LEAF SENSE: DECODING NATURE’S PHARMACY

Abstract

Medicinal plants have been an essential part of traditional healthcare systems for centuries, offering natural remedies for a wide range of diseases. Despite their importance, identifying these plants correctly and understanding their medicinal value remains a challenge for the general public due to the need for specialized botanical knowledge. In recent years, the rapid advancement of artificial intelligence and mobile technologies has created new opportunities to make this knowledge more accessible through automated and user-friendly systems.This paper presents Leaf Sense: Decoding Nature’s Pharmacy, an intelligent system that identifies medicinal plants using leaf images and provides detailed information about their therapeutic properties. The system utilizes image processing techniques such as feature extraction, image normalization, and pattern recognition, along with machine learning models—particularly Convolutional Neural Networks (CNNs)—to achieve accurate classification of plant species. A curated dataset of leaf images is used to train and test the model, ensuring robustness under varying conditions such as lighting, orientation, and background noise.In addition to plant identification, the system integrates a structured knowledge base that contains information about medicinal uses, preparation methods, dosage considerations, and safety precautions. This enables users not only to recognize plants but also to understand their practical applications in healthcare. The platform is designed to be accessible through a web or mobile interface, allowing users to upload or capture images in real time and receive instant results.Experimental evaluation shows that the system achieves high classification accuracy and provides reliable information retrieval, making it suitable for educational, agricultural, and healthcare support purposes. By combining artificial intelligence with traditional knowledge, Leaf Sense aims to promote awareness of medicinal plants, support self-learning, and encourage the responsible use of natural remedies in everyday life.