scholarly journals Applying a deployment strategy and data analysis model for water quality continuous monitoring and management

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092982
Author(s):  
Fan-Lun Chen ◽  
Bo-Chieh Yang ◽  
Shu-Yi Peng ◽  
Tzu-Chi Lin
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Early Warning ◽  
Continuous Monitoring ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Source Analysis ◽  
Analysis Model ◽  
Environment Analysis ◽  
The Impact

In Taiwan, where residential and industrial areas are in close proximity, finding ways to effectively continuous monitor and manage water quality is an essential issue. This study established a total solution for an Internet of things water quality monitoring network that integrates domestic miniaturized water quality monitoring sensors for real-time transport data of pH, temperature, conductivity, chemical oxygen demand, and copper ions. The data will be used to establish an analysis model based on continuous monitoring of the nation’s background concentration. We designed an automatic continuous monitoring and early warning analysis module for automatic analysis of environmental and instrumental anomalies for decision makers, a “pollution source analysis module” utilizing static and dynamic cross-environment data to swiftly trace upstream pollution sources, and a “pollution hotspot analysis module” to evaluate the impact area of pollutants, and immediate response measures to achieve early warning and swift evaluation for the prevention of water pollution. To do this, we installed 100 domestic miniaturized water monitoring devices in Taoyuan City for testing the solution. We found that the establishment of an Internet of things environment analysis and response model integrated with cross-environment analysis can be applied in water quality monitoring and management to assure improved environmental quality.

scholarly journals STUDY OF WATER POLLUTION EARLY WARNING FRAMEWORK BASED ON INTERNET OF THINGS

2016 ◽  
Vol XLI-B8 ◽  
pp. 335-338
Author(s):  
H. Chengfang ◽  
X. Xiao ◽  
S. Dingtao ◽  
C. Bo ◽  
W. Xiongfei
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Internet Of Things ◽  
Early Warning ◽  
High Speed ◽  
Water Quality Monitoring ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Monitoring Method ◽  
Application Systems

In recent years, with the increasing world environmental pollution happening, sudden water pollution incident has become more and more frequently in China. It has posed a serious threat to water safety of the people living in the water source area. Conventional water pollution monitoring method is manual periodic testing, it maybe miss the best time to find that pollution incident. This paper proposes a water pollution warning framework to change this state. On the basis of the Internet of things, we uses automatic water quality monitoring technology to realize monitoring. We calculate the monitoring data with water pollution model to judge whether the water pollution incident is happen or not. Water pollution warning framework is divided into three layers: terminal as the sensing layer, it with the deployment of the automatic water quality pollution monitoring sensor. The middle layer is the transfer network layer, data information implementation is based on GPRS wireless network transmission. The upper one is the application layer. With these application systems, early warning information of water pollution will realize the high-speed transmission between grassroots units and superior units. The paper finally gives an example that applying this pollution warning framework to water quality monitoring of Beijing, China, it greatly improves the speed of the pollution warning responding of Beijing.

scholarly journals STUDY OF WATER POLLUTION EARLY WARNING FRAMEWORK BASED ON INTERNET OF THINGS

2016 ◽  
Vol XLI-B8 ◽  
pp. 335-338
Author(s):  
H. Chengfang ◽  
X. Xiao ◽  
S. Dingtao ◽  
C. Bo ◽  
W. Xiongfei
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Internet Of Things ◽  
Early Warning ◽  
High Speed ◽  
Water Quality Monitoring ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Monitoring Method ◽  
Application Systems

In recent years, with the increasing world environmental pollution happening, sudden water pollution incident has become more and more frequently in China. It has posed a serious threat to water safety of the people living in the water source area. Conventional water pollution monitoring method is manual periodic testing, it maybe miss the best time to find that pollution incident. This paper proposes a water pollution warning framework to change this state. On the basis of the Internet of things, we uses automatic water quality monitoring technology to realize monitoring. We calculate the monitoring data with water pollution model to judge whether the water pollution incident is happen or not. Water pollution warning framework is divided into three layers: terminal as the sensing layer, it with the deployment of the automatic water quality pollution monitoring sensor. The middle layer is the transfer network layer, data information implementation is based on GPRS wireless network transmission. The upper one is the application layer. With these application systems, early warning information of water pollution will realize the high-speed transmission between grassroots units and superior units. The paper finally gives an example that applying this pollution warning framework to water quality monitoring of Beijing, China, it greatly improves the speed of the pollution warning responding of Beijing.

scholarly journals Designing a Mobile Application for Pool Water Quality Monitoring Based on the Internet of Things

2021 ◽  
Vol 9 (1) ◽  
pp. 47-55
Author(s):  
Yohanes Anton Nugroho ◽  
Muhammad Fitra Pratama
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Fish Mortality ◽  
The Internet ◽  
Monitoring Equipment ◽  
Pool Water ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Changes in temperature, pH, and turbidity in concrete fish ponds greatly impact to the fish survival. Initial observations showed that among 3.067 fish seeds, 1.633 fish (53%) died and only 1.434 fish (47%) was successfully harvested. The application of water quality monitoring devices from concrete pools designed based on the Internet of Things technology has been tested. The monitoring equipment will not function optimally without an application that functions to receive monitoring data and then take action. Pool water quality monitoring equipment connected to the cloud using a GSM network connection. The recorded data is then displayed on the water quality monitoring application that designed using the Android operating system. Application design is developed using a User-Centered Design approach, where the design process was carried out by considering several variables: ease for use, clarity of information delivery, the fulfillment of needs, and appearance. Based on the results of the design evaluation, weaknesses can be determined, namely, difficulty to find the search menu for click history data, find the refresh button, read the results of searching for historical data, and read data in tables and graphs. Based on this, further improvements can be made to improve the application being made. The monitoring equipment is expected to provide information to pond managers to immediately take action if changing in pH and temperature beyond the limit so that the fish mortality rate can be minimized.

scholarly journals Development of Miniaturized Water Quality Monitoring System Using Wireless Communication

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3758
Author(s):  
Hsing-Cheng Yu ◽  
Ming-Yang Tsai ◽  
Yuan-Chih Tsai ◽  
Jhih-Jyun You ◽  
Chun-Lin Cheng ◽  
...  
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Wireless Communication ◽  
Monitoring System ◽  
Industrial Waste ◽  
Continuous Monitoring ◽  
Copper Ion ◽  
Water Quality Monitoring ◽  
Ion Concentration ◽  
Quality Monitoring

Recently, environmental pollution resulting from industrial waste has been emerging in an endless stream. The industrial waste contains chemical materials, heavy metal ions, and other toxic materials. Once the industrial waste is discharged without standards, it might lead to water or environmental pollution. Hence, it has become more important to provide evidence-based water quality monitoring. The use of a multifunctional miniaturized water quality monitoring system (WQMS), that contains continuous monitoring, water quality monitoring, and wireless communication applications, simultaneously, is infrequent. Thus, electrodes integrated with polydimethylsiloxane flow channels were presented in this study to be a compound sensor, and the sensor can be adopted concurrently to measure temperature, pH, electrical conductivity, and copper ion concentration, whose sensitivities are determined as 0.0193 °C/mV, −0.0642 pH/mV, 1.1008 mS/V·cm (from 0 mS/cm to 2 mS/cm) and 1.1975 mS/V·cm (from 2 mS/cm to 5.07 mS/cm), and 0.0111 ppm/mV, respectively. A LoRa shield connected into the system could provide support as a node of long range wide area network (LoRaWAN) for wireless communication application. As mentioned above, the sensors, LoRa, and circuit have been integrated in this study to a continuous monitoring system, WQMS. The advantages of the multifunctional miniaturized WQMS are low cost, small size, easy maintenance, continuous sampling and long-term monitoring for many days. Every tested period is 180 min, and the measured rate is 5 times per 20 min. The feedback signals of the miniaturized WQMS and measured values of the instrument were obtained to compare the difference. In the measured results at three different place-to-place locations the errors of electrical conductivity are 0.051 mS/cm, 0.106 mS/cm, and 0.092 mS/cm, respectively. The errors of pH are 0.68, 0.87, and 0.56, respectively. The errors of temperature are 0.311 °C, 0.252 °C, and 0.304 °C, respectively. The errors of copper ion concentration are 0.051 ppm, 0.058 ppm, 0.050 ppm, respectively.

A Community Facilitation Model for E-Government

2007 ◽  
pp. 114-126
Author(s):  
Kyle B. Murray ◽  
Cory A. Habulin
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Water Monitoring ◽  
Quality Monitoring ◽  
Central Tenet ◽  
Traditional Approaches ◽  
The Impact

This chapter introduces a community facilitation model for e-government. The central tenet of this approach is the empowerment of a segment of the population to act, by providing the tools and information necessary to tackle issues that have been difficult to address with traditional approaches to government. Under this model, government provides an initial spark and then plays a supporting role in the growth of the community. By doing so, the costs of the program are minimized while the impact of the program is maximized. We examine the viability of the model by looking at a case study in water quality monitoring. The case illustrates the power of a government facilitated community of action to address an important problem, and it suggests that such a model can be applied globally and may be relevant to government initiatives beyond water monitoring.

scholarly journals Real-time water quality monitoring through Internet of Things and ANOVA-based analysis: a case study on river Krishna

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Prasad M. Pujar ◽  
Harish H. Kenchannavar ◽  
Raviraj M. Kulkarni ◽  
Umakant P. Kulkarni
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Real Time ◽  
River Basin ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Quality Analysis ◽  
Water Quality Analysis

AbstractIn this paper, an attempt has been made to develop a statistical model based on Internet of Things (IoT) for water quality analysis of river Krishna using different water quality parameters such as pH, conductivity, dissolved oxygen, temperature, biochemical oxygen demand, total dissolved solids and conductivity. These parameters are very important to assess the water quality of the river. The water quality data were collected from six stations of river Krishna in the state of Karnataka. River Krishna is the fourth largest river in India with approximately 1400 km of length and flows from its origin toward Bay of Bengal. In our study, we have considered only stretch of river Krishna flowing in state of Karnataka, i.e., length of about 483 km. In recent years, the mineral-rich river basin is subjected to rapid industrialization, thus polluting the river basin. The river water is bound to get polluted from various pollutants such as the urban waste water, agricultural waste and industrial waste, thus making it unusable for anthropogenic activities. The traditional manual technique that is under use is a very slow process. It requires staff to collect the water samples from the site and take them to the laboratory and then perform the analysis on various water parameters which is costly and time-consuming process. The timely information about water quality is thus unavailable to the people in the river basin area. This creates a perfect opportunity for swift real-time water quality check through analysis of water samples collected from the river Krishna. IoT is one of the ways with which real-time monitoring of water quality of river Krishna can be done in quick time. In this paper, we have emphasized on IoT-based water quality monitoring by applying the statistical analysis for the data collected from the river Krishna. One-way analysis of variance (ANOVA) and two-way ANOVA were applied for the data collected, and found that one-way ANOVA was more effective in carrying out water quality analysis. The hypotheses that are drawn using ANOVA were used for water quality analysis. Further, these analyses can be used to train the IoT system so that it can take the decision whenever there is abnormal change in the reading of any of the water quality parameters.

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