Fast adaptation of activity sensing policies in mobile devices

• Main Authors: ALSHEIKH, Mohammad Abu, NIYATO, Dusit, LIN, Shaowei, TAN, Hwee-Pink, KIM, Dong In
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Activity tracking; fast adaptation; Internet of Things; Markov decision processes; wireless charging; Computer Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3887; https://ink.library.smu.edu.sg/context/sis_research/article/4889/viewcontent/161103202v1.pdf
• Institution: Singapore Management University

With the proliferation of sensors, such as accelerometers,in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics...