MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641076940 A) filed by Cvr College Of Engineering on June 22, 2026, for Intelligent Agricultural Yield Prediction Using Quantum Neural Networks.
Inventors include Sindhu Boianapalli; and K Anuradha.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses an Intelligent Agricultural Yield Prediction System Using Quantum Neural Networks (QNNs) for accurate and early estimation of crop yield under diverse agricultural conditions. The proposed system integrates agricultural data such as soil properties, weather parameters, irrigation levels, fertilizer usage, pest incidence, and historical crop productivity. A hybrid quantum-classical learning framework is employed, where quantum neural networks process high-dimensional agricultural data to capture complex nonlinear relationships that are difficult for conventional machine learning models to identify. The system performs data preprocessing, feature optimization, quantum-enhanced learning, and yield prediction through adaptive training mechanisms. By leveraging quantum computing principles such as superposition and entanglement, the invention improves prediction accuracy, computational efficiency, and scalability. The proposed method supports precision agriculture by enabling farmers and agricultural agencies to make informed decisions regarding crop planning, resource allocation, and risk management, thereby enhancing productivity and sustainability.
Disclaimer: Curated by HT Syndication.
