AI- Driven Identification of Therapeutic Plants

Abstract

The AI Driven Identification of Therapeutic Plants project introduces an innovative solution for identifying medicinal plants using deep learning techniques. By leveraging a Convolutional Neural Network (CNN) algorithm, the system accurately classifies plants from user-uploaded images. Upon identification, the system provides comprehensive information, including the predicted class of the plant, its medical content, age restrictions, gender restrictions, pregnancy restrictions, recommended dose per day, and the mode of use. This detailed, user-friendly web interface allows individuals to upload images and quickly access relevant medicinal details, bridging the gap between technology and traditional plant knowledge. The system is designed to assist healthcare professionals, researchers, and individuals interested in natural remedies, offering an accessible and reliable resource for therapeutic plants. With the continuous growth of data available on medicinal plants, the integration of AI allows for faster and more accurate identification, reducing human error and the time required for manual identification. Additionally, the model’s scalability ensures that as more plant species are studied, the system’s database will continue to expand, providing a valuable tool for plant-based healthcare applicationsnt.