Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A survey of mobile phone sensing
IEEE Communications Magazine
Activity recognition using cell phone accelerometers
ACM SIGKDD Explorations Newsletter
Design considerations for the WISDM smart phone-based sensor mining architecture
Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data
Code in the air: simplifying sensing and coordination tasks on smartphones
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Ubiquitous mobile instrumentation
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
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Mobile devices such as smart phones, tablet computers, and music players are ubiquitous. These devices typically contain many sensors, such as vision sensors (cameras), audio sensors (microphones), acceleration sensors (accelerometers) and location sensors (e.g., GPS), and also have some capability to send and receive data wirelessly. Sensor arrays on these mobile devices make innovative applications possible, especially when data mining is applied to the sensor data. But a key design decision is how best to distribute the responsibilities between the client (e.g., smartphone) and any servers. In this paper we investigate alternative architectures, ranging from a "dumb" client, where virtually all processing takes place on the server, to a "smart" client, where no server is needed. We describe the advantages and disadvantages of these alternative architectures and describe under what circumstances each is most appropriate. We use our own WISDM (WIreless Sensor Data Mining) architecture to provide concrete examples of the various alternatives.