Intellectual Property India Publishes Patent Application for Multi-Sensor Iot And Machine Learning-Based Smart Farm Management System For Automated Resource Optimization And Sustainable Agriculture

MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641098872 A) filed by Mr. Boban Mathews; Prof. Vishal Gotarane; Dr. Pooja Nayak S; Dayananda Sagar Academy Of Technology And Management; Dr. Prabhakar M.; Mrs. Shwetha K; Dr. Rajesh Siddanna; Dr. Santoshkumar S. T.; Dr. Priyanka Naik; and Dr. Devika G on August 15, 2026, for Multi-Sensor Iot And Machine Learning-Based Smart Farm Management System For Automated Resource Optimization And Sustainable Agriculture.

Inventors include Mr. Boban Mathews; Prof. Vishal Gotarane; Dr. Pooja Nayak S; Dr. Prabhakar M.; Mrs. Shwetha K; Dr. Rajesh Siddanna; Dr. Santoshkumar S. T.; Dr. Priyanka Naik; and Dr. Devika G.

The application for the patent was published on August 21, 2026, under issue no. 34/2026.

Abstract: The present invention relates to a multi-sensor Internet of Things (IoT) and machine learning-based smart farm management system for automated resource optimization and sustainable agriculture. The system comprises distributed agricultural sensor nodes, an IoT communication network, an edge and/or cloud processing platform, a sensor data preprocessing and fusion module, a machine learning engine, a farm decision and resource optimization engine, an automated actuator control module, an anomaly detection module and a user interface. The sensor nodes acquire soil, environmental, crop, water and equipment-related parameters from a plurality of agricultural management zones. The acquired data is validated, fused and supplied to the machine learning engine for predicting irrigation requirements, crop conditions, resource demand and agricultural anomalies. The optimization engine determines zone-specific resource-management actions by considering crop requirements, environmental conditions, available water, energy availability and equipment constraints. The actuator control module automatically operates pumps, valves, irrigation systems, fertigation units and other agricultural equipment. Sensor feedback following an automated operation is compared with predicted conditions and supplied to the machine learning engine for adaptive updating of subsequent decisions. The system thereby provides an integrated closed-loop architecture for precision agriculture, automated resource allocation, fault detection and sustainable farm management. Accompanied Drawing [FIGS. 1-2]

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