IoT Based SCADA for Electrical Measurements and Control

Abstract

The suggested system's primary goal is to shield electrical equipment against malfunctions. The
system consists of various sensors that deployed strategically on electrical equipment. The data of the
equipment is collected and transmitted to cloud platform through Node MCU ESP8266. The data is
simultaneously displayed using LCD display. The collected data is splitted into train and test data.
Train the machine learning model by using different algorithms. The best algorithm is chosen by
calculating their accuracy. In our case, decision tree algorithm is used. The real time data has been
processed and analyzed. If real time data of current and vibration is greater than the recorded values,
the relay tripped, and the equipment is prevented from damage. The main goal of this research is to
create a machine failure prediction system utilizing machine learning techniques. The system's goal is
to use machine-generated real-time data to detect abnormalities in important electrical parameters
including over current, overvoltage, over temperature, over vibration, and other pertinent variables.
The system may anticipate and prevent probable failures by using these aberrant values as reference
points for identical devices.