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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19455
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Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | REAL TIME TRAFFIC RULES VIOLATION DETECTOR USING MACHINE LEARNING |
| Authors Name: | Sanjay H , Bhargav J K , RoopaShree C S |
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| Author Reg. ID: |
IJRTI_189830
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| Published Paper Id: | IJRTI2405032 |
| Published In: | Volume 9 Issue 5, May-2024 |
| DOI: | |
| Abstract: | The integration of real-time traffic rules violation detection and automatic number plate recognition using machine learning technologies heralds the emergence of a transformative paradigm in traffic management, ushering in the era of Virtual Traffic Police. By leveraging advanced ML algorithms, this system obviates the necessity of human traffic enforcement, offering an automated solution for monitoring traffic violations and identifying vehicles in real-time. The system's capabilities encompass the detection of various violations, including motorcyclists without helmets, and instances of triple riding, thus promoting safer road environments. Moreover, the ANPR component plays a pivotal role in simplifying traffic congestion by swiftly identifying vehicles and enabling seamless monitoring of traffic flow. The proposed model employs a camera-based approach to capture video footage, which is then subjected to ANPR techniques for plate localization and character recognition. The overarching objective of this project is to mitigate road violations and enhance traffic safety. Additionally, the system facilitates the generation of challans for detected violations, ensuring accountability and compliance with traffic regulations. Furthermore, by harnessing ANPR technology, advanced systems capable of identifying and tracing stolen or uncertified vehicles are introduced, bolstering efforts to combat vehicle-related crimes. This paper outlines the methodology, implementation, and potential impact of the proposed system in revolutionizing traffic enforcement and fostering a culture of compliance on the roads. |
| Keywords: | CNN,YOLOV7, Machine Learning, Deep Learning, Tenser Flow, OpenCV. |
| Cite Article: | "REAL TIME TRAFFIC RULES VIOLATION DETECTOR USING MACHINE LEARNING ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.215 - 221, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405032.pdf |
| Downloads: | 000205150 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2405032
Registration ID:189830
Published In: Volume 9 Issue 5, May-2024
DOI (Digital Object Identifier):
Page No: 215 - 221 Country: Bengaluru, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2405032 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2405032 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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