| Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
|
|
|---|---|---|
| Article Number | 00007 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202560100007 | |
| Published online | 16 January 2025 | |
Detection and Management of Water Stress at Plants by Deep Learning and Image processing Case-study of Tomato
1 MMCS Team, EST Meknes, Moulay Ismail University, Meknes, Morocco
2 Faculty of Sciences Meknes, Moulay Ismail University, Meknes, Morocco
3 S.A.R.S Team, ENSA of Safi, UCA University, Marrakech, Morocco
4 Faculty of science Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fes Morocco
This project aims to develop an innovative technique for detecting water stress in tomato plants using deep learning and image processing techniques, and to integrate it into a mobile application for real-time monitoring. The methodology adopted includes the acquisition and preprocessing of image data, the construction and training of a deep learning model, and the development of a user-friendly mobile application. The results show a promising performance of the model in the precise detection of water stress, confirming the usefulness and usability of the developed mobile application.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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