The integration of Artificial Intelligence and Internet of Things technologies is revolutionizing traffic signal controllers, transforming them from isolated timing devices into intelligent nodes within connected urban ecosystems.

Modern smart controllers leverage machine learning algorithms to analyze complex traffic patterns and make predictive adjustments that optimize flow across entire transportation networks. These systems process vast amounts of data from various sources including vehicle detectors, CCTV cameras, connected vehicles, and even mobile devices to create comprehensive traffic models.

IoT-enabled controllers serve as data collection points within larger smart city frameworks, communicating with other infrastructure elements such as smart lighting, parking systems, and public transportation networks. This interconnected approach allows for coordinated responses to changing conditions – for instance, adjusting signal timing to accommodate public transit vehicles or creating green waves for emergency response routes. The controllers can also interface with vehicle-to-infrastructure (V2I) systems, receiving data directly from connected vehicles about their…

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