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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 |