Smart devices continue to proliferate and can provide end users with access to a variety of applications that perform a nearly limitless set of functions to assist end users. Each application may access, and leverage, data obtained from a number of sensors incorporated into or accessible to the smart device. Although some applications operate in isolation from one another and are programed to access only certain specified sensors, the experience of an end user could be improved by a machine-learning model that assists separate applications and separate sensors in performing functions together more harmoniously. When an end user initiates a particular application, a machine-learning model may suggest or automatically enable additional sensors that may increase the application’s functionality and improve the end-user experience. Likewise, the machine-learning model can suggest or automatically enable a particular application based on the initiation of a particular sensor. The machine-learning-based approach expands the user experience by coordinating and interconnecting the operations of both applications and sensors available on or accessible to computing devices.
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Carbune, Victor and Damian, Alexandru, "Contextual Enabling or Disabling of Computing-Device Applications and Sensors", Technical Disclosure Commons, (April 09, 2019)