An Advanced RLVD System Incorporating E-Challan Enforcement

Red lights are installed at surveillance spots or multiple entry-exit roads, but enforcement is still a challenge due to the lack of technology. Manual enforcement in India is a challenge for police, as tracking vehicle numbers is not always possible or officers may miss capturing the evidence at the right time without an overview camera.

Intozi’s RLVD-Red Light Violation Detection System is an automated system designed for places with multiple entry-exit or surveillance spots. This system tracks multiple vehicles through a single centralized system, which makes traffic enforcement Smart and traffic management systems Intelligent using artificial intelligence (AI) and computer vision (CV).

Automated RLVD system – How it works?

Intozi’s advanced computer vision-enabled technology detects vehicles jumping the red light and violating zebra crossings using a video stream of cameras installed at traffic junctions in real-time. This system helps enforcement agencies track down offenders by automatically extracting the vehicle number and issuing E-challans, which reduces accidents and fatalities at traffic intersections.

Additionally, Intozi’s RLVD system is able to present heat maps of traffic flow, and its built-in vehicle classification adds another feature of class-based vehicle counts passing through the junction, which can help with further transport planning. The intelligent AI model can capture two vehicles without helmets and drivers without seat belts, and generate an E-challan of the captured vehicle automatically with evidence records.

Benefits of an Automated RLVD System

Automated traffic enforcement systems like Intozi’s RLVD-Red Light Violation Detection System can significantly improve road safety by reducing the number of accidents caused by reckless driving. By automating the enforcement process, the system eliminates the need for manual intervention, which can often be unreliable and subject to human error. This not only makes the enforcement process more efficient but also more accurate, leading to fewer false positives and ensuring that only genuine offenders are penalized.


In conclusion, automated RLVD systems like Intozi’s are the future of traffic enforcement. By incorporating advanced computer vision and AI technology, these systems can improve road safety, reduce accidents and fatalities, and make our roads a safer place to drive. The combination of real-time tracking, centralized data storage, and AI-powered analysis makes the RLVD system a reliable tool for traffic management and enforcement.