MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085150 A) filed by Vignan'S Nirula Institute Of Technology And Science For Women on July 11, 2026, for Predictive Analysis Of Rainfall Patterns Using Machine Learning Techniques.
Inventors include V. Pavani; K. V. S. S. Rama Krishna; P. Sandhya Krishna; B. Aruna Kumari; Challagundla Amrutha; Palanati Sirisha; Ganjapu Sowmya; Gottipatti Tejaswini; Lavanya; and D. Rathnamani.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present invention is related to Predictive Analysis of Waterfall that uses Artificial Intelligence (AI), Machine Learning (ML), Data Analytics, Internet of Things (IoT), and real-time environmental sensing to predict the condition of waterfalls and ensure public safety. The suggested system gathers data from different sources like weather stations, rainfall sensors, water level sensors, flow rate sensors, past environmental records, and satellites. Collected data is subjected to pre-processing, normalization, and feature extraction to remove any noise and improve the prediction accuracy. The machine learning algorithms use different environmental parameters like rainfall rate, river flow, humidity, temperature, water level, seasonality, etc., to forecast future waterfall behavior and possible risks. The suggested system keeps monitoring the environment and makes predictions about changes in the waterfall flow rate, water level, flood chances, and any risky situations through intelligent predictive modeling. Depending upon the prediction output, the proposed invention generates warnings for tourists, local authorities, and disaster management teams. The system will also be storing historical as well as real-time monitoring data in a central database that would ensure continuous improvement of the model, long term environmental analysis, and effective decision making for waterfall management as well as disaster prevention. This particular invention offers a predictive framework that is intelligent, scalable, and automated for implementation purposes in waterfalls, dams, rivers, reservoirs, eco-tourism places, and other natural sources of water. This particular invention incorporates features such as real- time sensing, machine learning for prediction, alert generation, cloud computing, and environmental analysis in one single framework.
Disclaimer: Curated by HT Syndication.
