International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 05 | May 2024
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p-ISSN: 2395-0072
Development Of Automation Fine Imposition System For Traffic Violation Omkar kangralkar1, Prajwal Hiremath2, Armaan Nalband3, Uddesh Poojary4 Srinath .U. Ghodke5, Dr. Rajendra M Galagali6 1234Students, Department of Mechanical Engineering S.G. Balekundri Institute of Technology
Engineering Belgaum, Karnataka, India 5Professor and Project Guide, Department of Mechanical Engineering S.G. Balekundri Institute of Technology
Engineering Belgaum, Karnataka, India 6Professor and HOD, Department of Mechanical Engineering S.G. Balekundri Institute of Technology
Engineering Belgaum, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------The project consists of two main scenarios: No Parking Abstract - This project presents an Automatic Fine
Violation and Over Speed Violation. In the case of parking violations, ultrasonic sensors are utilized to detect vehicles in restricted areas, while over-speeding violations are identified through the application of IR sensors to measure vehicle speed. A prototype has been developed to enforce a conservative speed limit of 10 km/hr.
Imposition System for Traffic Violations, specifically targeting parking and speeding offenses. By harnessing the power of machine learning and IoT technologies, the system utilizes ESP32CAM modules to capture images of violations, which are thereafter kept safety in Firebase through a Python server. Machine learning techniques are applied to accurately detect vehicle license plates, facilitating precise identification for fine imposition. The system encompasses two main scenarios: No Parking Violation and Over Speed Violation, both of which leverage ESP32CAM modules. Parking violations are detected using ultrasonic sensors, while over-speeding violations are identified through the incorporation of two IR sensors. A prototype implementation enforces a speed limit of 10 km/hr. This cutting-edge solution is intended to improve traffic management efficiency and raise public awareness by providing easily accessible violation data.
Figure 1: ESP32CAM Module The ESP32CAM module is an essential part of the Automatic Fine Imposition System, allowing for the capture of violation evidence using its integrated camera and enabling seamless communication with the system's backend infrastructure. With Wi-Fi connectivity and powerful computational capabilities, the ESP32CAM module plays a crucial part in the automated detection and enforcement of traffic violations.
Key Words: Automation Traffic, Violations, ESP32CAM, Machine Learning, Detection, Fines
1.INTRODUCTION Traffic violations, especially parking and speeding offenses, present major obstacles to urban traffic management systems. in order to overcome these obstacles, this project introduces an Automatic Fine Imposition System that utilizes cutting-edge technologies to enhance the enforcement process. Through the integration of IoT devices like ESP32CAM modules as well as machine learning algorithms, the system seeks to automate the identification and imposition of fines for parking and speeding violations.
The implementation of an automated system for detecting and enforcing fines for traffic violations is intended to improve the effectiveness of urban traffic management, additionally to enhance public safety and awareness. This report provides an summary of the project's objectives, methodology, and anticipated results, highlighting its capacity to tackle current issues in urban traffic management.
The ESP32CAM modules play a vital part in capturing evidence of violations, allowing for real-time monitoring and data collection. These components are combined with a Python server to securely store violation images in Firebase, providing easy access to violation records. Sophisticated machine learning techniques are used to accurately identify vehicle license plates from the captured images, ensuring precise identification of offending vehicles.
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2.LITERATURE SURVEY Current developments in Automatic Fine Imposition Systems (AFIS) have transformed traffic management by providing effective solutions for detecting and penalizing traffic violations. Smith et al. (2019) introduced a machine learning-based system algorithms to accurately identify
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