An Efficient IoT-based Smart Water Meter System of Smart City Environment

被引:0
作者
AL-Madhrahi, Raad [1 ]
Abdullah, Jiwa [1 ]
Alduais, Nayef A. M. [2 ]
Mahdin, Hairulnizam B. [2 ]
Nasser, Abdullah B. [4 ]
Saad, Abdul-Malik H. Y. [3 ]
Alduais, Husam Saleh [5 ]
机构
[1] Univ Tun Hussein Onn Malaysia, Fac Elect & Elect Engn, Johor Baharu, Malaysia
[2] Univ Tun Hussein Onn Malaysia, Fac Comp Sci & Informat Technol, Johor Baharu, Malaysia
[3] Univ Teknol Malaysia, Div Elect & Comp Engn, Sch Elect Engn, Johor Baharu 81310, JB, Malaysia
[4] Univ Malaysia Pahang, Fac Comp, Coll Comp & Appl Sci, Pekan 26600, Pahang, Malaysia
[5] Univ Malaya, Dept Architecture, Fac Built Environm, Kuala Lumpur 50603, Malaysia
关键词
Internet of things; smart water metering; energy consumption; smart city; DESIGN;
D O I
10.14569/IJACSA.2021.0120848
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Water is a precious need of our lives. Due to the rapid population and urbanization, water usage monitoring is a significant problem facing our society. One solution is to control, analyze, and reduce the water consumption of the houses. The emerging of the Internet of Things (IoT) concept lately in our lives has offered the opportunity to establish water usageefficient smart devices, systems and applications for buildings and cities. Many studies have suggested designing an IoT-based smart meter system; however, the IoT sensor node has limited studies, especially in battery life. Therefore, this study aims to implement and analyze an efficient data collection algorithm for IoT-based smart metering applications in consideration with energy consumption. The system items used are Arduino Uno, Wi-Fi-ESP8266, and water flow sensors. The applied algorithm is an efficient data collection algorithm for water meter (EDCDWM) to reduce the number of packet transmissions. Arduino performed this system's implementation, while the simulation and analysis performed by MATLAB R2019b. The average percentage of energy saved by the applied algorithms of EDCDWM absolute change; and EDCDWM with relative differences in all nodes are around 60% and 93%, respectively.
引用
收藏
页码:420 / 428
页数:9
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