Aggregating mobile device battery life data

• US 8,538,712 B2
• Filed: 09/30/2011
• Issued: 09/17/2013
• Est. Priority Date: 06/02/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Shirriff, Ken, Egnor, Dan, Parks, Jason
• Primary Examiner(s): Wachsman, Hal
• Application Number:
  US13/250,986
• Publication Number:
  US 20120022818A1
• Time in Patent Office: 718 Days
• Field of Search: 702/63, 702/57, 702/60, 702 64- 68, 702 70- 71, 702/81, 702/84, 702/127, 702179-183, 702187-189, 703/2, 703/4, 703/18, 703 20- 22, 320/134, 320/136, 340/636.1, 340/636.19, 455/67.11, 4553431-3436, 455/423, 700/9, 700 28- 32, 700108-109, 700/286, 700/291, 709202-203, 709/218, 709/224, 713/340
• US Class Current: 702/63
• CPC Class Codes: G01R 31/371 with remote indication, e.g. on external chargers
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health

Abstract

Battery life data may be collected from a number of mobile devices. The battery life data for each of the mobile devices may be correlated with one or more characteristics of each of the mobile devices. The battery life data for the mobile devices may be aggregated based on at least one of the one or more characteristics. In some examples, a report of the aggregated battery life data for the mobile devices including at least one common characteristic is generated.

Claims

1. A method comprising:

collecting, by a computing device and from a plurality of mobile devices, battery life data from each of the plurality of mobile devices and data including at least one of a device model and software build from each of the plurality of mobile devices, wherein the battery life data for each of the plurality of mobile devices is tracked by each respective mobile device;

correlating, by a computing device, the battery life data collected from each of the plurality of mobile devices with the at least one of the device model and the software build for the corresponding mobile device; and

aggregating, by the computing device, the battery life data collected from each of the plurality of mobile devices into different groups based on the at least one of the at least one of the device model and the software build.

2. The method of claim 1, wherein aggregating the battery life data comprises aggregating battery life data for all of the plurality of mobile devices comprising at least one of a common device model and a common software build.

3. The method of claim 2, further comprising generating a report of the aggregated battery life data collected from each of the plurality of mobile devices comprising the at least one of the common device model and the common software build.

4. The method of claim 3, wherein the report comprises a histogram that represents one or more proportions of the mobile devices comprising the at least one of the common device model and the common software build falling into one or more respective battery life ranges.

5. The method of claim 1, wherein the one or more characteristics further comprises at least one usage pattern.

6. The method of claim 5, wherein the at least one usage pattern comprises an amount of network data traffic for each of the mobile devices over a time period.

7. The method of claim 5, wherein aggregating the battery life data further comprises aggregating the battery life data for all of the plurality of mobile devices comprising a common usage pattern.

8. The method of claim 7, further comprising generating a report of the aggregated battery life data for the plurality of mobile devices comprising the common usage pattern.

9. The method of claim 8, wherein the report comprises a linear regression of percentage of battery life versus time for the plurality of mobile devices comprising the common usage pattern.

10. The method of claim 1, further comprising calculating an estimated battery life for each of the plurality of mobile devices based on the battery life data collected from each of the plurality of mobile devices.

11. The method of claim 5, wherein the at least one usage pattern comprises an amount of time a display of the mobile device is on over a period of time.

12. The method of claim 1 further comprising calculating an estimated battery life for each of the mobile devices based on the battery life data collected from each of the mobile devices.

13. The method of claim 12, wherein the estimated battery life is equal to 100multiplied by a ratio of a difference between a last time included in the battery life data and a first time included in the battery life data to a difference between a battery charge as a percentage of fully charged at the first time and a battery charge as a percentage of fully charged at the last time.

14. A system comprising:

a non-transitory computer-readable storage medium storing a database configured to store battery life data and at least one of a device model and a software build collected from each of a plurality of mobile devices via a communication network; and

one or more processors configured to;

correlate the battery life data collected from each of the plurality of mobile devices with the at least one of the device model and the software build for the corresponding mobile device; and

aggregate the battery life data collected from each of the mobile devices into groups based on at least one of the at least one of device model and software build.

15. The system of claim 14, wherein the one or more processors are configured to aggregate battery life data for all of the plurality of mobile devices comprising at least one of a common device model and a common software build.

16. The system of claim 15, wherein the one or more processors are configured to generate a report of the aggregated battery life data for the plurality of mobile devices comprising the at least one of the common device model and the common software build.

17. The system of claim 16, wherein the report comprises a histogram that represents one or more proportions of the plurality of mobile devices comprising the at least one of the common device model and the common software build falling into one or more respective battery life ranges.

18. The system of claim 14, wherein the one or more characteristics comprises at least one usage pattern.

19. The system of claim 18, wherein the at least one usage pattern comprises an amount of network data traffic for each of the plurality of mobile devices over a time period.

20. The system of claim 18, wherein the one or more processors are configured to further aggregate battery life data for all of the plurality of mobile devices comprising a common usage pattern.

21. The system of claim 20, wherein the one or more processors are configured to generate a report of the aggregated battery life data for the plurality of mobile devices comprising the common usage pattern.

22. The system of claim 21, wherein the report comprises a linear regression of percentage of battery life versus time for the plurality of mobile devices comprising the common usage pattern.

23. The system of claim 18, wherein the at least one usage pattern comprises a number of external network connection attempts over a time period.

24. The system of claim 14 wherein the one or more processors are configured to calculate an estimated battery life for each of the plurality of mobile devices based on the battery life data collected from each of the plurality of mobile devices.

25. The system of claim 24, wherein the estimated battery life is equal to 100 multiplied by a ratio of a difference between a last time included in the battery life data and a first time included in the battery life data to a difference between a battery charge as a percentage of fully charged at the first time and a battery charge as a percentage of fully charged at the last time.

26. A non-transitory computer readable storage medium comprising instructions for causing a programmable processor to:

collect battery life data and data including at least one of a device model and a software build from each of the plurality of mobile devices from each of a plurality of mobile devices, wherein the battery life data for each of the plurality of mobile devices is tracked by each respective mobile device;

correlate the battery life data collected from each of the mobile devices with the at least one of device model and software build of each of the plurality of mobile devices for the corresponding mobile device; and

aggregate the battery life data collected from each of the plurality of mobile devices into different groups based on the at least one of the device model and the software build.