Abstract
Pedestrian safety at road crossings in urban environments is a critical issue due to the increasing vehicular traffic and high pedestrian density. Traditional traffic control measures often fail to adequately address the dynamic interactions between vehicles and pedestrians, leading to significant risks of accidents. This study proposes the development of an intelligent road-crossing sensor system leveraging advanced technologies such as sensors, artificial intelligence (AI), and the Internet of Things (IoT). The system aims to enhance pedestrian safety by providing real-time alerts and adaptive traffic control, thereby reducing the risk of pedestrian-vehicle collisions. The methodology includes sensor selection, data collection, machine learning model development, and system implementation and testing. The potential benefits and challenges of deploying such systems are also discussed, offering insights into creating smarter and safer urban environments. Keywords: Pedestrian safety, intelligent sensor systems, road crossing, vehicle detection, traffic signals
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