MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641008233 A) filed by Srinivas Institute Of Technology, Mangaluru, Karnataka, on Jan. 28, for 'agro-predict: data driven crop and yield prediction.'
Inventor(s) include Dr. Lokesh V; Mr. Vivek V Kumar; Mr. Karthik R Kargi; Mr. Rahul M V; Mr. Yogeesha B; Ms. Bhuvana Priya T J; Mr. Ahammad Farzan; Mr. Akesh Vincent; Mr. Akesh Vincent Mr. Anish Raj; Mr. Bhojraj A S; and Mr. Bimal Biju.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "This invention presents a system for modernizing agricultural practices by providing an integrated, data-driven solution for crop and yield prediction. The system addresses the critical challenge farmers face in making optimal planting decisions due to variable soil and environmental conditions. Traditional farming methods lack the precision required to maximize productivity and sustainability. This invention aims to empower farmers with actionable insights derived from machine learning. The system is an interactive web-based platform that allows farmers to input key parameters, including soil metrics (Nitrogen, Phosphorus, Potassium, pH) and environmental factors (temperature, humidity, rainfall). By leveraging sophisticated algorithms, specifically a Random Forest Classifier for crop recommendation and a Support Vector Regressor for yield prediction, the system delivers high-accuracy predictions. It analyzes the user's data to suggest the most suitable crop for cultivation and, by incorporating fertilizer input data, estimates the potential yield. The system architecture features a secure, user-friendly interface with functionalities for data entry, storage, and management, ensuring a seamless user experience. By fusing conventional farming knowledge with advanced data-driven technologies, the system helps increase productivity, optimize resource consumption, and promote sustainable agriculture. This addresses key issues like food security, resource mismanagement, and climate variability, creating a robust tool for future-ready farming."
Disclaimer: Curated by HT Syndication.
