MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641094833 A) filed by Dhanalakshmi Srinivasan College Of Engineering And Technology on August 05, 2026, for Quantum Machine Learning For Advanced Climate Pattern Detection Using Satellite Data.
Inventors include K. Rajavadhani; Kasturi Uday Kiran; Jerlin Flowerence D; and Challagundla Rakesh.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: Quantum Machine Learning for Advanced Climate Pattern Detection Using Satellite Data The present invention provides a system and method for advanced climate pattern detection using satellite-derived climate data and Hybrid Quantum Machine Learning techniques. The framework utilizes climate variables including temperature, precipitation, soil moisture, evapotranspiration, and vegetation indices for environmental analysis and anomaly prediction. The system performs data preprocessing, feature engineering, StandardScaler normalization, and Principal Component Analysis (PCA) to generate optimized feature representations. A Quantum Neural Network implemented using PennyLane and PyTorch is employed to identify complex climate patterns and predict environmental anomalies such as drought risk, vegetation stress, and land degradation. A Random Forest model is additionally utilized as a classical baseline model for comparative evaluation. The system incorporates an interactive Streamlit dashboard for climate visualization, prediction monitoring, performance evaluation, and decision support. The proposed invention improves climate anomaly detection accuracy, reduces computational complexity, and provides an efficient framework for environmental monitoring, climate risk assessment, and future climate forecasting applications._
Disclaimer: Curated by HT Syndication.
