Big data management in participatory sensing: Issues, trends and future directions

Karim, Ahmad and Siddiqa, Aisha and Safdar, Zanab and Razzaq, Maham and Gillani, Syeda Anum and Tahir, Huma and Kiran, Sana and Ahmed, Ejaz and Imran, Muhammad (2020) Big data management in participatory sensing: Issues, trends and future directions. Future generation computer systems-the international journal of Escience, 107. pp. 942-955. ISSN 0167739X,

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Abstract

Participatory sensing has become an emerging technology of this era owing to its low cost in big sensor data collection. Prior to participatory sensing, large-scale deployment complexities were found in wireless sensor networks when collecting data from widespread resources. Participatory sensing systems employ handheld devices as sensors to collect data from communities and transmit to the cloud, where data are further analyzed by expert systems. The processes involved in participatory sensing, such as data collection, transmission, analysis, and visualization, exhibit certain management issues. This study aims to identify big data management issues that must be addressed at the cloud side during data processing and storing and at the participant side during data collection and visualization. It then proposes a framework for big data management in participatory sensing to resolve the contemporary big data management issues on the basis of suggested principles. Moreover, this work presents case studies to elaborate the existence of the highlighted issues. Finally, the limitations, recommendations, and future research directions for academia and industry in the domain of participatory sensing are discussed. (C) 2017 Published by Elsevier B.V.

Item Type: Article
Funders: Deanship of Scientific Research, King Saud University [Grant No: 1435-051]
Uncontrolled Keywords: Participatory sensing; Big data; Big data management; Big data analytics; Mobile cloud computing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 14 Aug 2024 08:24
Last Modified: 14 Aug 2024 08:24
URI: http://eprints.um.edu.my/id/eprint/36653

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