MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641056278 A) filed by Vayunandan Kumar Konakalla, Ms - Mis; Dr Gunupusala Satyanarayana; Y. Sherly Priscilla, Assistant Professor,department Of Cse; Mr Suresh Sappa, Assistant Professor, Department Of Computer Science And Engineering; Mr. Siva Ramakrishna Tatapudi, Assistant Professor, Department Of Information Technology; Ms M. Pallavi; Dr B Veeramallu, Professor, Department Of Computer Science And Engineering; and B Durga Sravani, Assistant Professor, Department Of Cse on May 01, 2026, for A Real-Time Adaptive Deep Learning Framework For Edge-Based Anomaly Detection In Distributed Iot Networks.
Inventors include Vayunandan Kumar Konakalla, Ms - Mis; Dr Gunupusala Satyanarayana; Y. Sherly Priscilla, Assistant Professor,department Of Cse; Mr Suresh Sappa, Assistant Professor, Department Of Computer Science; Mr. Siva Ramakrishna Tatapudi, Assistant Professor, Department Of; Ms M. Pallavi; Dr B Veeramallu, Professor, Department Of Computer Science And Engineering; and B Durga Sravani, Assistant Professor, Department Of Cse.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: The present invention employs a decentralized approach, incorporating collaborative learning techniques such as federated learning to enhance model accuracy while preserving data privacy and minimizing communication overhead. Additionally, the framework includes context-aware analysis that leverages temporal and spatial correlations to improve anomaly detection precision. Resource optimization strategies, including model compression and dynamic workload management, are utilized to ensure efficient operation within heterogeneous IoT environments. By combining real-time processing, adaptive intelligence, and distributed coordination, the invention provides a scalable, secure, and robust solution for detecting anomalies in modern IoT ecosystems, making it particularly suitable for critical applications requiring high reliability and responsiveness.
Disclaimer: Curated by HT Syndication.
