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

Sensors
Paweł ForemskiKonrad Polys

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 gat...Continue Reading

References

Jun 12, 2014·Sensors·Muhammad ShoaibPaul J M Havinga
Mar 6, 2015·Sensors·Luis Miguel Soria MorilloMiguel Angel Alvarez de la Concepcion

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Citations

May 31, 2016·Sensors·Sergi Delgado-SeguraJordi Herrera-Joancomartí

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Methods Mentioned

BETA
chip

Software Mentioned

Google Provider
Google Play Services
Foursquare
OpenSignal
Photoshop
MOSDEN
Google Maps JavaScript API
iOS
LifeMap
OpenStreeMap

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