MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202621054561 A) filed by Dr. Madhuri M. Barhate; Malhar Ugale; Omkar Singare; Tanvi Shinde; Swanandi Shukla; and Akshata Shirsath on April 29, 2026, for Soil2crop: Smart Soil-Based Crop Recommendation And Yield Optimization System Using Iot And Machine Learning.
Inventors include Dr. Madhuri M. Barhate; Malhar Ugale; Omkar Singare; Tanvi Shinde; Swanandi Shukla; and Akshata Shirsath.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention relates to a smart soil health analysis and crop recommendation system based on Internet of Things (loT) and machine learning technologies for improving agricultural decision-making. The system utilizes a multi-parameter soil sensor capable of measuring key soil properties including nitrogen (N), phosphorus (P), potassium (K), pH level, electrical conductivity, soil moisture, and temperature. These parameters are continuously collected using an ESP32 microcontroller interfaced through an RS485 communication module and transmitted wirelessly to a remote server. The system incorporates a machine learning prediction engine that analyzes soil parameters along with environmental data to recommend the most suitable crops for cultivation. In addition, the system generates fertilizer recommendations and irrigation schedules based on detected soil nutrient deficiencies and moisture levels. A web-based dashboard allows farmers to visualize real-time soil health data, crop predictions, and farming guidance in an intuitive interface. The invention further supports dual input modes, including real-time sensor-based prediction and manual parameter entry, making the system accessible even in environments without sensor hardware. By enabling multi-location soil analysis across different areas of a field, the system improves the accuracy of crop suitability predictions and provides personalized agricultural recommendations. The proposed system offers a scalable, cost-effective, and data-driven solution for precision agriculture, helping farmers optimize crop productivity, reduce resource wastage, and maintain long-term soil health.
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