MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641086007 A) filed by Savitha Hiremath; Dayananda Sagar University; and Krupanidhi Degree College on July 14, 2026, for Ai-Powered Soil Microbiome Sensor Network With Edge-Ai Inference And 3d Digital Soil Twin.
Inventors include Savitha Hiremath; Dayananda Sagar University; Krupanidhi Degree College; Sushma R; and Dr. Nandini K.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: A network of AI-driven soil microbiome sensors is revealed, including a number of multi-depth covered sensor networks buried in the soil, edge AI gateways, a cloud analytics service, and a mobile application that could be used by farmers. Each sensor node contains six electrochemical and physical sensors, one of which is a new Electrochemical Impedance Spectroscopy (EIS) module, which can measure simultaneously the carbon of microbial biomass and pH, volumetric water content, multi-ion NPK concentrations, temperature and dissolved oxygen at that sensor node, 10 cm, 30 cm, and 60 cm depth. Convolutional Neural Network (CNN) on- device predicts EIS impedance spectra to microbial biomass carbon (MBC) values with R 2 = 0.91 compared to gold-standard wild- type PLFA laboratory analysis. A 3D Digital Soil Twin engine based on Gaussian Process Regression (GPR) builds a continuous spatial soil health model of the field, which produces a quantitative Cumulative Soil Health Index (CSHI) that is updated every 15 minutes with crop-growth-stage-specific weighting. Field trials on a 50-acre wheat crop in Karnataka, India, showed a 22.3 percent increase in yield, 34.7 percent decrease in nitrogen fertiliser usage, 18.4 percent water savings, and 75.9 percent decrease in the occurrence of root disease as compared to conventional monitoring.
Disclaimer: Curated by HT Syndication.
