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.

中文翻译：

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基于专利视角的边缘计算技术创新趋势

边缘计算是构建5G网络的重要基础，但在我国，基于边缘计算的应用或发明很少。为了提高边缘计算的应用，本文基于专利视角创新设计了人类行为识别系统，为其他研究人员提供参考。本文讨论和设计了一种结合边缘设备和云计算中心的新型边缘计算框架的软硬件方案和相关通信方式。对采集到的人类行为数据进行处理后，对相应监控对象的行为进行分类建模，然后利用边缘设备的分布式计算对这些模型进行修正。这些系统的特点是低能耗和快速响应。实验结果证明。从专利角度看，边缘计算技术的识别效率有了很大的提升。其识别速度比其他算法计算快30%以上，识别准确率达到0.852，比传统识别高20%左右。作者表明，基于专利视角的边缘计算技术可以在我们的生活中发挥重要作用。