AIDSII: An AI-based digital system for intelligent irrigation

被引:2
|
作者
Raouhi, El Mehdi [1 ]
Zouizza, Mohamed [2 ]
Lachgar, Mohamed [1 ]
Zouani, Younes [3 ]
Hrimech, Hamid [4 ]
Kartit, Ali [1 ]
机构
[1] Univ Chouaib Doukkali, LTI Lab, ENSA, El Jadida, Morocco
[2] Moroccan Sch Engn Sci Marrakech, LAMIGEP Lab, Marrakech, Morocco
[3] Cadi Ayyad Univ, Fac Sci & Technol, LAMAI Lab, Marrakech, Morocco
[4] Hassan First Univ, LAMSAD Lab, ENSA, Berrechid, Morocco
关键词
Irrigation; Mobile; Web; Convolutional neural network; Long Short-Term Memory; SECURITY;
D O I
10.1016/j.simpa.2023.100574
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years, precision agriculture has gained significant attention as a result of the rising demand for food and water by the world population and the increasing impact of climate change. This highlights the need for innovative solutions to address this critical challenge. Farmers are facing a shortage of water and fertile land, which demands a new approach to their work. Intelligent irrigation is crucial to improve yields and maximize the use of resources. Various machine learning-based irrigation models have been proposed to minimize water wastage. This paper introduces AIDSII, an AI-powered digital application that leverages IoTbased precision agriculture and CNN-LSTM models. It offers a comprehensive feedback system through mobile and web technologies, enabling farmers to automate, optimize, and streamline their irrigation processes.
引用
收藏
页数:3
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