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Sensors 2015, 15(9), 22060-22088; doi:10.3390/s150922060

Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, ul. Baltycka 5, Gliwice44-100, Poland
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 26 May 2015 / Revised: 20 August 2015 / Accepted: 23 August 2015 / Published: 2 September 2015
(This article belongs to the Section Physical Sensors)
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Abstract

The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. View Full-Text
Keywords: crowdsensing; energy efficiency; mobility models; network modeling; mobility measurements crowdsensing; energy efficiency; mobility models; network modeling; mobility measurements
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Foremski, P.; Gorawski, M.; Grochla, K.; Polys, K. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks. Sensors 2015, 15, 22060-22088.

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