Water quality monitoring system for aquaponic technology using the internet of things (IoT)

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Communications in Mathematical Biology and Neuroscience Pub Date : 2023-01-01 DOI:10.28919/cmbn/8221
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引用次数: 0

Abstract

The fishery sector has a vital role in driving Indonesia's economy. However, the supply of fish has recently begun to dwindle because of the high cost of fish and unpredictable weather changes. Because of that, this increases the demand for freshwater fish and raises the potential for freshwater aquaculture. Besides, finding suitable water, sources and farming land for fish is extremely difficult because of the limitations of the primary source. This study aims to develop an Internet of Things (IoT) that can monitor water quality parameters, including acid content, dissolved oxygen, the temperature of the water, as well as ammonia, and is integrated with Internet-based mobile applications. The results of the system design have been successfully implemented. The system structure has successfully incorporated a sensor that collects data from the system and sends it to the blynk cloud server, which can be accessed directly via the Internet. Furthermore, this research showed that water quality and circulation are well preserved. The sensor's accuracy of potential hydrogen (pH) acid water is an average error of 1.52%, temperature sensor error of 0.238%, dissolved oxygen sensor error of 0.23%, and ammonia sensor error of 1.723%, and the monitoring system is functioning normally.
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基于物联网的水培技术水质监测系统
渔业部门在推动印尼经济方面发挥着至关重要的作用。然而,由于鱼的高成本和不可预测的天气变化,鱼的供应最近开始减少。因此,这增加了对淡水鱼的需求,提高了淡水水产养殖的潜力。此外,由于主要来源的限制,为鱼类寻找合适的水、水源和农田是极其困难的。本研究旨在开发一种物联网(IoT),可以监测水质参数,包括酸含量、溶解氧、水温和氨,并与基于互联网的移动应用程序集成。系统设计成果已成功实现。该系统结构成功地集成了一个传感器,该传感器从系统收集数据并将其发送到blynk云服务器,该服务器可以通过互联网直接访问。此外,研究表明,水质和循环得到了很好的保存。传感器对潜在氢(pH)酸性水的测量精度平均误差为1.52%,温度传感器误差为0.238%,溶解氧传感器误差为0.23%,氨传感器误差为1.723%,监测系统运行正常。
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来源期刊
Communications in Mathematical Biology and Neuroscience
Communications in Mathematical Biology and Neuroscience COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.10
自引率
15.40%
发文量
80
期刊介绍: Communications in Mathematical Biology and Neuroscience (CMBN) is a peer-reviewed open access international journal, which is aimed to provide a publication forum for important research in all aspects of mathematical biology and neuroscience. This journal will accept high quality articles containing original research results and survey articles of exceptional merit.
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