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A Low-Cost Vehicular Traffic Monitoring System Using Fog Computing

Department of Informatics, Ionian University, 49100 Corfu, Greece
Department of Audio and Visual Arts, Ionian University, 49100 Corfu, Greece
Department of Informatics and Telecommunications, University of Ioannina, 47100 Arta, Greece
Author to whom correspondence should be addressed.
The 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA 20 September 2019, University of Piraeus, Piraeus-Greece).
Smart Cities 2020, 3(1), 138-156;
Received: 22 January 2020 / Revised: 1 March 2020 / Accepted: 13 March 2020 / Published: 19 March 2020
With the rapid increase of vehicles in use worldwide, the need for efficient traffic monitoring systems has arisen. This work proposes a low-cost vehicular traffic monitoring system using IoT devices and fog computing. The system is based on a three-tiered architecture which is composed of (i) the mobile tracking system that records the positions of the vehicles using GPS technologies; (ii) the information gathering system which gathers all the data collected by the mobile tracking system; and (iii) the fog devices that process the data collected and extract the information needed. The system is tested in the town of Corfu during a period of increased tourism when the traffic is considered to be relatively dense. The mobile tracking system devices are placed on taxis and with the help of professional taxi drivers the accuracy of the data collected is evaluated. The system is able to record the movement of the vehicles accurately using its own independent data. The results can be remotely accessed by utilizing fog and cloud computing infrastructure established to process the data and upload it on a server. The system is used to give a better understanding of the speed variance in the center of the town during different dates and hours. In conclusion the system presented in this study can be utilized to monitor the traffic and provide vital information about its behavior in relation to time. View Full-Text
Keywords: networks; fog computing; internet of things; smart cities; road traffic monitoring networks; fog computing; internet of things; smart cities; road traffic monitoring
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Vergis, S.; Komianos, V.; Tsoumanis, G.; Tsipis, A.; Oikonomou, K. A Low-Cost Vehicular Traffic Monitoring System Using Fog Computing. Smart Cities 2020, 3, 138-156.

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