The 4W project system allows providing users with location and time contextualized cues that are generated automatically starting from user expressed needs. The system comprises a server side engine capable of reasoning to find out which location categories have to be searched for and a mobile device to track user location and provide intelligent cues to the user. One of the main weaknesses of the system is the high energy toll that continuously identifying the user location with high precision has on the mobile device battery. In this paper, we describe a novel ad-hoc algorithm that leverages a hierarchical approach to adaptively decide which is the current sweet-spot sufficient for providing the needed precision in location as well as the lowest energy impact. Our experiments show a significant reduction in the energy consumption.

Migliardi, M., Merlo, A., Tettamanti, M. (2015). Reducing Energy Consumption in Prospective Memory Support System through Hierarchical Positioning Algorithm. In Proceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 (pp.575-580). IEEE [10.1109/incos.2014.47].

Reducing Energy Consumption in Prospective Memory Support System through Hierarchical Positioning Algorithm

Tettamanti, M
2015

Abstract

The 4W project system allows providing users with location and time contextualized cues that are generated automatically starting from user expressed needs. The system comprises a server side engine capable of reasoning to find out which location categories have to be searched for and a mobile device to track user location and provide intelligent cues to the user. One of the main weaknesses of the system is the high energy toll that continuously identifying the user location with high precision has on the mobile device battery. In this paper, we describe a novel ad-hoc algorithm that leverages a hierarchical approach to adaptively decide which is the current sweet-spot sufficient for providing the needed precision in location as well as the lowest energy impact. Our experiments show a significant reduction in the energy consumption.
paper
Active Aging; Energy Awareness; Mobile Computing; Prospective Memory; Smartphones;
English
6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 - 10 September 2014 through 12 September 2014
2014
Proceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
9781479963867
2015
575
580
7057152
none
Migliardi, M., Merlo, A., Tettamanti, M. (2015). Reducing Energy Consumption in Prospective Memory Support System through Hierarchical Positioning Algorithm. In Proceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 (pp.575-580). IEEE [10.1109/incos.2014.47].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/467601
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