MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641064387 A) filed by Aditya University, Surampalem, Andhra Pradesh, on May 21, for 'ai-based predictive maintenance platform utilizing sensor fusion and advanced time-series learning models.'
Inventor(s) include Dr. Chintureena Thingom; and Dr. Thangjam Ravichandra.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "An AI-based predictive maintenance platform utilizing sensor fusion and advanced time-series learning models is disclosed. The platform comprises a sensor acquisition layer configured to collect operational data from multiple industrial sensors associated with monitored equipment and infrastructure assets. A sensor fusion engine aggregates, preprocesses, synchronizes, and correlates heterogeneous sensor data streams to generate unified operational representations. A time-series learning engine employing artificial intelligence and deep learning models analyzes sequential operational data to identify degradation patterns, anomaly conditions, remaining useful life estimations, and potential failure probabilities. An anomaly detection subsystem continuously evaluates real-time equipment behavior against learned operational profiles, while an adaptive learning controller dynamically updates predictive models using operational feedback and maintenance records. A maintenance orchestration module generates predictive alerts, maintenance schedules, and optimization recommendations for improving equipment reliability, minimizing downtime, reducing maintenance costs, and enhancing industrial asset management efficiency."
Disclaimer: Curated by HT Syndication.
