MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202621007829 A) filed by Dr. Hitesh Kumar; Dr. Anoop Kumar Pathariya; Prof. Shivendra Singh; Yogita Kumbhare; Jay Shankar Kumar; Sushil Kumar; Arpit Pethe; and Dr. Palak Jain Choudhary, Bhopal, Madhya Pradesh, on Jan. 27, for 'a smart predictive maintenance system for industrial assets using multi-parameter sensing.'
Inventor(s) include Dr. Hitesh Kumar; Dr. Anoop Kumar Pathariya; Prof. Shivendra Singh; Yogita Kumbhare; Jay Shankar Kumar; Sushil Kumar; Arpit Pethe; and Dr. Palak Jain Choudhary.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses a smart predictive maintenance system for industrial assets using multi-parameter sensing, designed to enhance reliability and operational efficiency in industrial environments. The system employs a network of heterogeneous sensors to continuously monitor multiple operational parameters such as vibration, temperature, pressure, electrical characteristics, acoustic signals, and environmental conditions of industrial equipment. By capturing comprehensive real-time data from critical assets, the system provides a holistic view of equipment health under varying operating conditions. The collected sensor data is processed through a data acquisition and intelligent analytics framework that performs signal conditioning, feature extraction, and data fusion. Advanced predictive techniques are applied to identify abnormal patterns, detect early-stage faults, and estimate the remaining useful life of industrial assets. The integration of historical and real-time data enables accurate fault prediction and adaptive learning, allowing the system to respond effectively to dynamic industrial operating environments. The proposed predictive maintenance system generates real-time alerts, diagnostic insights, and maintenance recommendations through an interactive user interface. By enabling condition-based and predictive maintenance strategies, the invention significantly reduces unplanned downtime, optimizes maintenance scheduling, and lowers operational costs. The system is scalable and suitable for deployment across various industrial sectors, supporting improved asset management, safety, and long-term performance."
Disclaimer: Curated by HT Syndication.
