MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202621091659 A) filed by Priyanka Rajesh Patil; Dr. Ajay P. Thakare; Anjali Pradip Patil; and Dr. Sumit Dilip Ingle on July 28, 2026, for Iot And Ai-Based Precision Irrigation And Crop Disease Prediction System.
Inventors include Priyanka Rajesh Patil; Dr. Ajay P. Thakare; Anjali Pradip Patil; and Dr. Sumit Dilip Ingle.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: IoT and AI-Based Precision Irrigation and Crop Disease Prediction System The present invention relates to an Internet of Things (IoT) and Artificial Intelligence (AI)- based precision irrigation and crop disease prediction system designed to improve agricultural productivity, optimize water utilization, and support sustainable farming practices. The proposed system integrates multiple environmental sensors, including soil moisture, soil temperature, air temperature, humidity, rainfall, pH, and light intensity sensors, with wireless IoT communication modules to continuously collect real-time field data. The acquired data are transmitted to a cloud-based platform, where AI and machine learning algorithms analyze environmental conditions, crop growth parameters, and historical agricultural datasets to determine optimal irrigation schedules and predict the occurrence of crop diseases at an early stage. The system further incorporates image processing techniques through camera modules or unmanned aerial vehicles for detecting visible symptoms of plant diseases, nutrient deficiencies, and pest infestations. Based on predictive analytics, the system automatically controls irrigation valves and pumps to deliver precise quantities of water only when required, thereby reducing water wastage, energy consumption, and labor costs. Farmers receive instant notifications, disease alerts, irrigation recommendations, and preventive measures through a mobile application or web dashboard, enabling timely decision-making. The invention supports remote monitoring, data logging, weather forecasting integration, and adaptive learning to improve prediction accuracy over time. The proposed system is scalable for various crop types, field sizes, and climatic conditions and can operate in both greenhouse and open-field environments. By combining IoT-enabled sensing, AI-driven analytics, automated irrigation control, and intelligent disease prediction, the invention enhances crop health, increases agricultural yield, minimizes resource consumption, and promotes environmentally sustainable and economically efficient precision agriculture.
Disclaimer: Curated by HT Syndication.
