MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641126975 A) filed by Rns Institute Of Technology, R R Nagar Post, Channasandra, Bengaluru.; Rajshekhar A Grncs; Dr. Girijamma H Aprofessor; Dr. Bhavanishankar Kprofessor; Rahul Chavhan Rncs; Sameer Mrncs; and Bharath Y K Rncs on October 25, 2026, for A Machine Learning Based Agricultural Profit Prediction System Using Data Analytics And Deep Learning Techniques.
Inventors include Dr. Girijamma H Aprofessor; Dr. Bhavanishankar Kprofessor; Rahul Chavhan Rncs; Rajshekhar A G Rncs; Sameer Mrncs; and Bharath Y K Rncs.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: Agriculture is one of the most important sectors supporting a large population, but farmers face challenges such as uncertain weather conditions, fluctuating market prices, and plant diseases, which affect crop yield and profitability. Improper decision-making due to lack of accurate information leads to reduced productivity and financial losses. Traditionally, farmers rely on experience-based methods without data analysis. However, the proposed work presents an automated system for predicting agricultural profit using Machine Learning and Deep Learning techniques, mainly Convolutional Neural Networks (CNN). The system uses datasets including soil data, weather conditions, market prices, and plant images, which are preprocessed for analysis. This is followed by model training, profit prediction, disease detection, and evaluation. The system integrates weather and market data through APIs to improve prediction accuracy. The results show improved efficiency compared to traditional methods with reduced time and increased automation. Therefore, the model is deployed as an application with a user friendly interface, enabling farmers to make accurate decisions
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