MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641034471 A) filed by Marri Laxman Reddy Institute Of Technology And Management, Hyderabad, Telangana, on March 22, for 'cropsentinel-mnv2: an efficient lightweight transfer learning framework for edge-based rice leaf disease detection.'
Inventor(s) include Mrs. D. Malathi Rani; Mrs. S Sindhu Rekha; Golkonda Sri Sai Akhila; Chalimeti Samhitha; Jampa Haritha; Mrs. P Lavanya; and Mr. Singuluri Manikanth.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "The current invention is associated with a smart platform of automated identification and categorization of rice leaf illnesses by applying artificial intelligence. The system involves a lightweight convolutional neural network based on MobileNetV2 to extract deep features of rice leaf images. The features obtained are then evaluated with the help of various machine learning classifiers such as Support Vector machine (SVM), random forest, and XGBoost. The use of a stacking ensemble approach where the base classesifier predictions are combined with a logistic regression meta-classifier to enhance classification accuracy and reliability is used. The suggested system is computationally effective and able to implement it on resource-constrained edge devices like smartphones and embedded agricultural monitoring systems. The invention will allow farmers to detect rice leaves diseases in real time and precision agriculture, as it will help them identify the disease early and monitor the health of their crops."
Disclaimer: Curated by HT Syndication.
