MUMBAI, India, Aug. 8 -- Intellectual Property India has published a patent application (202421007572 A) filed by Shriganesh R Yadav, Thane, Maharashtra, on Feb. 5, 2024, for 'kisaan dost - a comprehensive ml and iot based web framework for smart agriculture.'
Inventor(s) include Adarsh Jaiprakash Singh; Kanan Shailesh Sananse; Shruti Nitin Pinjarkar; Prof. Sonal Jain; Dr. Kiran Deshpande; Dr. Uttam Kolekar; Prof. Vishal Badgujar; and Prof. Mandar Ganjapurkar.
The application for the patent was published on Aug. 8, under issue no. 32/2025.
According to the abstract released by the Intellectual Property India: "More than 70% of rural families in India depend on agriculture for their living, highlighting its vital role in the country's economy. The agriculture industry is an important part of India's economy, contributing around 17% to GDP. Because farmers don't have up-to-the-minute information about soil acidity, the proportion of different soil contents (such as nitrogen, phosphorus, and potassium), soil moisture, and other environmental factors, inefficient farming practices lead to a decrease in overall crop yield. We developed the web-framework "Kisaan Dost" based on Machine Learning (ML), the Internet of Things (IoT), and real-time data analytics to address the issues of underproduction, overfertilization, and soil quality deterioration. Using the hardware module that has been installed, the proposed system can extract data about soil quality and environmental parameters in real-time from the farm field. This data is then processed and sent to cloud and fog computing servers through wireless communication between the gateway and the servers. Utilizing technologies such as real-time data analytics and machine learning, valuable insights are being derived regarding how much fertilizer to apply to soil in order to maintain its quality and optimize crop growth. These insights can then be used to make informed decisions about farming, such as which crops are best suited to specific climates and soil types, and how to maximize crop yields. In order to support optimal crop yield, the proposed system encourages environmentally friendly approaches to different farming techniques and makes it easy for many stakeholders in the agricultural industry to access the information insights that are created."
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