Automatic self-protection for a portable electronic device
Provided are techniques for automatically protecting portable and wearable electronic devices from potential hazards by predicting when such hazards may occur. Techniques may include monitoring a plurality of sensors on the mobile computing device; receiving, on the mobile computing device, context data from a plurality of context-service applications; selecting a set of device-protection policies based upon an availability of the plurality of sensors and the plurality of context-service applications, wherein the set of device-protection policies are configured to determine a level of risk to the mobile computing device based on sensor data received from the plurality of sensors and the context data; applying the sensor data and the context data to the set of device-protection policies to generate the level of risk; and triggering a self-protection action if the level of risk exceeds a pre-determined threshold level of risk.
1. A method for protecting a mobile device, comprising:
monitoring a plurality of sensors on the mobile computing device;
receiving, on the mobile computing device, context data from a plurality of context-service applications;
selecting a set of device-protection policies based upon an availability of the plurality of sensors and the plurality of context-service applications, wherein the set of device-protection policies are configured to determine a level of risk to the mobile computing device based on sensor data received from the plurality of sensors and the context data, wherein the context data is used as a factor in determining a potential hazard to the mobile computing device prior to an actual hazard corresponding to the potential hazard being detected by a sensor of the plurality of sensors;
applying the sensor data and the context data to the set of device-protection policies to generate the level of risk; and
triggering a self-protection action if the level of risk exceeds a pre-determined threshold level of risk.
2. The method of claim 1 , wherein the plurality of sensors are selected from a list, the list consisting of:
a plurality of motion sensors;
a plurality of environmental sensors; and
a plurality of position sensors.
3. The method of claim 1 , wherein at least one of the plurality of context-service applications is a cloud-based service.
4. The method of claim 1 , wherein at least one of plurality of context-service applications is an application executing on the mobile computing device.
5. The method of claim 1 , wherein the self-protection action comprises controlling the mobile computing device.
6. The method of claim 5 , wherein the controlling the mobile computing device comprises powering off the mobile computing device.
7. The method of claim 1 , wherein the self-protection action comprises controlling a device other than the mobile computing device.
8. The method of claim 1 , wherein the self-protection policies are generated by a method, the method comprising:
collecting historical data corresponding to a plurality of failures of a plurality of mobile computing devices; and
data mining the historical data to identify a particular source of failure of the plurality of failures.
9. The method of claim 1 , wherein the self-protection policies are based upon crowd-sourced scenarios of a plurality of failures on other mobile computing devices.
10. A mobile computing device, comprising:
a plurality of processors;
a non-transitory computer-readable recording medium coupled to the plurality of processors;
a plurality of sensors; and
logic, stored on the computer-readable recording medium and executed on the plurality of processors, to perform a method the method comprising:
monitoring the plurality of sensors;
receiving, on the mobile computing device, context data from a plurality of context-service applications;
selecting a set of device-protection policies based upon an availability of the plurality of sensors and the plurality of context-service applications, wherein the set of device-protection policies are configured to determine a level of risk to the mobile computing device based on sensor data received from the plurality of sensors and the context data, wherein the context data is used as a factor in determining a potential hazard to the mobile computing device prior to an actual hazard corresponding to the potential hazard being detected by a sensor of the plurality of sensors;
applying the sensor data and the context data to the set of device protection policies to generate the level of risk; and
triggering a self-protection action if the level of risk exceeds a pre-determined threshold level of risk.
11. The mobile computing device of claim 10 , wherein the plurality of sensors are selected from a list, the list consisting of:
a plurality of motion sensors;
plurality of environmental sensors; and
a plurality of position sensors.
12. The mobile computing device of claim 10 , wherein at least one of the plurality of context-service applications is a cloud-based service.
13. The mobile computing device of claim 10 , wherein at least one of plurality of context-service applications is an application executing on the mobile computing device.
14. The mobile computing device of claim 10 , wherein the self-protection policies are generated by a method, the method comprising:
collecting historical data corresponding to a plurality of failures of a plurality of mobile computing devices; and
data mining the historical data to identify a particular source of failure of the plurality of failures.
15. The mobile computing device of claim 10 , wherein the self-protection policies are based upon crowd-sourced scenarios of a plurality of failures on other mobile computing devices.
16. A computer programming product for protecting a mobile computing device comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by a plurality of processors to perform a method comprising, comprising:
monitoring a plurality of sensors the mobile computing device;
receiving, on the mobile computing device, context data from a plurality of context-service applications;
selecting a set of device-protection policies based upon an availability of the plurality of sensors and the plurality of context-service applications, wherein the set of device-protection policies are configured to determine a level of risk to the mobile computing device based on sensor data received from the plurality of sensors and the context data, wherein the context data is used as a factor in determining a potential hazard to the mobile computing device prior to an actual hazard corresponding to the potential hazard being detected by a sensor of the plurality of sensors;
applying the sensor data and the context data to the set of device-protection policies to generate the level of risk; and
triggering a self-protection action if the level of risk exceeds a pre-determined threshold level of risk.
17. The computer programming product of claim 16 , wherein the plurality of sensors are selected from a list, the list consisting of:
a plurality of motion sensors;
a plurality of environmental sensors; and
a plurality of position sensors.
18. The computer programming product of claim 16 , wherein the self-protection action comprises controlling the mobile computing device.
19. The computer programming product of claim 16 , wherein the self-protection policies are generated by a method, the method comprising:
collecting historical data corresponding to a plurality of failures of a plurality of mobile computing devices; and
data mining the historical data to identify a particular source of failure of the plurality of failures.
20. The computer programming product of claim 16 , wherein the self-protection policies are based upon crowd-sourced scenarios of a plurality of failures on other mobile computing devices.