A prediction and auto-execution system of smartphone application services based on user context-awareness

Smartphones have emerged as suitable environments for user context-awareness and intelligent service provision due to the high penetration rate, the high usability, various embedded sensors, and so on. In particular, its most unique characteristic is the usage of various applications. However, the most of existing studies through the three steps process (log collection, context inference, and service provision) did not consider smartphone applications (Apps) as the target service. Smartphone users still have to use Apps with manual controls by own decision. Therefore, in this paper, we propose a system to predict smartphone applications based on inferring user context. We define a mobile context model with a new level of context (Situation) and its inference method to perceive a user’s intention or purpose related to the App usage. Based on the Situation context, the system predicts Apps which can be useful and helpful for a user and automatically executes it on his/her smartphone. With the proposed system, it will be possible to autonomously provide and manage smartphone application services without users’ perception or intervention.