Abstract
Illegally parked cars are a prominent cause of road safety issues as well as metropolitan traffic jams. This paper presents an artificial intelligence-based parking violation detection and fine collection system that employs object detection using YOLO-based and OCR technology for automatic plate number recognition. The system scans real- time camera feeds employing an integrated database to detect illegal parking, acquire vehicle details, and levy penalties. In addition to this, people can take and upload photos of illegally parked vehicles via a citizen-supported reporting system, which police agencies verify prior to issuing penalties. To maintain equity, the framework imposes a limitation that a vehicle is penalized just once per day for the same spot. The extensive database facilitates law enforcement's ability to find repeat violators and implement harsher penalties by following previous offenses. By combining AI and community outreach, the strategy improves traffic flow, alleviates congestion, and promotes correct parking behavior. In the end, this ingenuous enforcement tactic promotes safer and more effective urban mobility.
Keywords
YOLO object detection, Optical character recognition (OCR), Traffic congestion reduction, Smart urban mobility, Illegal parking monitoring.
Citations
IRE Journals:
Praveen G, Rajageethan A, Dhanu Murugan K , Naren Karthikeyan S "AI-Driven No Parking Violation Detection and Fine Management System" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 1671-1676 https://doi.org/10.64388/IREV9I6-1713042
IEEE:
Praveen G, Rajageethan A, Dhanu Murugan K , Naren Karthikeyan S
"AI-Driven No Parking Violation Detection and Fine Management System" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1713042
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