MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202621066151 A) filed by Nivedita Ghodke; Prof. Yogesh J. Gaikwad; Dr. Halaharvi Keerthi; Mrs. Aparna A. Veer; Mrs. Rakhi S. Meshram; and Mrs. Naziya A. Inamdar on May 26, 2026, for Ai-Based Plant Health Monitoring And Disease Prediction System Using Multimodal Data Fusion..
Inventors include Nivedita Ghodke; Prof. Yogesh J. Gaikwad; Dr. Halaharvi Keerthi; Mrs. Aparna A. Veer; Mrs. Rakhi S. Meshram; and Mrs. Naziya A. Inamdar.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: The present invention discloses an Artificial Intelligence (AI)-based plant health monitoring and disease prediction system using multimodal data fusion. The system integrates heterogeneous data sources, including real-time plant leaf images captured through a camera, soil parameters such as moisture, pH, and nutrient levels, and environmental conditions including temperature, humidity, and light intensity. A preprocessing module refines the collected data through cleaning, normalization, and image enhancement techniques. The system employs a hybrid deep learning framework comprising Convolutional Neural Networks (CNN) for extracting visual features and Long Short-Term Memory (LSTM) networks for analyzing temporal sensor data. A multimodal data fusion module combines features from different modalities to generate a unified representation, thereby improving prediction accuracy and robustness. The prediction module classifies plant conditions into healthy, stressed, or diseased categories and performs comprehensive health assessment. Further, a decision support module generates real-time alerts and actionable recommendations related to irrigation, fertilization, and pesticide application. The system is integrated with IoT-enabled devices and supports cloud or edge computing for continuous monitoring. The invention enhances early disease detection, reduces manual intervention, and significantly improves agricultural productivity and sustainability in precision farming environments.
Disclaimer: Curated by HT Syndication.
