Traffic Rule Violation Detection System using ML

September 2020
Vol-6, Issue-5
Paper ID: 12688
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Firebase GC CNN ML TCP/IP WWW BaaS YOLO.
Abstract
Real time identification systems are very important and needful for safety, security rule following and socialism and also for own safety concerns. Traffic rules are important for safety as traffic laws are to prevent drivers of vehicles from causing accidents or hitting pedestrians. They are also to help control the flow of traffic so that it is more efficient. Traffic Rule Violations are leading cause of accidents, according to WHO India is a leading country in casualties occurring on road. The current system uses human interaction for rule violation detection, as it is a manual process it has some limitations, on multiple occasions we find the system gets corrupt. An alternative solution would be AI-developed System. With our system, we can detect multiple rule violations, for example, Vehicle crossing signal during red light or driving without a helmet, etc. Basic idea is to detect these violations through preinstalled cameras. We can do it by ML based algorithm where we can detect the violators by Image- Processing, getting the number pate, categorizing violation accordingly and issuing fine. Which will help increase the efficiency of traffic rule enforcement

Author Information

# Name Institute / Affiliation
1 Shakib Jakir Deshmukh Jayawantrao Sawant College of Engineering
2 Hrishikesh Ashok Atole Jayawantrao Sawant College of Engineering
3 Amit Sugriv Rangwal Jayawantrao Sawant College of Engineering
4 Balaji Jeevan Kokil Jayawantrao Sawant College of Engineering
5 Shipra Saraswat Jayawantrao Sawant College of Engineering

How to Cite

Use the following formats to cite this article in your research.

APA Style
Deshmukh, Shakib Jakir, Atole, Hrishikesh Ashok, Rangwal, Amit Sugriv, Kokil, Balaji Jeevan, & Saraswat, Shipra (2020). Traffic Rule Violation Detection System using ML. International Journal of Advance Research and Innovative Ideas In Education, 6(5), 410-416.
MLA Style
Deshmukh, Shakib Jakir, et al. "Traffic Rule Violation Detection System using ML." International Journal of Advance Research and Innovative Ideas In Education, vol. 6, no. 5, 2020, pp. 410-416.
IEEE Style
Shakib Jakir Deshmukh, Hrishikesh Ashok Atole, Amit Sugriv Rangwal, Balaji Jeevan Kokil, and Shipra Saraswat, "Traffic Rule Violation Detection System using ML," International Journal of Advance Research and Innovative Ideas In Education, vol. 6, no. 5, pp. 410-416, 2020.
Vancouver Style
Deshmukh Shakib Jakir, Atole Hrishikesh Ashok, Rangwal Amit Sugriv, Kokil Balaji Jeevan, Saraswat Shipra. Traffic Rule Violation Detection System using ML. International Journal of Advance Research and Innovative Ideas In Education. 2020;6(5):410-416.
Harvard Style
Deshmukh, Shakib Jakir, Atole, Hrishikesh Ashok, Rangwal, Amit Sugriv, Kokil, Balaji Jeevan, & Saraswat, Shipra (2020) 'Traffic Rule Violation Detection System using ML', International Journal of Advance Research and Innovative Ideas In Education, 6(5), pp. 410-416.
Chicago Style
Deshmukh, Shakib Jakir, et al. "Traffic Rule Violation Detection System using ML." International Journal of Advance Research and Innovative Ideas In Education 6, no. 5 (2020): 410-416.
Turabian Style
Deshmukh, Shakib Jakir, et al. "Traffic Rule Violation Detection System using ML." International Journal of Advance Research and Innovative Ideas In Education 6, no. 5 (2020): 410-416.

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