MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641079455 A) filed by Mr. Win Mathew John; Dr. Binda M B; Dr. Seema Nayak; Dr. S. Sree Hari Raju; Dr. Chamundeeswari R M; Dr. Y. M. Mahaboobjohn; Mr. G D Vignesh; Dr. R. Balakrishna; Dr. Anvesha Katti; Dr. Priyanka Vashisht; and Prof. Dr. Harikumar Pallathadka on June 27, 2026, for Deep Learning Based Autonomous Monitoring System For Early Detection Of Anomalies In Edge Devices.
Inventors include Mr. Win Mathew John; Dr. Binda M B; Dr. Seema Nayak; Dr. S. Sree Hari Raju; Dr. Chamundeeswari R M; Dr. Y. M. Mahaboobjohn; Mr. G D Vignesh; Dr. R. Balakrishna; Dr. Anvesha Katti; Dr. Priyanka Vashisht; and Prof. Dr. Harikumar Pallathadka.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses a deep learning based autonomous monitoring system for early detection of anomalies in edge devices. The system collects real-time operational data from distributed edge devices and processes the collected information using advanced deep learning based anomaly detection models. The system identifies deviations from normal device behavior, generates anomaly scores, predicts potential failures, and initiates autonomous corrective actions. The invention includes adaptive learning mechanisms configured to continuously improve detection accuracy based on changing operational conditions, device behavior patterns, and historical data. The system further supports predictive analytics, explainable anomaly analysis, and distributed edge-based processing to reduce latency and dependency on centralized systems. The disclosed invention enhances reliability, minimizes downtime, improves maintenance efficiency, and enables intelligent monitoring of large-scale edge computing environments.
Disclaimer: Curated by HT Syndication.
