On the use of an IoT integrated system for water quality monitoring and management in wastewater treatment plants

被引:0
|
作者
Martínez R. [1 ]
Vela N. [2 ]
el Aatik A. [2 ]
Murray E. [3 ]
Roche P. [3 ]
Navarro J.M. [1 ]
机构
[1] Research Group in Advanced Telecommunications (GRITA), Universidad Católica de Murcia (UCAM), Guadalupe
[2] Applied Technology Group to Environmental Health, Universidad Católica de Murcia (UCAM), Guadalupe
[3] Research and Development, T.E. Laboratories Ltd. (TelLab), Tullow, Carlow
关键词
Data analytics; Internet of things; Nitrate; Nitrite; Smart city; Water quality monitoring; Water treatment plant; Wireless sensor networks;
D O I
10.3390/W12041096
中图分类号
学科分类号
摘要
The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device. © 2020 by the authors.
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