MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202641092948 A) filed by Ms. Kochumol Abraham; Naveen Parameshwarappa; Deepak Sahu; Dr. Binda M B; Dr. Y. M. Mahaboobjohn; Dr. Kurumalla Suresh; Prof. Twinkle Gaur; Dr. R. Prabhavathy; Dr. Sarika Keswani; Dr. R Bhuvana; and Prof. Dr. Harikumar Pallathadka on July 31, 2026, for Ai-Based Predictive Maintenance Platform Utilizing Sensor Fusion And Advanced Time-Series Learning Models.
Inventors include Ms. Kochumol Abraham; Naveen Parameshwarappa; Deepak Sahu; Dr. Binda M B; Dr. Y. M. Mahaboobjohn; Dr. Kurumalla Suresh; Prof. Twinkle Gaur; Dr. R. Prabhavathy; Dr. Sarika Keswani; Dr. R Bhuvana; and Prof. Dr. Harikumar Pallathadka.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The present invention discloses an AI-based predictive maintenance platform configured to perform intelligent equipment health monitoring and failure prediction through adaptive sensor fusion and advanced time-series learning models. The platform acquires heterogeneous operational data from multiple sensors and performs preprocessing, temporal synchronisation, and feature extraction to generate comprehensive equipment health representations. Advanced artificial intelligence architectures analyse degradation patterns, detect operational anomalies, estimate remaining useful life, and predict potential failures in real time. The invention further incorporates adaptive maintenance recommendation mechanisms and model retraining capabilities for continuously evolving industrial environments. Explainable analytical outputs facilitate informed maintenance decisions while reducing unplanned downtime and improving asset reliability. The scalable architecture supports deployment across manufacturing, transportation, energy, and industrial Internet of Things ecosystems to enhance operational efficiency, maintenance optimisation, and intelligent asset lifecycle management.
Disclaimer: Curated by HT Syndication.
