Fluid Management of Traffic Congestion based on Artificial [!Intelligence]

Mekki, Hamza (2023) Fluid Management of Traffic Congestion based on Artificial [!Intelligence]. UNSPECIFIED thesis, UNSPECIFIED.

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Abstract

Nowadays, various innovative technologies are employed to enhance urban mo bility management. In our project, we have embraced this approach by integrating the YOLOv8 model for real-time vehicle detection, utilizing a live video feed from the webcam. This combination has enabled precise traffic surveillance and dynamic management of traffic lights at intersections. Thanks to advanced image processing, we have developed an effective system for regu lating traffic flow, contributing to improved road fluidity and safety. The cameras, capturing real-time processed video streams, enable vehicle detection and intelligently adjust the traffic light cycles. This project illustrates the successful application of embedded technology and artificial intelligence to meet current urban mobility challenges.

Item Type:	Thesis (UNSPECIFIED)
Additional Information:	Mechanical Engineering BSc - Mechatronics Specialization
Divisions:	Műszaki Intézet
Depositing User:	Gergely Beregi
Date Deposited:	07 Aug 2025 09:20
Last Modified:	07 Aug 2025 09:20
URI:	http://szakdolgozat.repo.uniduna.hu/id/eprint/2490

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