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.
Revolutionizing Traffic Management: AI-Driven Micro:bit Integration for Real-Time Traffic Control
Lect. Notes in Networks, Syst.
International Conference on Robotics in Education (RiE) ; 2024 ; Koblenz, Germany April 10, 2024 - April 12, 2024
27.09.2024
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
REVOLUTIONIZING SPACE TRAFFIC MANAGEMENT
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