The Role of Edge Computing in Real-Time Iot Data Processing

With the rapid growth of IoT devices, traditional cloud computing faces challenges such as high latency and bandwidth overload, making it unsuitable for real-time applications like industrial control and smart transportation. This paper introduces a real-time IoT data processing approach based on edge computing, enabling efficient local processing through layered architecture design, core technology integration, and optimized workflows. In industrial IoT scenarios, the method reduces equipment downtime from 12 to 4.8 hours per month and shortens data processing delay from 200–300 ms to just 10 ms. In smart city applications, it decreases average travel time by 20% and lowers traffic congestion by 18%. For agricultural IoT, it cuts irrigation water use by 35% while increasing crop yields by 15%. Overall, the proposed method reduces processing delays by 60–95%, improves system throughput by 35%, and enhances resource utilization—offering a reliable, high-performance solution for real-time IoT data processing.