Review of “Identification of Ayurvedic Medicinal Plant and their Medicinal Properties: A Comprehensive Study”

Review of “Identification of Ayurvedic Medicinal Plant and their Medicinal Properties: A Comprehensive Study”

Sprooha Athalye1, Raj Joshi2, Sahil Shivgan3, Afan Fondu4

1Assistant Professor, Computer Science and Engineering, Finolex Academy of Management and Technology

2 Computer Science and Engineering, Finolex Academy of Management and Technology

3 Computer Science and Engineering, Finolex Academy of Management and Technology

4 Computer Science and Engineering, Finolex Academy of Management and Technology

---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract - Ayurvedic medicinal plants play a crucial role in treating various health conditions, yet their identification often requires expert knowledge. This project proposes an automated, image-based identification system using machine learning and image processing techniques to classify Ayurvedic plants from leaf images. The model is trained on a curated dataset, utilizing convolutional neural networks (CNNs) for accurate recognition and delivering information on each plant’s medicinal properties, traditional uses, and health benefits. Designed with a user-friendly interface, the system aims to assist researchers, herbal practitioners, and the general public in plant identification and knowledge dissemination. Future enhancements may include disease detection, fertilizer recommendations, and an expanded plant database to support broader agricultural and medicinal applications.

Key Words: deep learning, image pre-processing, convolutional neural network, medicinal plants, crops, fertilizer recommendation