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Smart city article details

Title	Smart Traffic Congestion Model In Iot-A Review
ID_Doc	51574
Authors	Ramesh K.; Lakshna A.; Renjith P.N.
Year	2020
Published	Proceedings of the 4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020
DOI	http://dx.doi.org/10.1109/ICECA49313.2020.9297631
Abstract	Rising incidents of traffic congestion among increasing usage of vehicles have become a high concern in an urban area. Internet of Things (IoT) is the technology to support the monitoring and controlling the road traffic using sensors and cloud-based prediction algorithms. Many researchers are working on this from a different point of view. The purpose of this study is to compare and analyze the methodologies proposed by different researchers and highlight the open challenges in smart traffic. To minimize the traffic congestion in a certain area by diverting or redirecting the upcoming vehicles into the shortest path or alternate path. To predict and prevent the traffic in smart cities, Sensor-based techniques are started using normal traffic cameras in which IoT plays an important role. Some other techniques using signals from vehicles through Wi-Fi, Bluetooth, Zigbee from the smart devices used in vehicles and data used to analyze the traffic pattern by vehicle count. In location-based input, the proximity of dense urban population has the highest amount of traffic flow was found. Traffic prediction and rerouting reduces the level of traffic flow and air pollution (gasoline emission) and provides the traffic free urban roadways. © 2020 IEEE.
Author Keywords	Congestion Reduction; IoT; Sensor; Traffic Congestion; Traffic Flow Prediction

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