Intersections account for most road accidents and delay in a road network. The intersection's efficiency and safety concerns can be addressed by collecting vehicle platoon size, queue length, and delay data and implementing a red light violation detection technique (RLVDS) to reduce accidents. It is challenging to collect this traffic information in heterogeneous and less lane disciplined traffic, a scenario often observed in developing countries such as India. Traditional sensors such as inductive loop, infrared, radar, or magnetic sensors and image processing solutions do not work well under these conditions. Hence the current work presents a set of robust techniques developed for heterogeneous traffic. First, the platoons were detected using foreground extraction, connected component analysis, and a density-based clustering algorithm. Then, the queue length was extracted using a progressive block processing technique. Separately the RLVD was performed using corner point tracking and user-defined detection zones. © 2023, Transportation Research Group of India.