MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202611051811 A) filed by Dr. Utpal Dhar Das; Dr. Surya Kant Pal; Dr. Arun Kumar; and Dr. Sachin Singh, Greater Noida, Uttar Pradesh, on April 23, for 'ai-based system for rainfall forecasting and flood risk prediction using hybrid machine learning models.'
Inventor(s) include Dr. Utpal Dhar Das; Dr. Surya Kant Pal; Dr. Arun Kumar; and Dr. Sachin Singh.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "The present disclosure relates to an artificial intelligence-based system for rainfall forecasting and flood risk prediction using hybrid machine learning models. The system comprises a data acquisition module configured to collect real-time and historical meteorological and environmental data from multiple heterogeneous sources. A preprocessing module processes the collected data by performing cleaning, normalization, and feature transformation to ensure data consistency and reliability. A predictive analytics module employs a hybrid architecture integrating Random Forest and Support Vector Regression models to generate accurate rainfall forecasts and assess flood risk levels. The system further includes an output module configured to generate early warning alerts and provide actionable insights to disaster management authorities and stakeholders. The proposed system enhances prediction accuracy, supports timely decision-making, and reduces the adverse impact of flood-related disasters through efficient forecasting and risk assessment."
Disclaimer: Curated by HT Syndication.
