Abstract
Continuously identifying a user’s location context provides new opportunities to understand daily life and human behavior. Indoor location systems have been mainly based on WiFi infrastructures which consume a great deal of energy mostly due to keeping the user’s WiFi device connected to the infrastructure and network communication, limiting the overall time when a user can be tracked. Particularly such tracking systems on battery-limited mobile devices must be energy-efficient to limit the impact on the experience of using a phone. Recently, there have been a lot of studies of energy-efficient positioning systems, but these have focused on outdoor positioning technologies. In this paper, we propose a novel indoor tracking framework that intelligently determines the location sampling rate and the frequency of network communication, to optimize the accuracy of the location data while being energy-efficient at the same time. This framework leverages an accelerometer, widely available on everyday smartphones, to reduce the duty cycle and the network communication frequency when a tracked user is moving slowly or not at all. Our framework can work for 14 h without charging, supporting applications that require this location information without affecting user experience.Version
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Yao, D. Z., Yu, C., Dey, A. K., Koehler, C., Min, G. Y., Yang, L. T. and Jin, H. (2014) Energy efficient indoor tracking on smartphones. Future Generation Computer Systems-the International Journal of Grid Computing and Escience, 39, 44-54.Link to Version of Record
https://doi.org/10.1016/j.future.2013.12.032Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1016/j.future.2013.12.032