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research-article

Empowering mobile crowdsensing through social and ad hoc networking

Published: 01 July 2016 Publication History

Abstract

Mobile crowdsensing (MCS) enables collective data harvesting actions by coordinating citizens willing to contribute data collected via their sensor-rich smartphones that represent sources of valuable sensing information in urban environments nowadays. One of the biggest challenges in a real long-running MCS system lies in the capacity not only to attract new volunteers, but also, and most importantly, to leverage existing social ties between volunteers to keep them involved to build long-lasting MCS communities. In addition, the advent of high-performing devices and ad hoc communication technologies can help to further amplify the effect of sensing actions in proximity of the volunteer devices. This article originally describes how to exploit these socio-technical networking aspects to increase the performance of MCS campaigns in the ParticipAct living laboratory, an ongoing MCS real-world experiment that involved about 170 students of the University of Bologna for more than two years. The article also reports some significant experimental results to quantify the effectiveness of the proposed techniques.

Cited By

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  • (2023)Heterogeneous multi-project multi-task allocation in mobile crowdsensing using an ensemble fireworks algorithm▪Applied Soft Computing10.1016/j.asoc.2023.110571145:COnline publication date: 1-Sep-2023
  • (2021)Task Execution Quality Maximization for Mobile Crowdsourcing in Geo-Social NetworksProceedings of the ACM on Human-Computer Interaction10.1145/34760535:CSCW2(1-29)Online publication date: 18-Oct-2021
  • (2021)A Multi-Leader Multi-Follower Game-Based Analysis for Incentive Mechanisms in Socially-Aware Mobile CrowdsensingIEEE Transactions on Wireless Communications10.1109/TWC.2020.303382220:3(1457-1471)Online publication date: 1-Mar-2021
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Published In

cover image IEEE Communications Magazine
IEEE Communications Magazine  Volume 54, Issue 7
July 2016
212 pages

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IEEE Press

Publication History

Published: 01 July 2016

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Cited By

View all
  • (2023)Heterogeneous multi-project multi-task allocation in mobile crowdsensing using an ensemble fireworks algorithm▪Applied Soft Computing10.1016/j.asoc.2023.110571145:COnline publication date: 1-Sep-2023
  • (2021)Task Execution Quality Maximization for Mobile Crowdsourcing in Geo-Social NetworksProceedings of the ACM on Human-Computer Interaction10.1145/34760535:CSCW2(1-29)Online publication date: 18-Oct-2021
  • (2021)A Multi-Leader Multi-Follower Game-Based Analysis for Incentive Mechanisms in Socially-Aware Mobile CrowdsensingIEEE Transactions on Wireless Communications10.1109/TWC.2020.303382220:3(1457-1471)Online publication date: 1-Mar-2021
  • (2019)Quantifying location privacy in permissioned blockchain-based internet of things (IoT)Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3360774.3360800(116-125)Online publication date: 12-Nov-2019
  • (2019)A Classification Framework of Mobile Health CrowdSensing ResearchProceedings of the South African Institute of Computer Scientists and Information Technologists 201910.1145/3351108.3351113(1-12)Online publication date: 17-Sep-2019
  • (2019)Co-production of Public Service and Information TechnologyProceedings of the 20th Annual International Conference on Digital Government Research10.1145/3325112.3325232(123-132)Online publication date: 18-Jun-2019
  • (2018)A Systematic Review for Smart City Data AnalyticsACM Computing Surveys10.1145/323956651:5(1-41)Online publication date: 4-Dec-2018
  • (2018)Risk Prevention of Spreading Emerging Infectious Diseases Using a HybridCrowdsensing Paradigm, Optical Sensors, and SmartphoneJournal of Medical Systems10.1007/s10916-018-0937-242:5(1-14)Online publication date: 1-May-2018
  • (2017)Binarized cross-approximate entropy in crowdsensing environmentComputers in Biology and Medicine10.1016/j.compbiomed.2016.11.01980:C(137-147)Online publication date: 1-Jan-2017
  • (2016)Adopting incentive mechanisms for large-scale participation in mobile crowdsensingHuman-centric Computing and Information Sciences10.1186/s13673-016-0080-36:1(1-31)Online publication date: 1-Dec-2016

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