Smart Traffic Management and Control System
A traffic signal control module is integrated with the system to adjust signal timings dynamically based on real-time congestion levels. The module receives input from the YOLO-AlexNet model and uses an ML-based decision algorithm to optimize green light durations. This significantly reduces waiting time at intersections and enhances overall traffic flow efficiency.
Emergency vehicles, such as ambulances and fire trucks, are detected separately using YOLO-based object tracking. Upon detection, the system adjusts traffic signals in favor of emergency vehicles, creating a clear passage and reducing response time.The architecture of the proposed YOLO-AlexNet-based traffic management system consists of multiple interconnected components that work together to enhance traffic detection, monitoring, and optimization.
Intelligent Traffic System Using Machine Learning
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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