Monitoring System for Physical Water Quality Parameters and Automatic Control for Chlorine Dosing in a Aerator Treatment Plant

In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.

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Design of Monitoring System Based on Android Platform and GPRS

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.433-435.1188 ◽

2013 ◽

Vol 433-435 ◽

pp. 1188-1191

Author(s):

Xing Qiao Liu ◽

Qing Feng Chong ◽

Xiao Song Lu

Keyword(s):

Water Quality ◽

Mobile Phone ◽

Monitoring System ◽

Measurement Accuracy ◽

Quality Parameters ◽

Water Quality Parameters ◽

Remote Monitoring System ◽

Control Precision ◽

Dissolved Oxygen Control ◽

Android Platform

This paper presents a wireless remote monitoring system of water quality parameters based on Android platform and GPRS communication technology. This system realizes the remote collection, storage and management of water quality parameters, and also realize the remote control of the control nodes. In acquisition part, sensors collect data which is sent to the remote server through GPRS module, and water quality parameters from the server is sent to the Android mobile phone. In the control part, the control commands from the android mobile phone is sent to the server, and the server again send it to the lower machine to control the control nodes. After practical testing to the system in Liyang, Jiangsu province, temperature measurement accuracy reaches 0.5°C, PH measurement accuracy reaches 0.3, water level control precision can be controlled within ± 3cm, dissolved oxygen control precision can be controlled within ±0.3 mg/L, all the indexes can meet the requirements.

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Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17030737 ◽

2020 ◽

Vol 17 (3) ◽

pp. 737 ◽

Cited By ~ 1

Author(s):

Wei-Jhan Syu ◽

Tsun-Kuo Chang ◽

Shu-Yuan Pan

Keyword(s):

Heavy Metals ◽

Water Quality ◽

Quality Management ◽

Real Time ◽

Monitoring System ◽

Irrigation Water ◽

Water Quality Management ◽

Quality Parameters ◽

Water Quality Parameters ◽

Irrigation Water Quality

In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the real-time automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control.

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Evaluation of physicochemical water parameters in watersheds of southern Brazil

Ambiente e Agua - An Interdisciplinary Journal of Applied Science ◽

10.4136/ambi-agua.2596 ◽

2020 ◽

Vol 15 (5) ◽

pp. 1

Author(s):

Marta Sória ◽

Vitor Emanuel Quevedo Tavares ◽

Marília Alves Brito Pinto ◽

Lizete Stumpf ◽

Daiane Zarnott ◽

...

Keyword(s):

Water Quality ◽

Organic Matter ◽

Water Treatment ◽

Dissolved Oxygen ◽

Treatment Plant ◽

Water Treatment Plant ◽

Quality Parameters ◽

Water Quality Parameters ◽

Water Color ◽

Water Parameters

Water-quality monitoring is one of the main instruments for water-resource management. This work therefore evaluated the water quality of the contribution basin of the Sinnott water treatment plant as well as the relationship between physicochemical water parameters, and analyzed the seasonal variation of water quality parameters as a function of rainfall. The study area encompassed the contribution basin of the Sinnott water treatment plant, formed mainly by the drainage areas of the Pelotas stream and its tributary, the Quilombo Stream, located in the city of Pelotas - Rio Grande do Sul, Brazil. A set of 118,368 data points for each stream was analyzed between 2007 and 2012. The following water quality parameters were evaluated: turbidity, temperature, color, pH, hardness, dissolved oxygen, organic matter, and alkalinity. Results showed that dissolved oxygen and water pH values conformed with Brazilian legislation in the 6 years evaluated. However, water color was the parameter that remained the greatest number of days above the set limits, mainly in the Pelotas Stream. Result indicates the need for conservation actions in the catchment, especially considering the importance of color for the assessment of water quality for public supply, in terms of both treatment costs and of public health. Highest values for water color, turbidity, and organic matter coincided with the occurrence of the highest rainfall values. Agricultural activities may potentiate sedimentation in the contribution basin of the Sinnott water treatment plant.

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Study on Automation Control with Water Quality Monitoring System Based on GPRS Technology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.738.239 ◽

2013 ◽

Vol 738 ◽

pp. 239-242 ◽

Cited By ~ 2

Author(s):

Shi Wei Lin ◽

Yu Wen Zhai

Keyword(s):

Water Quality ◽

Monitoring System ◽

Production Efficiency ◽

Water Quality Monitoring ◽

Quality Parameters ◽

Water Quality Parameters ◽

System Structure ◽

Quality Monitoring ◽

Automation Control ◽

Economy Benefit

The method of water quality monitoring applied by reservoirs is sampling in the scene and analyzing at the laboratory at present. Based on analyzing key problem of water quality monitoring, automatic water quality monitoring system based on GPRS is provided in this paper. The system structure and principle are introduced. The system collects, transmits and processes water quality parameters automatically, so the production efficiency and the economy benefit are improved greatly.

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Research on Monitoring System for Factory Aquaculture

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.765-767.2070 ◽

2013 ◽

Vol 765-767 ◽

pp. 2070-2073

Author(s):

Yan Hua Chen ◽

Jing Ou ◽

Guo Ping Hou

Keyword(s):

Water Quality ◽

Wireless Sensor Network ◽

Sensor Network ◽

Monitoring System ◽

Quality Parameters ◽

Water Quality Parameters ◽

Sensor Nodes ◽

Wireless Sensor ◽

Front End ◽

Upper Computer

This paper proposes a monitoring system for factory aquaculture, which collects data and sends them via wireless sensor network (WSN). This monitoring system consists of front-end equipment and upper computer. The front-end equipment is a wireless sensor network consisting of several sensor nodes with different functions and one coordinator node. The upper computer includes monitoring software to monitor the water quality parameters. We mainly focus on designing the solution of monitoring system, the connection circuit between RS232 and SP3232E, as well as the flow of sampling application. Experimental results show that our monitoring system can meet the basic requirements for monitoring the water quality parameters.

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Artificial intelligence-based monitoring system of water quality parameters for early detection of non-specific bio-contamination in water distribution systems

Water Science & Technology Water Supply ◽

10.2166/ws.2019.057 ◽

2019 ◽

Vol 19 (6) ◽

pp. 1785-1792 ◽

Cited By ~ 3

Author(s):

Silvia Tinelli ◽

Ilan Juran

Keyword(s):

Artificial Intelligence ◽

Water Quality ◽

Monitoring System ◽

Distribution Systems ◽

Water Distribution ◽

Real Life ◽

Quality Parameters ◽

Water Quality Parameters ◽

Support Vector ◽

Exposed Population

Abstract This research aims to simulate bio-contamination risk propagation under real-life conditions in the water distribution system (WDS) of Lille University's Scientific City Campus (France), solving the source identification and the response modeling. Neglecting dynamic reactions and not considering the possible chemical decay of most of the contaminants leads to an overestimation of the exposed population. Therefore, unlike the available event detection models, this study considers the interrelated change of several water-quality parameters such as free chlorine concentration, pH, alkalinity, and total organic carbon (TOC) resulting from the pollutants blending. In fact, starting from regular WDS monitoring, the baseline thresholds for each of the mentioned parameters are established; then, significant deviations from the baseline are used as indication for contaminations. For this reason, the purpose of the research was to develop and demonstrate the feasibility of an artificial intelligence (AI)-based smart monitoring system that will effectively enable water operators to ensure a quasi real-time quality control for early chemical and/or bio-contamination detection and preemptive risk management. Advanced pattern recognizers, such as Support Vector Machines (SVMs), and innovative sensing technology solutions, such as Artificial Neural Network (ANN), have been used for this purpose, identifying the anomalies and the severity-level assessment.

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Wastewater Monitoring System in Industrial Workshop Based on Wireless Sensor Network

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v13i03.6860 ◽

2017 ◽

Vol 13 (03) ◽

pp. 63 ◽

Cited By ~ 2

Author(s):

Minhai Zhang ◽

Shuangxiang She

Keyword(s):

Water Quality ◽

Data Acquisition ◽

Monitoring System ◽

Function Analysis ◽

Quality Parameters ◽

Water Quality Parameters ◽

Sensor Nodes ◽

Wireless Sensor ◽

Polluted Water ◽

Zigbee Network

In this paper, regarding the complexity of polluted water, through analyzing the water environment and its surrounding factors, a water quality monitoring system architecture based on wireless sensor networks is proposed. Firstly, the water quality parameters collected by the sensor are processed by the signal conditioning circuit and then transmitted to the sensor nodes so as to realize the data acquisition of the water quality parameters. Afterwards, through the function analysis of each node in the ZigBee network, the hardware design and software program design of the network coordinator node and the routing node are completed. After joint debugging of the hardware and software, point-to-point communication and system networking of the ZigBee network are achieved. Finally, the results of experiments show that the system can realize the data acquisition and wireless transmission of the temperature and PH parameters of different solutions. Furthermore, each node realizes its own function and meets the design requirements of the system.

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