MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202511115807 A) filed by Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh, on Nov. 23, 2025, for 'iot-enabled machine learning system for real-time weed detection and automated removal and working method thereof.'
Inventor(s) include Mr. Sandeep Yadav; Anjana Goel; Aniket Pravesh Singh; Akhand Pratap Singh; and Abhineet Yadav.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses an IoT-enabled machine learning system for real-time weed detection and automated removal. The system comprises an image acquisition assembly, a processing unit executing a convolutional neural network (CNN) for distinguishing weeds from crops, a microcontroller-based control module, and a robotic actuation mechanism configured for targeted mechanical weed extraction. An IoT communication module enables remote monitoring, cloud analytics, and adaptive operational control. The system operates on a mobile platform to autonomously traverse agricultural fields, detect weed clusters under variable environmental conditions, and perform precision removal without chemical herbicides. A corresponding method includes capturing field images, performing CNN-based classification, generating weed-localization coordinates, actuating mechanical removal, and synchronizing operational data with cloud servers. The invention provides an efficient, scalable, and environmentally sustainable alternative to manual weeding and chemical herbicide use."
Disclaimer: Curated by HT Syndication.
