Fog Computing for Detecting Vehicular Congestion, An Internet of Vehicles based Approach: A review

October 31, 2019 ยท The Cartographer ยท ๐Ÿ› IEEE Intelligent Transportation Systems Magazine

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: Fog Computing for Detecting Vehicular Congestion, An Internet of Vehicles based Approach: A review"

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Authors Arnav Thakur, Reza Malekian arXiv ID 1911.00039 Category cs.NI: Networking & Internet Cross-listed eess.SP Citations 60 Venue IEEE Intelligent Transportation Systems Magazine Last Checked 1 day ago
Abstract
Vehicular congestion is directly impacting the efficiency of the transport sector. A wireless sensor network for vehicular clients is used in Internet of Vehicles based solutions for traffic management applications. It was found that vehicular congestion detection by using Internet of Vehicles based connected vehicles technology are practically feasible for congestion handling. It was found that by using Fog Computing based principles in the vehicular wireless sensor network, communication in the system can be improved to support larger number of nodes without impacting performance. In this paper, connected vehicles technology based vehicular congestion identification techniques are studied. Computing paradigms that can be used for the vehicular network are studied to develop a practically feasible vehicular congestion detection system that performs accurately for a large coverage area and multiple scenarios. The designed system is expected to detect congestion to meet traffic management goals that are of primary importance in intelligent transportation systems.
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