Innovation Trend of Edge Computing Technology Based on Patent Perspective

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.

The Application of Edge Computing Technology in Strength Training in Hip-Hop Training and Teaching under the Background of Artificial Intelligence and Internet of Things

“…They then use distributed computing on edge devices to revise these models with low energy consumption and fast response. The final experimental results show that its recognition speed is more than 30% faster than other algorithms, and the recognition accuracy rate reaches 0.852, which is about 20% higher than traditional recognition [3]. Yu proposed an experimental model that takes mobile edge computing technology as the core and combines data ware-house technology, clustering algorithm, and other methods to build a MEC-based cache mechanism for civil aviation express marketing.…”

Jack and Masters of All Trades: One-Pass Learning of a Set of Model Sets from Foundation Models

“…In addition, despite the flexibility conferred by greater generality, JATs are often too large to be deployed in many situations. Resource-constrained computing requirements are growing in prevalence [13][14][15] owing to the surge in popularity of deep learning across industries and fields. As a result, the problem of inaccessibility-i.e., the lack of resources to utilize such state-of-the-art tools-is recognized as being of critical importance to the majority of the community [16,17].…”