Improved water resource management framework for water sustainability and security

被引:39
作者
Ahmed, Sameh S. [1 ,2 ]
Bali, Rekha [3 ]
Khan, Hasim [4 ]
Mohamed, Hassan Ibrahim [5 ]
Sharma, Sunil Kumar [6 ]
机构
[1] Majmaah Univ, Dept Civil & Environm Engn, Coll Engn, Majmaah 11952, Saudi Arabia
[2] Assiut Univ, Min & Met Engn Dept, Fac Engn, Assiut 71516, Egypt
[3] Harcourt Butlor Tech Univ, Dept Math, Kanpur 208002, India
[4] Jazan Univ, Dept Math, Coll Sci, Jazan 45142, Saudi Arabia
[5] Assiut Univ, Dept Civil Engn, Assiut, Egypt
[6] Majmaah Univ, Dept Informat Technol, Coll Comp & Informat Sci, Majmaah 11952, Saudi Arabia
关键词
Water resource management; Ultrasonic sensors; Social growth; Internet of things; Water sustainability; Water distribution monitoring system;
D O I
10.1016/j.envres.2021.111527
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The water resource is an essential field of economic growth, social progress, and environmental integrity. A novel solution is offered to meet water needs, distribution, and IoT-based quality management requirements. With technological growth, this paper presents an IoT-enabled Water Resource Management and Distribution Monitoring System (IWRM-DMS) using sensors, gauge meters, flow meters, ultrasonic sensors, motors to implement in rural cities. Thus, research proposes that the IWRM-DMS establish the rural demand for water and the water supply system to minimize water demand. The system proposed includes different sensors, such as the water flow sensor, the pH sensor, the water pressure valve, the flow meters, and ultrasound sensors. This water system has been developed, which addresses the demand for domestic water in the village. Machine Intelligence has been designed for demand prediction in the decision support system. The simulation results confirm the applicability of the proposed framework in real-time environments. The proposed IWRM-DMS has been proposed to analyse the water quality to ensure water distribution in a rural area to achieve less MAPE (21.41%) and RMSE(15.12%), improve efficiency (96.93%), Reliability (98.24%), enhance prediction (95.29%)), the overall performance (97.34%), moisture content ratio (7.4%), cost-effectiveness ratio (95.7%) when compared to other popular methods.
引用
收藏
页数:10
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