MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202631016716 A) filed by MCKV Institute of Engineering, Liluah, West Bengal, on Feb. 15, for 'machine learning and fuzzy logic based hybrid device for fertilizer type and quantity prediction.'
Inventor(s) include Mr. Milan Chakrabortty; Dr. Tanmoy Roy Choudhury; Mr. Ribhu Basu; Mr. Kishalay Das; Mr. Rajnish Pandey; Mr. Asim Dasgupta; Mr. Anish Das; and Mr. Arunanshu Paul.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "Machine Learning and Fuzzy Logic based Hybrid Device for Fertilizer Type and Quantity Prediction The present invention relates to an intelligent hybrid fertilizer recommendation system for precision agriculture. The system integrates real-time soil sensing, machine learning models, and a Takagi-Sugeno-Kang (TSK) fuzzy inference mechanism to accurately determine both fertilizer type and optimal application quantity for a selected crop. Soil parameters including nitrogen, phosphorus, potassium, pH, and moisture are acquired using sensors and processed through a machine learning regression model to predict crop-specific nutrient requirements and a classification model to identify suitable fertilizer formulations. A TSK fuzzy logic module computes precise fertilizer dosage by handling uncertainty in soil and environmental conditions, with an iterative nutrient deficit correction mechanism ensuring balanced fertilization. The system provides farmer-friendly outputs specifying fertilizer type and quantity in standard agricultural units and may be implemented as a standalone or automated dispensing device. The invention enables data-driven, adaptive, and environmentally sustainable fertilizer management."
Disclaimer: Curated by HT Syndication.
