CHARGE MANAGEMENT

• US 20180198307A1
• Filed: 01/07/2017
• Published: 07/12/2018
• Est. Priority Date: 01/07/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Abou Mahmoud, Alaa, Bastide, Paul R., Lu, Fang
• Granted Patent: US 10,346,812 B2
• Time in Patent Office: Days
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance

Abstract

Disclosed aspects relate to charge management of a device. A first location-modification event of the device may be detected by a charge management engine. The first location-modification event of the device may indicate a first movement event of the device from an original location to a target location. A device charge pattern may be determined based on a set of profile data for a user. The device charge pattern may include a set of criteria that indicates to charge the device. Achievement of the set of criteria may be identified by the charge management engine based on the device charge pattern. Achievement of the set of criteria may relate to the first location-modification event. An indication to charge the device may be provided by the charge management engine. A charge may be received by the device.

Claims

1. A computer-implemented method for charge management of a device, the method comprising:

detecting, by a charge management engine, a first location-modification event of the device which indicates a first movement event of the device from an original location to a target location;

determining, based on a set of profile data for a user, a device charge pattern which includes a set of criteria that indicates to charge the device;

identifying, by the charge management engine based on the device charge pattern, achievement of the set of criteria which relates to the first location-modification event;

providing, by the charge management engine, an indication to charge the device; and

receiving, by the device, a charge.

2. The method of claim 1, further comprising:

ascertaining, by the charge management engine, that the device charge pattern indicates a temporal period for which the device is expected to remain in a current location.

3. The method of claim 2, further comprising:

comparing, with a threshold temporal period, the temporal period for which the device is expected to remain in the current location; and

computing that the temporal period exceeds the threshold temporal period.

4. The method of claim 2, further comprising:

detecting, corresponding to detecting the first location-modification event of the device which indicates the first movement event of the device from the original location to the target location, that the device has moved from the original location to the target location, wherein the target location includes the current location.

5. The method of claim 2, further comprising:

detecting, corresponding to detecting the first location-modification event of the device which indicates the first movement event of the device from the original location to the target location, that the device is expected to move from the original location to the target location, wherein the original location includes the current location.

6. The method of claim 1, wherein the device includes a wearable computing device that includes both a location sensor and a biometric sensor.

7. The method of claim 1, further comprising:

collecting, by the charge management engine, the set of profile data for the user, wherein the set of profile data for the user is selected from the group consisting of;

a set of temporal data,

a set of user biometric data,

a set of user age data,

a set of user height data,

a set of user weight data,

a set of user heart rate data,

a set of user blood pressure data,

a set of user physical activity data,

a set of user sleep data,

a set of user calendar data, and

a set of user-provided input data.

8. The method of claim 1, further comprising:

analyzing, using a machine-learning technique, the set of profile data for the user to determine the device charge pattern.

9. The method of claim 1, further comprising:

configuring the indication to charge the device to correspond to an anticipated event.

10. The method of claim 9, further comprising:

affixing the indication to charge the device in association with an electronic calendar event.

11. The method of claim 1, wherein the set of profile data for the user is selected from the group consisting of:

a set of derivative data of a group of like users which is similar to the user, and

a set of individualized data of the user based an a history of the user.

12. The method of claim 1, further comprising:

sensing, by the charge management engine, a set of captured wellness data on the device; and

transmitting, by the charge management engine to a remote server, the set of captured wellness data when the charge is received by the device.

13. The method of claim 1, further comprising:

initiating, in response to identifying achievement of the set of criteria, a power efficiency mode for the device.

14. The method of claim 1, further comprising:

connecting, by the charge management engine in an automated fashion, the device to a wireless charging source.

15. The method of claim 1, wherein the detecting, the determining, the identifying, the providing, and the receiving each occur in a dynamic fashion to streamline charge management of the device.

16. The method of claim 1, wherein the detecting, the determining, the identifying, the providing, and the receiving each occur in an automated fashion without user intervention.

17. The method of claim 3, wherein the device includes a wearable computing device that includes both a location sensor and a biometric sensor, wherein each of the operational steps occurs in both a dynamic fashion to streamline charge management of the device and an automated fashion without user intervention, further comprising:

collecting, by the charge management engine, the set of profile data for the user, wherein the set of profile data for the user includes each of;

a set of temporal data, a set of user biometric data, a set of user age data, a set of user height data, a set of user weight data, a set of user heart rate data, a set of user blood pressure data, a set of user physical activity data, a set of user sleep data, and a set of user calendar data;

analyzing, using a machine-learning technique, the set of profile data for the user to determine the device charge pattern;

initiating, in response to identifying achievement of the set of criteria, a power efficiency mode for the device;

configuring the indication to charge the device to correspond to an anticipated event;

affixing the indication to charge the device in association with an electronic calendar event on the wearable computing device;

connecting, by the charge management engine, the device to a wireless charging source;

sensing, by the charge management engine, a set of captured wellness data on the device; and

transmitting, by the charge management engine to a remote server, the set of captured wellness data when the charge is received by the device.

18. A system for charge management of a device, the system comprising:

a memory having a set of computer readable computer instructions, and

a processor for executing the set of computer readable instructions, the set of computer readable instructions including;

detecting, by a charge management engine, a first location-modification event of the device which indicates a first movement event of the device from an original location to a target location;

determining, based on a set of profile data for a user, a device charge pattern which includes a set of criteria that indicates to charge the device;

identifying, by the charge management engine based on the device charge pattern, achievement of the set of criteria which relates to the first location-modification event;

providing, by the charge management engine, an indication to charge the device; and

receiving, by the device, a charge.

19. A computer program product for charge management of a device, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

detecting, by a charge management engine, a first location-modification event of the device which indicates a first movement event of the device from an original location to a target location;

determining, based on a set of profile data for a user, a device charge pattern which includes a set of criteria that indicates to charge the device;

identifying, by the charge management engine based on the device charge pattern, achievement of the set of criteria which relates to the first location-modification event;

providing, by the charge management engine, an indication to charge the device; and

receiving, by the device, a charge.

20. The computer program product of claim 19, wherein at least one of:

the program instructions are stored in the computer readable storage medium in a data processing system, and wherein the program instructions were downloaded over a network from a remote data processing system;

or

the program instructions are stored in the computer readable storage medium in a server data processing system, and wherein the program instructions are downloaded over a network to the remote data processing system for use in a second computer readable storage medium with the remote data processing system.