Advances in Brain-Computer Interfaces and Neural Integration
Iot-Based Industrial Equipment Monitoring System: Revolutionizing Maintenance Through Smart Data Analytics
Abstract
Amit Kumar Maity, Darshan and Kunal Chauhan
The integration of the Industrial equipment moni- toring and maintenance are revolutionized with the incorporation of Internet of Things (IoT) into industrial settings. This paper deals with an IoT-based industrial equipment monitoring system to optimize the efficiency of industrial process activities through realtime data collection and predictive analytics, minimizing the possible downtime. The proposed system exploits the benefits of a network of smart sensors constantly monitoring critical pa- rameters, like temperature, vibration, and status of operation, in industrial equipment. The advanced machine learning algorithms implemented by the system follow patterns that describe possible breakdowns of the equipment. Hence, there is predictive main- tenance possible through such an approach. This also eliminates sudden breaks; improvement in the maintenance scheduling; and maximization of the machinery’s lifespan. The implementation of this kind of system in industrial settings shows improvement both in the equipment reliability and operational performance while also offering insights into usage of equipment patterns. Further discussions of the paper will include architecture, sensor integration and data processing techniques and challenges in deploying such IoT solutions into industrial settings.