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Abstract

Understanding indoor mobility patterns of people is important in applications such as targeted advertisement, microclimate control, and delivery of anticipatory notifications. In this article, we devise GreenLocs, a nonparametric, profiling-free, yet lightweight and energy-efficient inference framework, to identify recurring and new places that mobile users visit indoor. Combining WiFi scans and accelerometer readings, GreenLocs can accurately …

Authors

Nguyen NT; Zheng R; Liu J; Han Z

Journal

ACM Transactions on Sensor Networks, Vol. 11, No. 3, pp. 1–21

Publisher

Association for Computing Machinery (ACM)

Publication Date

May 28, 2015

DOI

10.1145/2700271

ISSN

1550-4859

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