Intellectual Property India Publishes Patent Application for Ai-Driven Smart Education And Academic Excellence System For Students And Faculty

MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202621084133 A) filed by Abhay Shankar Mishra; Dr. Laxmi Singh Sengar; Ms. Komal Mishra; Dr. Vishal Singh Sengar; Mrs. Hemlata Dhoke; Ms. Sarita Chouhan; Ms. Shivangi Dwivedi; Dr. Sadaf Khan; Dr. Satish Mewada; and Mrs. Bindu Tripathi Pandey on July 09, 2026, for Ai-Driven Smart Education And Academic Excellence System For Students And Faculty.

Inventors include Abhay Shankar Mishra; Dr. Laxmi Singh Sengar; Ms. Komal Mishra; Dr. Vishal Singh Sengar; Mrs. Hemlata Dhoke; Ms. Sarita Chouhan; Ms. Shivangi Dwivedi; Dr. Sadaf Khan; Dr. Satish Mewada; and Mrs. Bindu Tripathi Pandey.

The application for the patent was published on August 28, 2026, under issue no. 35/2026.

Abstract: ABSTRACT AI-Driven Smart Education and Academic Excellence System for Students and Faculty The present invention relates to a system and a method of AI-driven adaptive education management and academic excellence for students and faculty. The system comprises a multi-source educational data acquisition module which collects educational data from learning management systems, enterprise resource planning systems, attendance devices, laboratory equipment, smart classrooms, assessment platforms, digital libraries, research repositories and user devices. A data fusion module validates and synthesizes the acquired information into a single academic dataset for processing by one or more processors. The processors perform distributed edge computing, federated learning, explainable AI, predictive academic analytics, creation of semantic knowledge graphs, adaptive curriculum optimization, intelligent assessment generation, laboratory resource optimization, faculty performance evaluation, secure academic record management, and multi-agent educational assistance. The system automatically produces personalized academic recommendations, optimizes institutional resources, predicts academic risks, and continuously improves analytical models based on operational feedback. The present invention provides improved computational efficiency, prediction accuracy, interoperability, privacy preservation, scalability and autonomous educational decision-making compared to conventional educational management systems.

Disclaimer: Curated by HT Syndication.