Industrial IoT Clustering and Digital Intelligent Manufacturing Based on K-Means Algorithm

Abstract

This article puts D2D communication technology into the cellular network for research, which will lead to failure to take into account the fairness of cellular users and D2D users, mainly because their shared spectrum resources will suffer from co-channel interference introduced between communication users during wireless resource allocation.This paper studies the method that the user's communication rate does not change because of the D2D level to a certain extent.However, the K-Means algorithm is generally directly used for industrial IoT clustering, causing some problems. We designed and constructed a 4-layer network topology suitable for digital manufacturing, and developed a unified data acquisition system for equipment. Subsequently, the paper constructed a data processing platform, and with the advantage of Lambda framework, it processed the data in the manufacturing process in batches, greatly improved the processing efficiency of manufacturing data.Finally, the data processing platform is introduced into the actual situation of industrial manufacturing, which is optimized and improved according to the needs of industrial manufacturing, and the industrial Internet of Things technology is combined to create an intelligent manufacturing platform.In this paper, through the study of industrial Internet of Things clustering and digital intelligent manufacturing, it is applied to wireless resource allocation, thereby promoting the development of intelligent systems.