Real-Time Data Processing Method of IoT Based on Edge Computing

Abstract

With the surge in IoT devices, traditional cloud computing models expose problems such as high transmission delay and high bandwidth pressure in real-time data processing, making it difficult to meet the needs of scenarios such as industrial control and intelligent transportation. This paper proposes a real-time data processing method for IoT based on edge computing, which realizes efficient local data processing through layered architecture design, core technology research and process optimization. In the industrial IoT scenario, this method reduces the equipment downtime from 12 hours per month to 4.8 hours, and shortens the data processing delay from 200-300 milliseconds to 10 milliseconds; in the smart city scenario, the average travel time on the main road is reduced by 20%, and the traffic congestion index is reduced by 18%; in the field of agricultural IoT, irrigation water consumption is reduced by 35%, and crop yields are increased by 15%. Studies have shown that this method can effectively reduce data processing delays by 60%-95%, increase system throughput by 35%, and significantly improve resource utilization efficiency, providing a reliable solution for the in-depth application and development of IoT technology.