Neural Network Based Traffic Monitoring using UAVs
Arjun Pillai1, Kajal Chourasia2, Bhavya Agarwal3, Robin Singh Balyan4
1Arjun Pillai, Department of Mechanical Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Kajal Chourasia, Department of Information Technology, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Bhavya Agarwal, Department of Information Technology, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4Robin Singh Agarwal, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 15 July 2019 | Revised Manuscript received on 24 July 2019 | Manuscript Published on 01 August 2019 | PP: 45-50 | Volume-8 Issue-4S2, April 2019 | Retrieval Number: D10030484S219/19©BEIESP | DOI: 10.35940/ijeat.D1003.0484S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In large and growing metropolitan areas, the rise in traffic congestion is becoming an inescapable problem. It is estimated that the traffic congestion in metro cities costs the nation approximately 1.5 lakh crore rupees every year. With the increase in congestion, accident rate increases proportionally. The reckless driving and increased speed are the root cause of road accidents. We propose a speed detection algorithm to detect and monitor the speed of vehicles crossing a certain threshold speed limit. On national highways, the long queues at toll booths lead to loss of time and money. We propose image processing and convolutional neural network based algorithm to address the problem of traffic congestion, ease the flow of traffic, anomalies detection and ultimately reduce pollution and fuel consumption.
Keywords: Convolutional Neural Network, Image Processing, License Plate Number Recognition, Speed Detection, Traffic Monitoring.
Scope of the Article: Neural Information Processing