Abstract
Edge computing is an important foundation for building 5G networks, but in my country, there are few applications or inventions based on edge computing. In order to improve the application of edge computing, this article innovatively designs a human behavior recognition system based on a patent perspective, which provides a reference for other researchers. This paper discusses and designs the software and hardware schemes and related communication methods of a new edge computing framework that combines edge devices and cloud computing centers. After processing the collected human behavior data, the behaviors of the corresponding monitoring objects are classified and modeled, and then the distributed computing of edge devices is used to modify these models. These systems are characterized by low energy consumption and fast response. The experimental results prove. The recognition efficiency of edge computing technology from the patent perspective has been greatly improved. Its recognition speed is more than 30% faster than other algorithm calculations, and the accuracy of recognition reaches 0.852, which is about 20% higher than traditional recognition. The authors show that edge computing technology based on a patent perspective can play an important role in our lives.
Highlights
With the rapid development of electronic, information, and communication technologies such as the Internet of Things, 5G, blockchain, and sensors, the growth of various types of data has shown an exponential trend, and the requirements of massive data on computing power and speed are increasing [1, 2]
This approach of putting the analysis model on the edge device can reduce the computing pressure on the cloud on the one hand, and on the other hand, for the delay-sensitive scenarios, the edge device to complete the data analysis work can effectively reduce the time for result generation
Through the coordination and interaction of edge devices and cloud computing centers, it solves the problems of the original system such as slow computing speed and high energy consumption
Summary
With the rapid development of electronic, information, and communication technologies such as the Internet of Things, 5G, blockchain, and sensors, the growth of various types of data has shown an exponential trend, and the requirements of massive data on computing power and speed are increasing [1, 2]. Cloud computing technology provides users with almost unlimited computing power through a large number of high-performance servers in the data center. It is one of the important solutions for big data analysis and processing. Based on edge computing innovation from the perspective of patents, this paper conducts research and analysis on cloud computing and big data and proposes a data acquisition and processing system architecture based on edge computing, which uses edge computing close to users to provide low latency and high processing capabilities. The distributed computing of edge devices is used to modify these models, thereby realizing a human behavior recognition system with high efficiency, low energy consumption, and fast response, which verifies the applicability of the current computing framework to physical data processing
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