IoT-Based AI-Driven Solutions for Automated Classification and Segregation of Ayurvedic Leaves in Agricultural Applications

In fields like Ayurvedic medicine, where the quality and purity of leaves have a direct impact on the effectiveness of medicinal formulations, the quality and appropriate sorting of leaves are crucial. Large-scale operations cannot use manual sorting techniques since they are frequently laborintensive, time-consuming, and prone to errors. The Ayurvedic Leaf Classification and Segregation System uses Internet of Things (IoT) technology to provide an automated, effective, and accurate solution to these constraints. Based on their current state of health, the technology automatically classifies and separates Ayurvedic leaves. Real-time photos of leaves are taken by a conveyor belt equipped with a camera. These images are then evaluated and contrasted with an existing dataset that includes information on healthy, afflicted, and non-Ayurvedic leaves. A Raspberry Pi processes and transmits the data for verification, and the system's IoT-based design allows for real-time monitoring and decision-making, greatly reducing manual effort while ensuring higher accuracy. The system's design directs healthy leaves to a dedicated storage area, while non-Ayurvedic and affected leaves are automatically removed and collected in a tray attached to the system stand. The system's efficiency and consistency modernize traditional practices, benefiting the agricultural and Ayurvedic medicine industries.