Physical Sciences and Mathematics Commons^™

Enabling Usage Pattern-Based Logical Status Inference For Mobile Phones, Jon C. Hammer

Graduate Theses and Dissertations

Logical statuses of mobile users, such as isBusy and isAlone, are the key enabler for a plethora of context-aware mobile applications. While on-board hardware sensors (such as motion, proximity, and location sensors) have been extensively studied for logical status inference, continuous usage typically requires formidable energy consumption, which degrades the user experience. In this thesis, we argue that smartphone usage statistics can be used for logical status inference with negligible energy cost. To validate this argument, we present a continuous inference engine that (1) intercepts multiple operating system events, in particular foreground app, notifications, screen states, and connected networks; (2) …