MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641098846 A) filed by Madhankumar C; Mr J. Thavamani - Srm Institute Of Science And Technology; Mr V. Rajasekar - Srm Institute Of Science And Technology; Dr. G. Kasiraman - Srm Institute Of Science And Technology; Dr. Shweta Chikkegoud - Sharnbasva University; Dr. S. Saranyasri - K. Ramakrishnan College Of Technology; and Dr. P. Madhan Kumar - V. S. B. College Of Engineering Technical Campus on August 15, 2026, for Ai-Driven Hybrid Thermal Energy Recovery And Intelligent Heat Management System For Sustainable Industrial Operations.
Inventors include Mr J. Thavamani - Srm Institute Of Science And Technology; Mr V. Rajasekar - Srm Institute Of Science And Technology; Dr. G. Kasiraman - Srm Institute Of Science And Technology; Dr. Shweta Chikkegoud - Sharnbasva University; Dr. S. Saranyasri - K. Ramakrishnan College Of Technology; and Dr. P. Madhan Kumar - V. S. B. College Of Engineering Technical Campus.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: AI-Driven Hybrid Thermal Energy Recovery and Intelligent Heat Management System for Sustainable Industrial Operations Abstract Industrial facilities generate substantial quantities of waste heat from furnaces, boilers, kilns, compressors, engines, exhaust systems, and other high-temperature processes, resulting in significant energy losses and increased operating costs. Conventional heat-recovery systems generally operate using fixed configurations and limited monitoring capabilities, making them less responsive to changing process conditions and variable thermal loads. The present invention proposes an AI-Driven Hybrid Thermal Energy Recovery and Intelligent Heat Management System for improving energy efficiency and sustainable industrial operations. The proposed system integrates thermal sensors, industrial IoT devices, heat exchangers, thermal storage units, heat pumps, thermoelectric or other waste-heat conversion modules, and an artificial intelligence-based heat management controller. Real-time temperature, pressure, flow rate, energy consumption, equipment operating conditions, and thermal-load data are continuously collected and analyzed by an AI prediction and optimization engine. The system dynamically identifies available waste-heat sources, predicts thermal energy availability, determines suitable recovery pathways, and intelligently distributes recovered heat to appropriate industrial processes. A hybrid thermal recovery architecture enables recovered energy to be utilized directly, stored for later use, converted into useful electrical energy, or upgraded through heat-pump based thermal management according to process requirements. The AI controller continuously optimizes heat-flow routing, storage charging and discharging, equipment operation, and thermal-load balancing while considering energy demand, operating constraints, and efficiency objectives. Predictive maintenance capabilities further identify abnormal thermal patterns and potential equipment degradation. The proposed system reduces waste-heat losses, improves overall energy utilization, reduces dependence on external energy sources, and supports lower industrial energy consumption and carbon emissions. The invention provides a scalable and intelligent framework for integrating waste-heat recovery with real-time predictive control, enabling more efficient, adaptive, and sustainable industrial thermal-energy management.
Disclaimer: Curated by HT Syndication.
