MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611057282 A) filed by Mr. Rishabh Tomar; and Mr. Yuvansh Teotia on May 05, 2026, for Intelligent Predictive Maintenance System Using Lstm-Based Failure Prediction And Automated Alerting.
Inventors include Mr. Rishabh Tomar; and Mr. Yuvansh Teotia.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The invention presents an intelligent predictive maintenance system that utilizes deep learning techniques, specifically Long Short- Term Memory (LSTM) networks, to predict machinery failures using time-series sensor data. The system processes key operational parameters such as temperature, vibration, pressure, and rotational speed to detect patterns indicative of potential failures. A key innovation lies in integrating failure prediction with severity classification and automated alert generation within a unified framework. The system categorizes predicted failures into multiple severity levels and provides real-time alerts along with actionable maintenance recommendations. The modular architecture enables efficient data preprocessing, model training, and deployment in a scalable manner. The proposed model achieves high performance with accuracy, precision, recall, and F1-score exceeding 95%, demonstrating its effectiveness in real-time industrial applications. Keywords: Predictive Maintenance, LSTM,Deep Learning, Time-Series Data, Failure Prediction, Severity Classification, Automated Alerting, Industrial AI
Disclaimer: Curated by HT Syndication.
