| Title | Smart Urban Traffic Management Using IoT-Enabled Edge Computing |
| Research Area | IOT |
| Abstract | The rapid growth of urban populations has intensified traffic congestion, resulting in economic losses, increased pollution, and reduced quality of life. Traditional centralized traffic management systems are often limited by high latency and poor scalability. This paper proposes a smart urban traffic management framework leveraging IoT-enabled edge computing. By deploying edge nodes equipped with IoT sensors and data analytics capabilities at critical intersections, the system enables real-time traffic monitoring, congestion prediction, and dynamic signal control. Experimental simulations demonstrate that the proposed framework reduces average traffic delays by 25% compared to traditional centralized systems. The integration of IoT and edge computing provides a scalable, cost-effective solution for smart cities. |
| Keywords | IoT, Edge Computing, Smart Cities, Traffic Optimization, Intelligent Transportation Systems. |
| Paper Status | Published |
| Volume | 1 |
| Issue | 1 |
| Published On | 06/01/2025 |
| Published File |
IJSRTD_4841.pdf
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