MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085354 A) filed by Sri Eshwar College Of Engineering on July 11, 2026, for Adaptive Edge Ai Framework For Maritime Safety With Predictive Distress Detection, Navic Border Intelligence, And Priority-Aware Emergency Communication.
Inventors include Ms. K. Gowthami; Ms. J. Yashwandra; Mr. S. Aravind; and Dr. H. Anandakumar.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: An Adaptive Edge AI Framework for Maritime Safety with Predictive Distress Detection, NavIC Border Intelligence, and Priority- Aware Emergency Communication has been proposed in this work to improve the safety of vessels, to enhance navigation awareness, and to expedite the emergency response. The Sensor Interface and Preprocessing Unit continuously acquire real-time environmental, vessel health, navigation, and crew safety data. An Edge AI Controller then integrates multi-sensor data fusion employing a Kalman Filter with the situational analysis employing Random Forest and Fuzzy Logic for classification. Furthermore, the framework employs LSTM, SVM, and SHAP for predictive distress detection, emergency severity classification, and explainable decision support, respectively. For intelligent navigation, the NavIC Border Intelligence Module continuously monitors the geo-fenced area and predicts the restricted zones or warns the mariners of crossing the borders. It also recommends the safe-route to the vessels. The Priority- Aware Emergency Communication Manager employing MCDM continuously monitors the severity of emergency and selects the best communication network between LoRa, 4G/5G, and Satellite based on the emergency severity, signal strength, battery level, network availability, and the location of vessel. The framework also incorporates energy-optimized vessel operations employing Reinforcement Learning (Q-Learning), real-time renewable power management, local secure data storage with cloud synchronization, vessel self-monitoring, and encryption/decryption employing AES-256. The proposed adaptive edge AI-based framework for maritime safety provides the autonomous risk assessment, predictive-based distress detection, adaptive communication, intelligent border monitoring, and energy-efficient safe navigation, thereby reducing the time for emergency response and minimizing the dependence of the system on continuous cloud connectivity.
Disclaimer: Curated by HT Syndication.
