Design of online industrial motor monitoring system using Industrial Internet of Things (IIoT)

In this paper, the Industrial Internet of Things (IIoT) is used to develop a design for an online industrial motor monitoring system. The system enables real-time data gathering, processing, and analysis from motor sensors to answer the growing demand for dependable and efficient industrial operations. Motor performance can be improved and preventive maintenance made easier by integrating IIoT technologies. The IIoT platform is cloud-based, and the system architecture includes motor sensors, a data acquisition system, data processing algorithms, visualisation dashboards, and interface with current industrial systems. While advanced analytics methods like machine learning and anomaly detection offer insights into motor health and enable predictive maintenance, the IIoT platform ensures seamless data transmission, storage, and analysis. Real-time motor health status, historical trends, and alerts are provided by a user-friendly interface to operators and maintenance staff, enabling prompt intervention and maintenance optimisation. The system also has security safeguards, scalability, and integration capabilities to support future development, protect data privacy, and make the most of existing infrastructure. Industrial settings can improve motor reliability, decrease downtime, and optimise maintenance practises by deploying an online motor monitoring system using IIoT.