Abstract: Advanced traffic control through IoT (Internet of Things) integration represents a transformative approach to urban mobility management, enabling smarter, more efficient, and responsive transportation systems. By leveraging IoT-enabled sensors, devices, and communication networks, real-time data collection and analysis are made possible, providing a holistic view of traffic conditions and allowing for dynamic decision-making. IoT devices, such as connected traffic signals, smart cameras, and vehicle-to-infrastructure (V2I) communication systems, can continuously monitor traffic flow, vehicle speeds, pedestrian movements, and environmental factors like weather or air quality. This data is then processed using advanced analytics, machine learning algorithms, and cloud computing, which can predict traffic congestion, optimize signal timings, reduce delays, and enhance safety measures. Furthermore, IoT integration enables the coordination of various transportation modes, such as public transit, ride-sharing services, and autonomous vehicles, leading to seamless intermodal connectivity. This connected infrastructure also allows for real-time updates and alerts to drivers, helping them navigate efficiently and avoid potential hazards. Additionally, IoT-enabled traffic systems can contribute to sustainable urban planning by reducing carbon emissions, improving energy efficiency, and minimizing traffic- related noise pollution. Ultimately, the integration of IoT in traffic control systems represents a crucial step towards the development of smart cities, where transportation infrastructure is not only automated but also intelligently adaptive to changing conditions, enhancing the overall quality of life for residents and visitors alike.
Keywords: Advanced traffic control through IoT integration uses smart sensors and real- time data to manage traffic better and reduce congestion. It connects vehicles and traffic lights to improve traffic flow and make roads safer.
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