MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641113862 A) filed by Dr. S. Sureshkumar; G. Devasena; Anitha. A; R. Tamilkumaran; S. Roobini; Senega. R; and S. P. Kirthivasan on September 23, 2026, for Machine Learning Enabled Iot System For Predictive Failure Detection.
Inventors include Dr. S. Sureshkumar; G. Devasena; Anitha. A; R. Tamilkumaran; S. Roobini; Senega. R; and S. P. Kirthivasan.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention relates to a machine-learning-enabled Internet of Things (IoT) system for predictive failure detection of industrial and electromechanical equipment. The system comprises a plurality of sensors configured to continuously acquire operating parameters including vibration, temperature, current, voltage, speed, pressure and other equipment-specific parameters. A sensor interface unit performs signal conditioning and data acquisition, while an edge-processing unit performs filtering, normalization and feature extraction. The processed data is transmitted through an IoT communication module to a machine-learning engine configured to learn normal operating patterns and identify abnormal conditions indicative of potential equipment failure. A failure-risk assessment unit determines the severity and risk level of the detected condition, and a maintenance decision unit generates appropriate maintenance alerts or recommendations. Historical sensor data, failure events and maintenance records are stored in an equipment condition database and may be used for updating the machine-learning model. The system enables continuous condition monitoring, early failure detection and data-driven predictive maintenance of equipment.
Disclaimer: Curated by HT Syndication.
