Department of CSE (Data Science), ACE Engineering College, Hyderabad, Telangana, India.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(03), 2240-2247
Received on 12 February 2024; revised on 23 March 2024; accepted on 25 March 2024
The main reason for many road accidents in modern times is speeding and negligent driving. This project aims to identify vehicles that exceed the speed limit and employs a machine learning algorithm for this purpose. It eliminates the need for manual checks by the police to identify speeding vehicles. The project involves vehicle detection and tracking as key steps, enabling us to classify the type of vehicle, their respective speeds, and the count of vehicles passing through given region. Counting the number of vehicles helps manage traffic, allowing us to identify peak traffic times and take necessary precautions to avoid long traffic jams. Vehicle tracking is the process of detecting a moving vehicle using a camera. Capture vehicle in video sequence from surveillance camera is demanding application to improve tracking performance. This technology is increasing the number of applications such as traffic control, traffic monitoring, traffic flow etc. Video and image processing are vital for traffic surveillance, analyzing, and monitoring in urban areas. Recent speed estimation methods prioritize accuracy and cost-effective hardware implementation.
Vehicle Detection; Classify the type of vehicle; Count of Vehicle; Traffic Jams; Video and image processing.
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Parwateeswar Gollapalli, Neha Muthyala, Prashanth Godugu, Nikitha Didikadi and Pavan Kumar Ankem. Speed sense: Smart traffic analysis with deep learning and machine learning. World Journal of Advanced Research and Reviews, 2024, 21(3), 2240-2247. Article DOI: https://doi.org/10.30574/wjarr.2024.21.3.0896