Context awareness is currently being investigated for applications in different application areas of mobile computing. The integration of Bluetooth and Wireless LAN technologies into a vast of mobile devices — ranging from smartphones and PDAs to portable computers – has made user context sensing based on those technologies a feasible and promising approach. In this paper, we study which of the Bluetooth and Wireless LAN technology features (like radio-signal strength, device address management, etc.) can be exploited to derive user context, and develop a procedure how low level sensor data can be brought to application level context information. We introduce a method to automatically classify heterogeneous sensor data features with supervised or un-supervised classification methods. By defining two operations, a distance metric and an adaptation operator, any feature can be used as input for the classifier and can thus contribute to context detection.
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