Mobile Users' Context Awareness Model based on a Novelty Contextual-Soundscape Information

With the wide spread of smartphones, providing contextualized information for mobile environment has been in demand, and many researchers have explored the topic of context awareness based on sensors in smartphones. The state-of-the-art method in this field only uses for input simple data such as location, current time, user activity and provides simple output. Various events that could take place in a given place and time are not distinguished for user. Implementation of such a feature requires additional contextual data. In this paper, we define associations of user's contextual data with sound from smartphone microphone and propose a method that discerns user's contextual information through background sound. Using the Bayesian Network, we combine our defined associations with locational and temporal data used in existing methods to discern user's context. The proposed context-discerning model and existing model are compared for validation.