FreshBox AI: A Machine Learning-Based Approach for Medicinal Plant Identification and Authentication

The rise of machine learning (ML) presents a powerful solution to challenges in identifying medicinal plants, particularly in India, where Ayurveda and traditional medicine play a critical role. This project proposes an ML-based image processing software to accurately identify medicinal plants, addressing issues of misidentification, adulteration, and unsustainable harvesting. Current methods often lack precision and automation, but by leveraging algorithms like Convolutional Neural Networks (CNNs) and Transfer Learning, the software will enhance the authenticity of herbal products and create a transparent, tech-driven supply chain. This system is designed to mitigate risks to consumers from counterfeit products and promote sustainable harvesting, ensuring the protection of India's rich biodiversity and the livelihoods of communities reliant on this trade. The success of the system will be evaluated through key performance metrics such as accuracy, precision, recall, and F1-score, positioning India as a leader in blending technology with traditional medicine

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Publication Details

Published
2025-05-07
DOI
https://doi.org/10.1109/rmkmate64874.2025.11042340
Primary Topic
Plant tissue culture and regeneration
Type
article
Field-Weighted Citation Impact
0.00
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article

FreshBox AI: A Machine Learning-Based Approach for Medicinal Plant Identification and Authentication

K. Chidambarathanu, R. Udhayakumar, S Sanjeevan
Plant tissue culture and regeneration
article

FreshBox AI: A Machine Learning-Based Approach for Medicinal Plant Identification and Authentication

K. Chidambarathanu, R. Udhayakumar, S Sanjeevan
article en

Abstract

The rise of machine learning (ML) presents a powerful solution to challenges in identifying medicinal plants, particularly in India, where Ayurveda and traditional medicine play a critical role. This project proposes an ML-based image processing software to accurately identify medicinal plants, addressing issues of misidentification, adulteration, and unsustainable harvesting. Current methods often lack precision and automation, but by leveraging algorithms like Convolutional Neural Networks (CNNs) and Transfer Learning, the software will enhance the authenticity of herbal products and create a transparent, tech-driven supply chain. This system is designed to mitigate risks to consumers from counterfeit products and promote sustainable harvesting, ensuring the protection of India's rich biodiversity and the livelihoods of communities reliant on this trade. The success of the system will be evaluated through key performance metrics such as accuracy, precision, recall, and F1-score, positioning India as a leader in blending technology with traditional medicine

Zero hunger
Openalex Percentile: Top 87%
Plant tissue culture and regeneration
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