Application of Intelligent Models in Water Resources Management
Subject Areas : Water resources management
Yaser Sabzevari
1
,
Saeid Eslamian
2
1 - Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology
2 - Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology.
Keywords: Artificial Intelligence, Intelligent Models, Deep Learning, Internet of Things, Water Resources Management,
Abstract :
Abstract:
Water resources are one of the most important elements of humanity and are among the factors of progress in various regions. The management of these important resources is an essential and challenging matter in today's world that includes various components. Matters related to the conservation of water resources, water withdrawal, planning of existing water resources and their very appropriate distribution among different consumption sectors are among these components. One of the key components in the optimal use of existing water resources is the proper management of existing water resources using advanced technologies. Water management includes matters related to the conservation of water resources, water withdrawal, planning of existing water resources and their very appropriate distribution among consumers. Water management methods must be fully considered so that water resources remain sustainable in the long term. Available freshwater resources are very limited and of this small amount, approximately 97% of it is saline and not suitable for drinking. The problem of pollution also affects existing water. Various sectors affect water resources, including: agriculture, drinking, industry. Water from different sources needs to be used in an efficient manner that is not available in traditional water management methods. Existing methods for water use are not very cost-effective. Along with the pressure on resources from these sectors, there is also a lack of interest in implementing the latest information and communication technologies. Machine learning algorithms have the potential to expand the learning process exponentially with a specific goal. Modern water management is needed in fields such as agriculture, water supply, industry, hydroelectric power generation, livestock production, etc. Hence, the study and application of modern methods such as machine learning is essential for improving water resource management. This study discussed various challenges and opportunities related to the implementation of deep neural networks for the water management process. Therefore, this study provides a suggestion in the direction of future research activities on the challenges and issues of implementing water management with deep neural networks.
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