Intersección inteligente e IoT: Enfoque basado en prioridades para la movilidad Ubran

Resumen

The recent growth in car use and population have been identified as potential drivers of municipal traffic congestion, particularly in emerging nations with inadequate road networks. In Nigeria, for example, traffic wardens and traffic lights are prominent traffic control measures used to ease traffic congestion at major road intersections. However, stress, public anger, and rash traffic signal judgments restrict the effectiveness of these tactics, resulting in delayed mobility, decreased transit times, and a climate disaster. Recent solutions have emphasized emerging technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and Artificial Neural Network (ANW). Consequently, an efficient use of these technologies can provide a sustainable future for city traffic management in Sub-Saharan African. This model seeks to develop a low cost internet-of-things traffic surveillance system to improve vehicles mobility on a Nigerian closed campus. The goal is to alleviate the academic community's problem of peak-hour traffic congestion by delivering real-time traffic updates