DL-Medic:Deep Learning-Based Software for Accurate Medicinal Plant Identification and Benefit Extraction

Medicinal plants play a vital role in both traditional and modern healthcare systems. Accurate identification of these plants is essential for effective use and conservation. However, manual identification is often error-prone due to morphological similarities and the need for expert knowledge. Conventional methods rely on handcrafted features or botanical keys, which lack scalability and generalization. This paper proposes DL-Medic, a deep learning-based software that uses EfficientNet to accurately identify medicinal plants and extract benefits. The system incorporates advanced features such as voice search, text-to-speech (TTS), multilingual support, and geolocation mapping for enhanced usability. A curated dataset of 10,000 images across 30 plant species was collected and augmented using techniques like rotation, flipping, and zooming. Experimental results demonstrate a classification accuracy of 91.5%, with high precision, recall, and F1 scores. In conclusion, DL-Medic bridges the gap between traditional knowledge and AI-driven tools, providing an accessible and robust solution for the identification of medicinal plants.