Industrial Automation with Safety Aspects using Machine Learning Techniques

Abstract

Human Machine Interactive(HMI) system is an interactive system which is used for the communication between user and machine. Based on Training data, the system is made to understand the simple commands even in peculiar timings and server will be able to predict user’s command acting on the basis of the previous history to make an intelligent workspace. The history is saved in datasets, whenever hardware senses the parameters pushes all values to dataset. With Training data machines can work as intelligent, just make them feed on relevant data. Industries with electronic appliances are controlled automatically. Machine Learning(ML) is one of the growing platforms for automation, through which new advancements are made through which easily monitor as well control the system using datasets. ML algorithms can discover associations, perceive patterns, understand composite tasks and make decisions. This paper uses past datasets of sensors, and then design the hardware using ML and connecting to embed system with training datasets. Based on the information, system is made to understand the simple commands and the server will be able to predict user’s command acting on the basis of the previous history to make an intelligent workspace. So we can provide safety aspects in industrial automation. This paper extending the use of random forest algorithm to fulfill the purpose of reduce false deduction, take important decisions and to get accurate results in very short period of time. It will raise alarms besides it will send notification to the mobile with danger message before accidents occur.