Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance

An online analytic service system was designed as a web and a mobile application for shrimp farmers and shrimp farm managers to manage the growth performance of shrimp. The MySQL database management system was used to manage the shrimp data. The Apache Web Server was used for contacting the shrimp database, and the web content displays were implemented with PHP script, JavaScript, and HTML5. Additionally, the program was linked with Google Charts to display data in various graphs, such as bar graphs and scatter diagrams, and Google Maps API was used to display water quality factors that are related to shrimp growth as spatial data. To test the system, field survey data from a shrimp farm in southern Thailand were used. Growth performance of shrimp and water quality data were collected from 13 earthen ponds in southern peninsular Thailand, located in the Surat Thani, Krabi, Phuket, and Satun provinces. The results show that the system allowed administrators to manage shrimp and farm data from the field sites. Both mobile and web applications were accessed by the users to manage the water quality factors and shrimp data. The system also provided the data analysis tool required to select a parameter from a list box and shows the association between water quality factors and shrimp data with a scatter diagram. Furthermore, the system generated a report of shrimp growth for the different farms with a line graph overlay on Google Maps™ in the data entry suite via mobile application. Online analytics for the growth performance of shrimp as provided by this system could be useful as decision support tools for effective shrimp farming.

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Comprehensive Assessment of Water Quality and Pollution Source Apportionment in Wuliangsuhai Lake, Inner Mongolia, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17145054 ◽

2020 ◽

Vol 17 (14) ◽

pp. 5054 ◽

Cited By ~ 1

Author(s):

Rui Shi ◽

Jixin Zhao ◽

Wei Shi ◽

Shuai Song ◽

Chenchen Wang

Keyword(s):

Water Quality ◽

Inner Mongolia ◽

Principal Component ◽

Middle Part ◽

Quality Data ◽

Quality Factors ◽

Water Quality Data ◽

Irrigation Area ◽

Irrigation Period ◽

Hetao Irrigation Area

Water quality is a key indicator of human health. Wuliangsuhai Lake plays an important role in maintaining the ecological balance of the region, protecting the local species diversity and maintaining agricultural development. However, it is also facing a greater risk of water quality deterioration. The 24 water quality factors that this study focused on were analyzed in water samples collected during the irrigation period and non-irrigation period from 19 different sites in Wuliangsuhai Lake, Inner Mongolia, China. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted to evaluate complex water quality data and to explore the sources of pollution. The results showed that, during the irrigation period, sites in the middle part of the lake (clusters 1 and 3) had higher pollution levels due to receiving most of the agricultural and some industrial wastewater from the Hetao irrigation area. During the non-irrigation period, the distribution of the comprehensive pollution index was the opposite of that seen during the irrigation period, and the degree of pollutant index was reduced significantly. Thus, run-off from the Hetao irrigation area is likely to be the main source of pollution.

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Characterizing water quality monitoring visualization with Hadoop and Google Maps

Water Practice & Technology ◽

10.2166/wpt.2017.093 ◽

2017 ◽

Vol 12 (4) ◽

pp. 882-893 ◽

Cited By ~ 1

Author(s):

Weijian Huang ◽

Xinfei Zhao ◽

Yuanbin Han ◽

Wei Du ◽

Yao Cheng

Keyword(s):

Water Quality ◽

Water Environment ◽

Large Data ◽

Water Quality Monitoring ◽

Quality Monitoring ◽

Quality Data ◽

Data Sets ◽

Google Maps ◽

Water Quality Data ◽

Computer Clusters

Abstract In water quality monitoring, the complexity and abstraction of water environment data make it difficult for staff to monitor the data efficiently and intuitively. Visualization of water quality data is an important part of the monitoring and analysis of water quality. Because water quality data have geographic features, their visualization can be realized using maps, which not only provide intuitive visualization, but also reflect the relationship between water quality and geographical position. For this study, the heat map provided by Google Maps was used for water quality data visualization. However, as the amount of data increases, the computational efficiency of traditional development models cannot meet the computing task needs quickly. Effective storage, extraction and analysis of large water data sets becomes a problem that needs urgent solution. Hadoop is an open source software framework running on computer clusters that can store and process large data sets efficiently, and it was used in this study to store and process water quality data. Through reasonable analysis and experiment, an efficient and convenient information platform can be provided for water quality monitoring.

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PERANCANGAN SISTEM BASIS DATA ONLINE MONITORING KUALITAS AIR DI SUNGAI CILIWUNG

Jurnal Air Indonesia ◽

10.29122/jai.v9i1.2475 ◽

2018 ◽

Vol 9 (1) ◽

Author(s):

Satmoko Yudo

Keyword(s):

Water Quality ◽

Online Monitoring ◽

Water Quality Monitoring ◽

River Pollution ◽

Database Management System ◽

Quality Data ◽

Water Quality Data ◽

Quality Of Water ◽

The Government

Population growth in the Jakarta city that continues to rise each year, this has resulted in environmental pollution, especially pollution of the Ciliwung river continues to grow. Nowadays various attempts have been made in terms of prevention of pollution of the river Ciliwung. One of the efforts to control pollution in the river Ciliwung is monitoring the quality of water in rivers and creeks Ciliwung. This monitoring is done in real-time and online, where the water quality data sent to data centers and analyzed into information that can be displayed at any time and anywhere through the Internet. If there are pollutants that enter the river so heavilly polluted in certain time, the government or the authorities that manages the river can take action to control pollution. To support online monitoring system running well required database management system (DBMS) for storing water quality data at any time and integrated well. Keywords : river pollution, water quality monitoring online, Ciliwung river, design database.

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