Integrating Traffic Density Analysis with Automated Violation Detection Through IoT Sensor Fussion - Chukwu Augustine Chisom; Ezema Longinus Sunday; Mfonobong Eleazar Benson; Hilary Ugo Ezea (LPPM Universitas Andalas, 2026)
Urban traffic congestion imposes heavy economic and safety burdens on cities, especially in developing countries where fixed-time signal systems are used. Conventional methods are static and exacerbating delays and infractions. This study designs and implements a low-cost intelligent traffic control system that uses density-based signal processing and dual infrared sensors to adapt green-phase durations dynamically. It integrates real-time IoT-enabled offender detection and capture to link control and enforcement. The system uses a PIC16F877A microcontroller with optical dual-sensor arrays to measure traffic density and a Wi-Fi camera to capture images of violators. The Dynamic Time Allocation Technology (DTAT) system uses rules to figure out how much