MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641050586 A) filed by Srinivasa Ramanujan Institute Of Technology; B. Varun Kumar; M. Shameer Baba; U. Sushma Priya; and M. Viswanath Reddy, Ananthapuramu, Andhra Pradesh, on April 21, for 'ai-based predictive maintenance system using sensor data and iot.'
Inventor(s) include Srinivasa Ramanujan Institute Technology; B. Varun Kumar; M. Shameer Baba; U. Sushma Priya; and M. Viswanath Reddy.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "AI-Based Predictive Maintenance System Using Sensor Data And IoT Abstract: Industrial systems frequently face unexpected equipment failures, which result in production losses, increased maintenance costs, and safety risks. Traditional maintenance approaches such as reactive and preventive maintenance are not sufficient to handle modern industrial requirements. Therefore, there is a strong need for intelligent maintenance systems that can predict failures before they occur. The present invention introduces an AI-based predictive maintenance system that integrates Internet of Things (IoT) sensors with machine learning techniques to continuously monitor machine health. The system collects real-time data from multiple sensors, including temperature, vibration, pressure, and motion, providing a comprehensive understanding of machine conditions. The collected data is processed using advanced preprocessing techniques such as noise filtering, normalization, and feature extraction. These steps ensure that the data is clean and suitable for analysis. A Random Forest machine learning algorithm is then applied to identify patterns and classify machine health into different states. The system categorizes machine conditions into Normal, Warning, and Critical states, enabling early detection of faults. When abnormal conditions are detected, alerts are generated through a buzzer and GSM module, ensuring immediate notification to maintenance personnel. The invention significantly reduces unplanned downtime, improves equipment reliability, and supports proactive maintenance strategies. It is highly suitable for Industry 4.0 applications and contributes to smart manufacturing environments by enabling intelligent, data-driven decision-making."
Disclaimer: Curated by HT Syndication.
