Intellectual Property India Publishes Patent Application for 'An Intelligent Iot And Deep Learning-based System For Real-Time Energy Saving And Financial Growth In Smart Educational Campuses' Filed by A. Vasantharaj; K Saifuddin; Dr. Andras Szeberenyi; Gokula Brindha S; Appa Rao Nagubandi; Venu Pantangi; Ravi Teja Aida; Yeshaswini R; Jasmine Mystica K; Nadikatla Chandrasekhar; R. Veerappan; and Boddeda Omnamasivaya

MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202641006769 A) filed by A. Vasantharaj; K Saifuddin; Dr. Andras Szeberenyi; Gokula Brindha S; Appa Rao Nagubandi; Venu Pantangi; Ravi Teja Aida; Yeshaswini R; Jasmine Mystica K; Nadikatla Chandrasekhar; R. Veerappan; and Boddeda Omnamasivaya, Coimbatore, Tamil Nadu, on Jan. 23, for 'an intelligent iot and deep learning-based system for real-time energy saving and financial growth in smart educational campuses.'

Inventor(s) include A. Vasantharaj; K Saifuddin; Dr. Andras Szeberenyi; Gokula Brindha S; Appa Rao Nagubandi; Venu Pantangi; Ravi Teja Aida; Yeshaswini R; Jasmine Mystica K; Nadikatla Chandrasekhar; R. Veerappan; and Boddeda Omnamasivaya.

The application for the patent was published on Feb. 6, under issue no. 06/2026.

According to the abstract released by the Intellectual Property India: "An Intelligent IoT and Deep Learning-Based System for Real-Time Energy Saving and Financial Growth in Smart Educational Campuses is the proposed invention. The proposed invention is an intelligent Internet of Things (IoT) and deep learning-based system for real-time energy saving and financial growth in smart educational campuses. The system utilizes distributed IoT sensors and smart meters to continuously monitor energy usage, occupancy, environmental conditions, and equipment status across campus facilities. Advanced deep learning models analyze the collected data to predict energy demand, detect anomalies, and optimize energy consumption dynamically. Automated control mechanisms regulate lighting, HVAC systems, and electrical devices based on real-time insights, thereby minimizing energy wastage while maintaining user comfort. In addition, the system incorporates financial analytics and predictive maintenance modules to reduce operational costs, support budget planning, and enhance long-term financial efficiency. The proposed solution offers a scalable, adaptive, and environmentally sustainable framework that supports green campus initiatives while enabling data-driven decision-making for improved energy efficiency and financial performance in educational institutions."

Disclaimer: Curated by HT Syndication.