• BANDA RAVIKUMAR
• R. Naveen Reddy
• K. Dhanunjaya
• Dr. K Sreenivasulu

The increasing quantity of metropolitan cars is making traffic management, an ongoing concern. In addition to seriously disrupting our daily lives and elevating stress levels, traffic bottlenecks have an adverse effect on the environment by raising carbon emissions. Megacities are facing enormous obstacles and delays in their daily transportation-related activities as a result of population growth. To continuously evaluate traffic density and implement necessary measures. We need an intelligent traffic management system. The availability of separate lanes for different kinds of vehicles does not, however, shorten commute wait times at traffic signal locations. A technology that gathers live pictures from signals using intelligent machines is presented as an approach to the situation with regards to existing methodology. This method determines Volume of traffic by applying the YOLOv4 image processing methodology to earn efficiency. KEYWORDS: artificial intelligence, intelligent monitoring, signal switching algorithm, traffic jams, the traffic light system, and the traffic management.

Artificial intelligence, intelligent monitoring, signal switching algorithm, traffic jams, the traffic light system, and the traffic management.

"INTELLIGENT TRAFFIC LIGHT CONTROL: ENHANCING EFFICIENCY WITH YOLO V4, AI TECHNOLOGY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.e100-e107, April-2024, Available :http://www.jetir.org/papers/JETIR2404410.pdf

"INTELLIGENT TRAFFIC LIGHT CONTROL: ENHANCING EFFICIENCY WITH YOLO V4, AI TECHNOLOGY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppe100-e107, April-2024, Available at : http://www.jetir.org/papers/JETIR2404410.pdf