Connecting personal-scale sensing and networked community behavior to infer human activities

UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Volumn , Issue , 2014, Pages 595-606

  Lane, Nicholas D ^a   Pengyu, Li ^b   Zhou, Lin ^c   Zhao, Feng ^a  

^a MICROSOFT RESEARCH   (United States)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Activity recognition; Community learning; Mobile sensing

Indexed keywords

ECONOMIC AND SOCIAL EFFECTS; PATTERN RECOGNITION; POPULATION STATISTICS; UBIQUITOUS COMPUTING;

ACTIVITY RECOGNITION; BEHAVIORAL PATTERNS; COMMUNITY LEARNING; ENVIRONMENTAL FACTORS; INCREASING CAPACITIES; MOBILE SENSING; NETWORKED COMMUNITIES; TRAFFIC CONDITIONS;

BEHAVIORAL RESEARCH;

EID: 84908568773     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2632048.2636094     Document Type: Conference Paper

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