Study on ACM Sensor Data Analysis by AI

Abstract

In this study, two methods of machine learning were investigated with the aim of using AI to identify the huge amount of output data obtained from ACM sensors. Specifically, the data obtained from the ACM sensors for implementation were analysed using supervised and unsupervised methods of machine learning. As a result, classification was carried out with high accuracy （95％） using supervised learning, but unsupervised learning, which is considered to be effective in actual operation, was considered to require further study because of low accuracy （60％）.