MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641064731 A) filed by Saveetha Engineering College on May 22, 2026, for Ai Powered Soil Health Monitoring System For Precision Farming.
Inventor includes N. Madhumitha.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The agriculture industry is increasingly resorting to sophisticated technologies aimed at tackling soil fertility depletion, inefficiency in resource use, and adverse weather conditions. One of the emerging solutions for improving the productivity of agriculture is precision farming, which relies on data analysis. In this regard, this paper will focus on the development of an Al-Powered Soil Health Monitoring System capable of collecting real-time data using IoT sensors and utilizing machine learning and automated recommendations in order to optimize soil management. The developed soil health monitoring system incorporates soil sensors embedded into the soil in order to constantly monitor soil moisture, soil pH, temperature, electrical conductivity, as well as the concentration of key nutrients, namely, nitrogen (N), phosphorus (P), and potassium (K). The sensor-generated data are uploaded to either a cloud-based or edge computing platform where it undergoes data preprocessing operations including normalization, filtering out noise, and filling missing values. Machine learning techniques, specifically, regression analysis, classification and clustering, are employed in order to assess soil conditions and make predictions. Moreover, predictive analytics can be used for estimating an ideal irrigation schedule as well as the required fertilizer combination, taking into account the type of crops planted, soil quality, and other environmental factors. Another important aspect of the proposed system lies in the automation of the process of giving suggestions and recommendations in terms of optimal irrigation schedules, fertilizer combinations, crops choice, and soil treatments. The system will provide users with actionable suggestions based on their farming needs while minimizing human intervention. By applying sensor-based analytics, the system can reduce the need for conventional soil tests in most cases. The main strengths of the proposed solution can be summed up as follows: crop yield increase, rational consumption of water resources, lower operating costs, and high environmental sustainability of the system. An advantage of the proposed system includes the provision of an overall intelligent framework, which addresses the limitations of the current solutions. In summary, it should be pointed out that the presented Al- Powered Soil Health Monitoring System is capable of ensuring efficient monitoring and maintenance of soil health conditions.
Disclaimer: Curated by HT Syndication.
