Monitoring and controlling the desalination plant using IoT

被引:0
|
作者
Murugan T.M. [1 ]
Kiruba Shankar R. [2 ]
Shivkumar P. [3 ]
Raja Kumar S. [4 ]
Gayathri K. [5 ]
Jeyam A. [6 ]
机构
[1] Department of Electronics and Instrumentation Engineering, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, Erode
[2] Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Tamilnadu, Coimbatore
[3] Department of Electrical and Electronics Engineering, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, Erode
[4] Department of Electronics and Communication Engineering, Panimalar Engineering College, Tamil Nadu, Chennai
[5] Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Tamil Nadu, Dindigul
[6] Nuclear Power Corporation of India Limited, Kudankulam, Radhapuram, Tamil Nadu
来源
Measurement: Sensors | 2023年 / 27卷
关键词
Cloud; Desalination; Internet of things; Sensors; Water;
D O I
10.1016/j.measen.2023.100720
中图分类号
学科分类号
摘要
In this paper, the need for innovative technology and ways to accomplish optimized resource use and desalination treatment, which transforms saltwater into clean drinking water, has been underlined by rising water demands and a degrading environment. The Internet of Things (IoT) now permits to automate a variety of formerly moment and source of energy tasks. One of these is improving water treatment management. This research represents an IoT model for monitoring and controlling a desalination plant. This system monitors the water quality parameters like pH values, temperature, and dissolved oxygen parameters, which are helpful to assess water quality and identify fault parameters at the desalination plant. Here, separate sensors are involved to gather the information and store it in the cloud. It also sends SMS notifications and warnings when it detects misfunctioning, and it regulates the gate valves. This is very needed to rectify the errors, prevent the system from failing, and reduce the maintenance costs as well. This proposed system is highly effective compared to others. According to experimental findings, the proposed technique extends the time by 1.0638%, 6.3829%, and 14.8936% compared to the RO, ED, and FACETS methods. © 2023
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