MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641063254 A) filed by P Durga Bhavani; V. Madhulatha; Ravindrababu Muvva; Pindi Venkanna; Pippirisetti Pavani; Sailaja Mandapalli; and Devalla Trishankar Manikanta on May 19, 2026, for Digital Twin-Based Underwater Waste Evolution Prediction And Risk Management System.
Inventors include P Durga Bhavani; V. Madhulatha; Ravindrababu Muvva; Pindi Venkanna; Pippirisetti Pavani; Sailaja Mandapalli; and Devalla Trishankar Manikanta.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: ABSTRACT: The present invention provides a digital twin based underwater waste evolution prediction and risk management system for continuously monitoring underwater waste deposit, predicting underwater waste degradation behavior, simulating underwater waste contaminant propagation and generating proactive underwater waste environment risk alerts. The system includes a distributed heterogeneous sensor network for collecting physicochemical and environmental telemetry data from underwater environments, an edge processing and data ingestion layer for signal processing and feature engineering, a digital twin modelling engine for generating a 3D virtual copy of monitored underwater waste deposit sites and continuously synchronizing with the real-world, and a machine learning based predictive analytics module for generating multi-horizon probabilistic forecasts of leaching rates of contaminants, degradation indices of structures, and the probability of containment breaches. The system also includes a hydrodynamic diffusion simulation engine for modeling propagation of the contaminants in space and time based on the current velocity fields and environmental parameters and a hierarchical risk classification module configured to provide automatic environmental alerts and contamination risk advisories for regulatory authority endpoints. In some embodiments, the invention also provides Autonomous Underwater Vehicle (AUV) swarms that can undertake adaptive environmental sampling at dynamically identified high uncertainty regions. The invention is a predictive analytics-based framework for environmental risk management that turns today's reactive monitoring of underwater contamination events into a proactive model by leveraging an integrated digital twin simulation and artificial intelligence that can help lower the latency of responding to environmental incidents, enhance contamination forecasting, protect marine ecosystems and support intelligent regulatory decision-making.
Disclaimer: Curated by HT Syndication.
