Tingting Wang 

College of Artificial Intelligence and Big Data, ZIBO VOCATIONAL INSTITUTE

Abstract：

In recent years, the rapid development of the Internet of Things (IoT) technology has led to its widespread application in various fields such as industry, transportation, and smart homes. With the explosive growth in the number of IoT devices, the volume of generated data has also increased exponentially, placing higher demands on data processing speed and efficiency. However, the traditional cloud computing model faces challenges in handling the massive data generated by IoT, including high data transmission latency, excessive bandwidth consumption, and significant processing pressure on cloud servers. In scenarios requiring high real-time performance, such as industrial automation and intelligent transportation, data transmission latency can lead to severe consequences. Additionally, security and privacy concerns in data transmission and storage have become increasingly prominent. Intelligent edge computing, as a novel computing paradigm, enables data collection, processing, analysis, and decision-making at the network edge near the data source, effectively addressing these issues. It not only reduces data transmission latency, decreases bandwidth consumption, and improves data processing efficiency but also enhances data security and privacy protection. Therefore, it holds significant application value in IoT architecture.

Key Words：

intelligent edge computing; IoT; optimization; application