Design considerations for the WISDM smart phone-based sensor mining architecture

Authors:
Jeffrey W. Lockhart;Gary M. Weiss;Jack C. Xue;Shaun T. Gallagher;Andrew B. Grosner;Tony T. Pulickal
Affiliations:
Fordham University, Bronx NY;Fordham University, Bronx NY;Fordham University, Bronx NY;Fordham University, Bronx NY;Fordham University, Bronx NY;Fordham University, Bronx NY
Venue:
Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data
Year:
2011

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Abstract

Smart phones comprise a large and rapidly growing market. These devices provide unprecedented opportunities for sensor mining since they include a large variety of sensors, including an: acceleration sensor (accelerometer), location sensor (GPS), direction sensor (compass), audio sensor (microphone), image sensor (camera), proximity sensor, light sensor, and temperature sensor. Combined with the ubiquity and portability of these devices, these sensors provide us with an unprecedented view into people's lives---and an excellent opportunity for data mining. But there are obstacles to sensor mining applications, due to the severe resource limitations (e.g., power, memory, bandwidth) faced by mobile devices. In this paper we discuss these limitations, their impact, and propose a solution based on our WISDM (WIireless Sensor Data Mining) smart phone-based sensor mining architecture.