Bayesian network-based high-level context recognition for mobile context sharing in cyber-physical system

With the recent proliferation of smart phones, they become useful tools to implement high-confidence cyber-physical systems. Among many applications, context sharing systems in mobile environment attract attention with the popularization of social media. Mobile context sharing systems can share more information than web-based social network services because they can use a variety of information from mobile sensors. To share high-level contexts such as activity, emotion, and user relationship, a user had to annotate them manually in previous works. This paper proposes a mobile context sharing system that can recognize high-level contexts automatically by using Bayesian networks based on mobile logs. We have developed a ContextViewer application which consists of a phonebook and a map browser to show the feasibility of the system. Experiments of evaluating Bayesian networks and performing the SUS test confirm that the proposed system is useful.