Edge Computing for Low Latency IoT Application in Urban Mobility
Abstract
Edge computing is transforming low-latency IoT applications related to urban mobility by allowing real-time data processing right at the point where it is generated. In smart cities, where connected vehicles, traffic sensors, and infrastructure generate enormous volumes of data, prompt decision-making is vital for optimizing traffic management, enhancing safety, and improving public transportation systems. This paper examines the role of edge computing in urban mobility scenarios, emphasizing its capacity to reduce latency, minimize bandwidth use, and improve reliability in areas with inconsistent connectivity. By handling data locally, edge computing enables swift reactions to evolving urban challenges and aids in the scalability of smart city projects. The results indicate that utilizing edge computing is crucial for developing efficient, responsive, and sustainable urban mobility solutions, ultimately aiding in the evolution of smarter cities.
Keywords:
Edge computing, Internet of Things , Smart city, AI optimization, Data privacyReferences
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