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

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

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-13
DOI
https://doi.org/10.55041/ijsrem44405
Primary Topic
Phytochemicals and Medicinal Plants
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Richa Joshi, Sprooha Athalye, Sahil Shivgan
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Phytochemicals and Medicinal Plants
article

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

Richa Joshi, Sprooha Athalye, Sahil Shivgan
article en

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

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 89%
Phytochemicals and Medicinal Plants
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.