scholarly journals A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring

Sensors ◽  
2012 ◽  
Vol 12 (4) ◽  
pp. 4605-4632 ◽  
Author(s):  
Edel O’Connor ◽  
Alan F. Smeaton ◽  
Noel E. O’Connor ◽  
Fiona Regan
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Sensor Networks ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Network Approach ◽  
Neural Network Approach

Study on Prediction Model of Dissolved Oxygen about Water Quality Monitoring System Based on BP Neural Network

2014 ◽  
Vol 912-914 ◽  
pp. 1407-1411 ◽  
Author(s):  
Jing Xin Yan ◽  
Li Juan Yu ◽  
Wen Wu Mao ◽  
Shou Qi Cao
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Prediction Model ◽  
Monitoring System ◽  
Bp Neural Network ◽  
Water Quality Monitoring ◽  
High Water ◽  
Eriocheir Sinensis ◽  
Quality Monitoring

Eriocheir sinensis should cultivate in high water quality ponds, which is affected by many combined factors such as physics, chemistry, biology etc. Using the real-time water quality monitoring historical data to test one of the water quality indexes and predict this index in the next time has great significance. The dissolved oxygen is one of the most important indexes in aquaculture, such as in the Eriocheir sinensis pond. This paper established a dissolved oxygen prediction model of water quality monitoring system based on BP neural network. The forecast data which is predicted by the established model could fit the actual monitoring data very well.

scholarly journals On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1096 ◽  
Author(s):  
Ramón Martínez ◽  
Nuria Vela ◽  
Abderrazak el Aatik ◽  
Eoin Murray ◽  
Patrick Roche ◽  
...  
Keyword(s):  
Water Quality ◽  
Wireless Sensor Networks ◽  
Wastewater Treatment ◽  
Sensor Networks ◽  
Low Cost ◽  
Treatment Plant ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Wireless Sensor ◽  
Smart Water

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.

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