Vision-Based Adaptive Traffic Signal System with LoRa Emergency Vehicle Priority

Rapid urbanization and the increasing number of vehicles have led to severe traffic congestion and inefficient traffic management systems. Conventional traffic signals operate using fixed timing mechanisms, which fail to adapt to real-time traffic conditions and emergency situations. This research proposes SmartFlow, a vision-based adaptive traffic signal management system integrated with LoRa communication for emergency vehicle prioritization. The system utilizes a Raspberry Pi with a camera module to analyze real-time traffic density using computer vision techniques. Based on detected vehicle density across multiple lanes, signal timings are dynamically adjusted to optimize traffic flow. Additionally, LoRa-enabled communication allows emergency vehicles to transmit priority signals to intersections, ensuring faster clearance and reduced response time. The proposed system enhances traffic efficiency, minimizes congestion, reduces waiting time, and improves emergency response performance.