MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085328 A) filed by Velammal Engineering College on July 12, 2026, for A Machine Learning-Driven Predictive Maintenance System For Industrial Iot Equipment Using Vibration And Thermal Sensor Fusion.
Inventors include Dr. J. Sathya Priya; Mrs. S. Vinodhini; Mrs. G. Preethi; and Mrs. T. V. Saranya.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present system discloses a machine learning-driven predictive maintenance system for Industrial Internet of Things (IIoT) equipment using vibration and thermal sensor fusion. The proposed system integrates MEMS vibration sensors and infrared thermal sensors to continuously monitor the operational condition of industrial machinery. Sensor data are preprocessed and fused through a novel Adaptive Hierarchical Sensor Fusion Predictive Learning (AHSF-PL) framework that dynamically adjusts the contribution of each sensing modality according to operating conditions. The fused features are analyzed using a hybrid machine learning architecture incorporating Random Forest, Gradient Boosting, and Long Short-Term Memory (LSTM) models to identify faults, estimate fault severity, and predict Remaining Useful Life (RUL). Edge computing enables real-time decision-making with low latency while cloud connectivity supports visualization, historical analysis, and maintenance scheduling. Experimental validation demonstrates improved fault detection accuracy of approximately 98.1% compared with conventional single-sensor approaches. The invention significantly reduces unexpected equipment failures, maintenance costs, and production downtime, making it highly suitable for smart factories, Industry 4.0 environments, manufacturing plants, power systems, oil and gas facilities, and other industrial automation applications.
Disclaimer: Curated by HT Syndication.
