MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202641064119 A) filed by Srm Institute Of Science And Technology Tiruchirappalli on May 21, 2026, for Iot -Based Early Warning And Real-Time Cloudburst Prediction System Based On Hybrid Cnn-Lstm Model.
Inventors include N. Therasa; S. Pavithra; and Dr. A. Kaliappan.
The application for the patent was published on September 04, 2026, under issue no. 36/2026.
Abstract: The current invention is connected to the real-time cloudburst prediction and early warning system grounded on the distributed Internet of Things (IoT) sensing infrastructure and hybrid deep learning analytics. This system consists of the internet of things sensors that are solar powered and programmed to constantly measure atmospheric variables such as rainfall quantity, atmospheric pressure, temperature and humidity in geographically susceptible areas. The information gathered via this network is sent wirelessly via a low-power long-range LoRaWAN network on to a cloud-based processing unit. The processing unit engages a combination of Convolutional Neural Network (CNN) plus Long Short-Term Memory (LSTM) structure and Convolutional layers capture spatial relationships among sensor nodes that are distributed and LSTM layers learn temporal atmospheric correlations based on sliding window time-series data. The system produces a probabilistic forecast of cloudburst and once the forecast probability is greater than a preset limit, an automatic multi-channel early warning signal is given.The invention offers proactive cloudburst forecasting with low operation latency, high forecast accuracy and can be deployed in remote and rough locations.
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