MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641108082 A) filed by R. M. D Engineering College on September 08, 2026, for Ai-Driven Intelligent Digital Twin System For Predictive Monitoring And Optimization Of Industrial Computing Infrastructure.
Inventors include Dr. A. Tamizharasi; Mrs. G. Manisha; Mr. T. Venkatesan; Dr. J. Sherine Glory; and Dr. A. Gnanasekar.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention discloses an AI-driven intelligent digital twin system for predictive monitoring, simulation, and optimization of industrial computing infrastructure. The system comprises sensors and software monitoring agents configured to collect real-time parameters from servers, processors, storage devices, networking equipment, edge computing nodes, virtual machines, power systems, and cooling systems. A data preprocessing module processes the collected information and supplies the processed data to a digital twin engine that generates and continuously synchronizes virtual representations of corresponding physical infrastructure components. An artificial intelligence engine analyzes historical and real-time data to detect anomalies, determine infrastructure health, predict performance degradation, and estimate potential component failures. The digital twin further enables what-if simulation of workload distribution, resource allocation, network configuration, power management, and thermal conditions without directly modifying the physical infrastructure. An optimization engine determines suitable operational actions based on performance, reliability, energy consumption, thermal conditions, resource utilization, and predicted failure risk. The system may implement workload migration, dynamic resource allocation, scheduling, scaling, and cooling or power optimization through a closed-loop feedback mechanism. The proposed invention enables proactive infrastructure management, predictive maintenance, improved computing-resource utilization, reduced downtime, enhanced energy efficiency, and adaptive optimization of industrial computing environments.
Disclaimer: Curated by HT Syndication.
