A framework of energy efficient mobile sensing for automatic user state recognition. Wang, Y., Lin, J., Annavaram, M., Jacobson, Q., A., Hong, J., Krishnamachari, B., & Sadeh, N. In Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys), pages 179-192, 6, 2009. ACM.
A framework of energy efficient mobile sensing for automatic user state recognition [link]Website  abstract   bibtex   
Urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location-based services. However, continuously capturing this contextual information on mobile devices consumes huge amount of energy. In this paper, we present a novel design framework for an Energy Efficient Mobile Sensing System (EEMSS). EEMSS uses hierarchical sensor management strategy to recognize user states as well as to detect state transitions. By powering only a minimum set of sensors and using appropriate sensor duty cycles EEMSS significantly improves device battery life. We present the design, implementation, and evaluation of EEMSS that automatically recognizes a set of users' daily activities in real time using sensors on an off-the-shelf high-end smart phone. Evaluation of EEMSS with 10 users over one week shows that our approach increases the device battery life by more than 75% while maintaining both high accuracy and low latency in identifying transitions between end-user activities.
@inProceedings{
 title = {A framework of energy efficient mobile sensing for automatic user state recognition},
 type = {inProceedings},
 year = {2009},
 identifiers = {[object Object]},
 keywords = {activity-recognition,activity-sensing,energy,sensors,ubicomp},
 pages = {179-192},
 websites = {http://dx.doi.org/10.1145/1555816.1555835},
 month = {6},
 publisher = {ACM},
 id = {db14cb66-ac21-3873-b2af-a1978787c007},
 created = {2018-07-12T21:31:19.864Z},
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 abstract = {Urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location-based services. However, continuously capturing this contextual information on mobile devices consumes huge amount of energy. In this paper, we present a novel design framework for an Energy Efficient Mobile Sensing System (EEMSS). EEMSS uses hierarchical sensor management strategy to recognize user states as well as to detect state transitions. By powering only a minimum set of sensors and using appropriate sensor duty cycles EEMSS significantly improves device battery life. We present the design, implementation, and evaluation of EEMSS that automatically recognizes a set of users' daily activities in real time using sensors on an off-the-shelf high-end smart phone. Evaluation of EEMSS with 10 users over one week shows that our approach increases the device battery life by more than 75% while maintaining both high accuracy and low latency in identifying transitions between end-user activities.},
 bibtype = {inProceedings},
 author = {Wang, Yi and Lin, Jialiu and Annavaram, Murali and Jacobson, Quinn A and Hong, Jason and Krishnamachari, Bhaskar and Sadeh, Norman},
 booktitle = {Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys)}
}

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