devices with an online management account maintained by a cloud-computing system, wherein the cloud-computing system communicates with the plurality of smart-home devices via the Internet;
registering a mobile device with the online management account maintained by the cloud-computing system, wherein the mobile device communicates with the cloud-computing system via the Internet;
measuring a level of CO in the smart-home environment, by each smart-home device of the plurality of smart-home devices, to generate a plurality of CO measurements, wherein each smart-home device of the plurality of smart-home devices are located at different locations;
providing the plurality of CO measurements and one or more current characteristics of the smart-home environment from one or more of the smart-home devices to an analyzing device;
evaluating, by the analyzing device, based on the plurality of CO measurements and the one or more current characteristics of the smart-home environment, a set of CO correlation scenarios, wherein:
each CO correlation scenario of the set of CO correlation scenarios indicates a corresponding specific CO source based on: smart device location, CO change trend, and the one or more current characteristics of the smart-home environment;

selecting a specific CO source as the most likely source of the CO based on the evaluated set of CO correlation scenarios; and
outputting a notification via the Internet to the mobile device that has been registered with the online management account with which the plurality of smart-home devices are linked, wherein the notification is indicative of the specific CO source as the most likely source of the CO.

2. The method of claim 1 , wherein a result of evaluating each CO correlation scenario of the set of CO correlation scenarios is generation of a confidence metric that the plurality of CO measurements are due to a corresponding specific CO source, the method further comprises:
generating a sum of confidence metrics that correspond to a same specific CO source.

3. The method of claim 2 , wherein evaluating one or more of the CO correlation scenarios of the set of CO correlation scenarios comprises:
generating a positive or negative result state for each of the one or more of the CO correlation scenarios of the set of CO correlation scenarios, and
assigning a fixed value as the confidence metric responsive to generating the positive result state.

4. The method of claim 2 , wherein evaluating one or more of the CO correlation scenarios of the set of CO correlation scenarios comprises generating a variable result for each of the one or more of the CO correlation scenarios, and assigning a variable value that is responsive to a degree of fit between the plurality of CO measurements and the one or more current characteristics, as the confidence metric.

5. The method of claim 2 , wherein selecting one or more of the specific CO sources as the most likely source of the CO comprises comparing the sums of the confidence metrics for the corresponding CO sources and determining that one of the corresponding CO sources is more likely than all of the other sources.

6. The method of claim 2 , wherein selecting one or more of the CO specific sources as the most likely source of the CO comprises determining that two or more of the corresponding sources are possible CO sources, responsive to the sums of the confidence metrics for each of the two or more corresponding CO sources being within a confidence window of one another.

7. The method of claim 1 , wherein the analyzing device is a smart-home device of the plurality of smart-home devices that measures the CO, and others of the smart-home devices provide at least some of the current characteristics to the smart-home device that measures the CO.

8. The method of claim 1 , wherein the analyzing device is a computer that receives the plurality of CO measurements and the current characteristics.

9. The method of claim 1 , wherein:
one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a garage;
the one or more current characteristics include a time of day; and
the specific CO source is automobile exhaust in the garage.

10. The method of claim 9 , wherein the one or more current characteristics further include a day of the week.

11. The method of claim 9 , wherein the one or more current characteristics further include an indication that a door associated with the garage has opened or closed.

12. The method of claim 1 , wherein:
one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a kitchen;
the one or more current characteristics include detection of a temperature increase in the kitchen; and
the specific CO source is operation of a gas stove in the kitchen.

13. The method of claim 12 , wherein the one or more current characteristics further include detection of smoke in the kitchen.

14. The method of claim 12 , wherein the CO measurements taken by one or more smart-home devices of the plurality of smart-home devices in or adjacent to a kitchen rise rapidly, while CO measurements taken by other smart-home devices of the plurality of smart-home devices do not change significantly.

15. The method of claim 1 , wherein:
one of the CO correlation scenarios of the set of CO correlation scenarios include CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a location of a wood burning appliance;
the one or more current characteristics include:
detection of a temperature increase in the location of the one or more smart-home device of the plurality of smart-home devices, and
information that an HVAC system is not operating as a heat source; and

the specific CO source is wood burning in the wood burning appliance.

16. The method of claim 1 , wherein:
one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a location of a water heater;
the one or more characteristics include detection of a humidity increase in or adjacent to a bathroom; and
the specific CO source is a CO leak from the water heater.

17. The method of claim 1 , further comprising generating one of the CO correlation scenarios of the set of CO correlation scenarios by:
periodically generating CO measurements by a hazard detector of the smart-home devices;
storing the CO measurements;
periodically generating current characteristics of the smart-home environment that are not the CO measurements;
storing the current characteristics; and
generating the one of the CO correlation scenarios by evaluating a correlation possibility between the CO measurements and one or more of the current characteristics, by:
determining correlation of the CO measurements with the one or more of the current characteristics; and
discarding the correlation possibility responsive to no correlation being present between t

Assignees

• Google Llc

Inventors

• Peterson Kevin
• Sloo David
• Matsuoka Yoky
• Webb Nicholas Unger

Classifications

• F24F11/46

  Improving electric energy efficiency or saving · CPC title

• F24F11/30

  for purposes related to the operation of the system, e.g. for safety or monitoring · CPC title

• H04L12/2818

  from a device located outside both the home and the home network (access arrangements H04L12/2856; for remote control or remote monitoring of applications H04L67/025; arrangements for transmitting signals characterised by the use of a wireless eletrical link G08C17/00; telephonic communication systems adapted for combination with remote control systems H04M11/007) · CPC title

• G08B21/12

  responsive to undesired emission of substances, e.g. pollution alarms · CPC title

• G08B29/02

  Monitoring continuously signalling or alarm systems · CPC title