Intelligent Traffic Control System

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dc.contributor.author 03-134212-001, ABDUL MATEEN
dc.date.accessioned 2025-10-20T13:29:56Z
dc.date.available 2025-10-20T13:29:56Z
dc.date.issued 2025-05-01
dc.identifier.uri http://hdl.handle.net/123456789/20007
dc.description Mr. Tahir Iqbal en_US
dc.description.abstract In cities, traffic jam usually prevents fast movements of emergency vehicles like ambulances and thus causing critical delays. This is a project that is titled “Intelligent Traffic Control System” and it is the proposal of an AI-centered solution to detect ambulances in traffic and dynamically adjust traffic lights prioritizing them to pass. Using computer vision methods, and deep learning algorithms such as YOLO (You Only Look Once), the system handles real-time or archived traffic video streams to identify ambulances among other vehicles. If an emergency vehicle is detected as approaching a traffic signal, the system automatically shifts the signal serving that vehicle to green thus allowing the vehicle to cross without a hitch. This smart control mechanism seeks to- minimise response time during emergencies, enhance public safety, and maximise traffic flow around junctions. The system is built on Python and OpenCV, with integration to traffic signal logic to show real-time decision-making in AI detection. en_US
dc.language.iso en_US en_US
dc.relation.ispartofseries ;BULC1438
dc.subject Intelligent Traffic Control System en_US
dc.title Intelligent Traffic Control System en_US
dc.type Thesis en_US


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