Medicinal Plant Detection Using Machine Learning

This paper presents the development of a machine learning–powered Ayurvedic plant detection system integrated into a Flask-based web application. Users can upload images of plants, which are then classified using a pre-trained image recognition model. The system returns a descriptive summary of each plant's medicinal properties and traditional uses. By combining image classification with modern web technologies, the application facilitates real-time plant recognition and enhances accessibility to Ayurvedic knowledge for educational, research, and diagnostic purposes. The integration of artificial intelligence with traditional medicine addresses a key challenge in the digitization and dissemination of indigenous knowledge systems. Many Ayurvedic plants are difficult to identify without expert knowledge, limiting access to their benefits. This application empowers users—ranging from students and researchers to herbal practitioners and enthusiasts—to identify and learn about medicinal plants quickly and accurately. The platform also opens avenues for preserving biodiversity and promoting sustainable practices by raising awareness of the ecological and therapeutic value of native flora. Future enhancements may include expanding the database, supporting multilingual descriptions, and integrating geolocation features for region-specific plant identification.