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Metropolitan cities worldwide face severe traffic congestion due to a significant increase in vehicles, despite inadequate road infrastructure. Conventional traffic signaling systems, relying on manual or time-based control, are inefficient and lack real-time data, leading to delayed emergency response times, fuel waste, and health issues. To address this, a smart traffic management system is proposed, utilizing real-time data from sensors or Google Maps to optimize traffic light control at junctions. This system aims to efficiently manage signaled intersections, leveraging IoT technology and comparative data analysis to develop an algorithm that adapts to dynamic traffic conditions. This approach offers opportunities for advancements in traffic management, detection technology, and flexible optimization techniques through automated learning.
Taiwo et al. (Thu,) studied this question.