IJEEDC Traffic Disciplinary Control Using IOT for Urban Areas and Expressways

Journal Paper

Paper Title :Traffic Disciplinary Control Using IOT for Urban Areas and Expressways

Author :Surat Pyari Atti, Shreya D Revankar, Sujitha S, Sanjana, Sakshi, Prathvi Gaonkar

Article Citation :Surat Pyari Atti ,Shreya D Revankar ,Sujitha S ,Sanjana ,Sakshi ,Prathvi Gaonkar , (2024 ) " Traffic Disciplinary Control Using IOT for Urban Areas and Expressways " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 30-34, Volume-12,Issue-6

Abstract : An automated Arduino Uno based traffic control system using sensors can be a helpful step in optimizing the traffic flow pattern in busy intersections, and solar based system is used to save electricity. This system describes a system where photoelectric sensors are integrated with the Arduino Uno to operate the lanes of an intersection based on the density of traffic. The distance between these sensors will depend on nature of traffic on a particular junction in addition, special sensors are places on roads and expressways that can detect unusual activities such as crowding or accidents and sends signal to respective authorities via an application using IoT. The authorities can immediately act regarding the problem and clear paths. Special sensors are installed to sense and send the signal in case of emergency or higher government vehicles so that they don’t face any issue while commuting. As a result, the improvement in traffic system can be incrementally enhanced, which can lead to eventually significant improvement in the overall traffic system. The existing Traffic control system is based on the “time” which is already assigned in the system. the existing traffic control systems fail to reduce traffic congestion problem. This project is designed to develop a system which perform execution based on density of vehicles and emergency instances. Keywords - Traffic density, Solar panels, Photoelectric sensors, IoT

Type : Research paper

Published : Volume-12,Issue-6


	\|		PDF	\|	Viewed - 22	\|	Published on 2024-09-20

Jan. 2025
Submitted Papers	:	80
Accepted Papers	:	10
Rejected Papers	:	70
Acc. Perc	:	12%
Issue Published	:	141
Paper Published	:	1771
No. of Authors	:	4924

Published : Volume-12,Issue-6

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