This project constitutes an educational initiative focused on the application of machine learning and programming within the classroom setting. Within this context, we faced the challenge of designing a system that simulates traffic congestion and responds to the gestures of a traffic guard through an AI-driven, micro:bit-based integrated system. The proposed system aims to alleviate real-world traffic congestion responding to the gestures of a traffic guard. The synchronization of traffic lights is orchestrated through Machine Learning (ML) algorithms. This solution targets easing congestion, particularly focusing on school areas representing a substantial leap forward in strategies for managing vehicle movements at critical junctions near educational institutions.


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    Title :

    Revolutionizing Traffic Management: AI-Driven Micro:bit Integration for Real-Time Traffic Control


    Additional title:

    Lect. Notes in Networks, Syst.


    Contributors:

    Conference:

    International Conference on Robotics in Education (RiE) ; 2024 ; Koblenz, Germany April 10, 2024 - April 12, 2024


    Published in:

    Robotics in Education ; Chapter : 33 ; 379-390


    Publication date :

    2024-09-27


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English