Internet of things based smart health monitoring of industrial standard motors

Abstract

The Industry 4.0 vision provides recommendations how companies can ease the challenges. In an industrial environment, it is beneficial to have a predictive approach to make smart industry using IoT. The Predictive approach includes automating the maintenance activities of machines which help to deliver safety, performance, customer experience, capacity, cost efficiency and sustainability of the key business assets. It also improves the precision and accuracy of data collection, introducing data analytics, removing human bias, improving reproducibility. This will improve information about asset condition, inform inspection and repair schedules based on asset risks. By implementing predictive and preventive maintenance, one can improve equipment life and avoid any unplanned maintenance activity and thus reducing unscheduled downtime. We in this work have a unit which could be easily attached to the motor units and this does not demand any wiring to carry out. The sensor monitor signals from the motor, accurately measuring key parameters at regular interval of time, as desired. And, the data is sent to the cloud, which in our case is adafruit. From there, the data is analysed and it produces meaningful information. The server then sends alert to the users about critical data of machine which can be used for taking corrective actions).