Intellectual Property India Publishes Patent Application for 'Facial Recognition And Machine Learning-Integrated Smart Attendance Management System For Educational Institutions Management System For Educational Institutions' Filed by Ms. Apeksha Pande; Mr. Prakhar; Ms. Pooja Vinayakrao Ingalkar; Dr. Anju Lata Gajpal; Dr. Swati Jain; Ms. Hemamalini. S; Dr. Ankitha. K; Dr. Brijendra Gupta; Mrs. A. Aafiya Thahaseen; and Mr. Vallem Ranadheer Reddy

MUMBAI, India, July 11 -- Intellectual Property India has published a patent application (202521059706 A) filed by Ms. Apeksha Pande; Mr. Prakhar; Ms. Pooja Vinayakrao Ingalkar; Dr. Anju Lata Gajpal; Dr. Swati Jain; Ms. Hemamalini. S; Dr. Ankitha. K; Dr. Brijendra Gupta; Mrs. A. Aafiya Thahaseen; and Mr. Vallem Ranadheer Reddy, Pune, Maharashtra, on June 2, for 'facial recognition and machine learning-integrated smart attendance management system for educational institutions management system for educational institutions.'

Inventor(s) include Ms. Apeksha Pande; Mr. Prakhar; Ms. Pooja Vinayakrao Ingalkar; Dr. Anju Lata Gajpal; Dr. Swati Jain; Ms. Hemamalini. S; Dr. Ankitha. K; Dr. Brijendra Gupta; Mrs. A. Aafiya Thahaseen; and Mr. Vallem Ranadheer Reddy.

The application for the patent was published on July 11, under issue no. 28/2025.

According to the abstract released by the Intellectual Property India: "The present invention provides a Facial Recognition and Machine Learning-Integrated Smart Attendance Management System tailored for educational institutions to automate and enhance attendance tracking processes. The system integrates convolutional neural networks (CNNs) for high-accuracy facial recognition, achieving over 95% accuracy in identifying students and staff under diverse environmental conditions. A machine learning module employs reinforce- ment learning to adapt to changes in appearance and recurrent neural networks to predict atten- dance patterns, enabling proactive institutional planning. The system features a cloud-based in- frastructure for secure data storage, real-time processing, and seamless integration with existing systems via APIs. A responsive user interface, accessible via web and mobile platforms, pro- vides real-time attendance records, analytics, and alerts to administrators, teachers, and parents in multiple languages. Robust security measures, including AES-256 encryption, anonymized data storage, and compliance with GDPR and the Indian IT Act, 2000, ensure data privacy. The system is scalable, cost-effective, and designed to minimize manual intervention, offering pre- dictive insights for absenteeism, resource allocation, and class scheduling, thereby improving operational efficiency and institutional management."

Disclaimer: Curated by HT Syndication.