Identification of medicinal plant by using Esp-32 module with IOT technology

Priyan, M Shunmuga and Deepthi, RD and Dharshini, P and Shalini, V and Swetha, V (2025) Identification of medicinal plant by using Esp-32 module with IOT technology. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2038-2049. ISSN 2582-8266

The accurate identification and monitoring of medicinal plants in remote and diverse terrains is crucial for biodiversity conservation, pharmaceutical research, and traditional medicine documentation. This project presents an IoT-based medicinal plant identification system that integrates deep learning with robotics and wireless communication to automate the process of plant species recognition in real-world environments. Manual plant identification is time-consuming and often error-prone, especially in inaccessible regions. With the advancement of IoT, automated plant classification systems can now be deployed in the field. The ESP32-CAM, a compact low-power module with onboard Wi-Fi and camera, offers an ideal platform for real-time image capture and cloud data transmission. Combining this with the Rocker-Bogie mechanism enables smooth traversal over rough terrain, making it suitable for field applications. The proposed system consists of a mobile robotic platform using the Rocker-Bogie mechanism for stable all-terrain navigation. Mounted on the robot is an ESP32-CAM module that captures high-resolution images of plants from multiple angles. A GPS module is integrated to tag each image with accurate geo location data. The Rocker-Bogie platform provided stable movement across uneven surfaces, while the ESP32-CAM captured clear images for classification. The developed IoT-based medicinal plant identification system effectively combines to provide a reliable and scalable solution for automated plant monitoring in remote environments.