The Mobile Sensing Platform: An Embedded Activity Recognition System
IEEE Pervasive Computing（2008）
摘要
The Mobile Sensing Platform (MSP) is a small-form-factor wearable device designed for embedded activity recognition. The MSP aims broadly to support context-aware ubiquitous computing applications. It incorporates multimodal sensing, data processing and inference, storage, all-day battery life, and wireless connectivity into a single 4 oz (115 g) wearable unit. Several design iterations and real-world deployments over the last four years have identified a set of core hardware and software requirements for a mobile inference system. This article presents findings and lessons learned in the course of designing, improving and using this system. This article is part of a special issue on activity-based computing.
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关键词
design iteration,mobile sensing platform,data processing,small-form-factor wearable device,activity-based computing,all-day battery life,mobile inference system,activity recognition system,context-aware ubiquitous computing application,wearable unit,core hardware,mobile communication,user interfaces,user interface,embedded system,accelerometers,activity recognition,sensors,wearable computers,pervasive computing,real time,wearable computer,smart environment,smart environments,computer architecture,embedded systems,ubiquitous computing,machine learning
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