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EUROMICRO '05 Proceedings of the 31st EUROMICRO Conference on Software Engineering and Advanced Applications
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EUC '08 Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Neural Networks
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More and more mobile phones are equipped with multiple sensors today. This creates a new opportunity to analyze users' daily behaviors and evolve mobile phones into truly intelligent personal devices, which provide accurate context-adaptive and individualized services. This paper proposed a MAST (Movement, Action, and Situation over Time) model to explore along this direction and identified key technologies required. The sensing results gathered from some mobile phone sensors were presented to demonstrate the feasibility. To enable always sensing while reducing power consumption for mobile phones, an independent sensor subsystem and a phone-cloud collaboration model were proposed. This paper also listed typical usage models powered by mobile phone sensor based user behavior prediction.