Detection of Plant Leaf Diseases Using Internet of Things and Machine Learning Based Drone System
Original version
Choudhary, S., Dhote, N. K., Kolhe, M. L. (2024). Detection of Plant Leaf Diseases Using Internet of Things and Machine Learning Based Drone System. I L. Trajković, S. S. Agaian, Y.-D. Zhang, D. Pelusi, Q. Feng, J. He (Red.) Image Processing, Electronics and Computers. Image Processing, Electronics and Computers (57, s. 703-712). https://doi.org/10.3233/ATDE240516Abstract
With rapid improvement in technology, drones become one of the best fit for agriculture due to their various applications such as spraying pesticides and supervising the yield area of farms. A drone-based system can help in detecting the diseases before they spread to the whole farm. The use of the technology will improve the efficiency of the farming sector. The system is designed using the Internet of Things (IoT) with the help of the ESP32 Cam board, Machine Learning (ML) algorithm, and Google Workspace. ESP-32 Cam module captures the images of plants. Google Drive is used to store captured images. The machine learning algorithm is used to extract features from images and detect possible plant diseases. Workspace is used to create an API that gives G-Drive access to the ML algorithm. The system not only saves human work but also helps in increasing the quality of yield.