Cloud-Integrated IoT Traffic Light Control System for Dynamic Urban Traffic Management

Background: Traditional traffic light systems implement static state-cycles and rely on expensive surveillance systems, causing intersection congestion that contributes to traffic accidents. According to recent urban mobility studies, intersection-related delays account for significant traffic inefficiencies with associated safety concerns [1]. Methods: This research proposes a Cloud-Integrated Internet of Things (IoT) Urban Traffic Light Control (IoT-UTLC) system based on IEEE 802.15.4 Wireless Sensor Network (WSN) using MQTT protocol with Quality of Service (QoS) optimization for adaptive traffic signal management. The system employs IPv6 over Low-power Wireless Personal Area Network (6LoWPAN) for energy-efficient communication and integrates UPPAAL timed automata for formal verification with model complexity analysis including 247 reachable states and 456 transitions across emergency and normal traffic scenarios. Results: Experimental validation on a 1:68 scale prototype with six Re-Motes demonstrated 94.5% accuracy in traffic flow optimization, 0.93 F1-score for emergency vehicle detection, and 185ms average latency with 98.2% Packet Delivery Ratio (PDR) under controlled testing conditions. Statistical analysis using logistic distribution modeling achieved 0.95 correlation coefficient for RTT prediction. Conclusion: The proposed system demonstrates effective performance for adaptive traffic signal management in smart city applications, though optimization remains important for real-world deployment scalability.