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Issue No. 02 - April-June (2008 vol. 7)
ISSN: 1536-1268
pp: 32-41
Tanzeem Choudhury , Dartmouth College
Gaetano Borriello , University of Washington
Sunny Consolvo , Intel Research
Dirk Haehnel , Stanford University
Beverly Harrison , Intel Research
Bruce Hemingway , University of Washington
Jeffrey Hightower , Intel Research
Predrag "Pedja" Klasnja , University of Washington
Karl Koscher , University of Washington
Anthony LaMarca , Intel Research
James A. Landay , University of Washington
Louis LeGrand , Intel Research
Jonathan Lester , University of Washington
Ali Rahimi , Intel Research
Adam Rea , Intel Research
Danny Wyatt , University of Washington
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.
activity recognition, embedded systems, machine learning, wearable computers

J. A. Landay et al., "The Mobile Sensing Platform: An Embedded Activity Recognition System," in IEEE Pervasive Computing, vol. 7, no. , pp. 32-41, 2008.
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