ABSTRACT. Traffic control is an essential activity in metropolitan environments, with machine vision and mapping methods employed to track the handling and pace of cars in transit. Such approaches are more effective in terms of precision and processing speed compared with current and other techniques. To order to address the issue of traffic control, the implementation of an electronic system for monitoring vehicles speeds is necessary. The key aspects of transport analytics are traffic movement prevision, analysis of irregularities, car re-identification and car monitoring. One of the most significant study subjects in recent years has been forecasting traffic movement or calculating vehicle speed. In order to provide an effective path to prediction of time, we merged advanced Artificial intelligence “models with classic computerization approaches. during this paper we have a tendency to discuss many state-of - the-art strategies for speed estimation, automotive identification and object” monitoring and our Track 1 Task solution. According to the amount of frame(s), frame size and vehicle distance the size was measured using statistical formulations. This work was conducted on multiple vehicle styles and varying speed ranges.