The Mobile Sensing Platform: An Embedded Activity Recognition System

Authors:
Tanzeem Choudhury;Gaetano Borriello;Sunny Consolvo;Dirk Haehnel;Beverly Harrison;Bruce Hemingway;Jeffrey Hightower;Predrag "Pedja" Klasnja;Karl Koscher;Anthony LaMarca;James A. Landay;Louis LeGrand;Jonathan Lester;Ali Rahimi;Adam Rea;Danny Wyatt
Affiliations:
Dartmouth College;University of Washington;Intel Research;Stanford University;Intel Research;University of Washington;Intel Research;University of Washington;University of Washington;Intel Research;University of Washington;Intel Research;University of Washington;Intel Research;Intel Research;University of Washington
Venue:
IEEE Pervasive Computing
Year:
2008

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Abstract

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.