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  • Open Access

    ARTICLE

    Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

    Wenwu Tan1, Jianjun Zhang1,*, Xing Liu1, Jiang Wu1, Yifu Sheng1, Ke Xiao2, Li Wang2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.5, pp. 85-97, 2023, DOI:10.32604/jbd.2022.030908 - 26 December 2023

    Abstract At present, water pollution has become an important factor affecting and restricting national and regional economic development. Total phosphorus is one of the main sources of water pollution and eutrophication, so the prediction of total phosphorus in water quality has good research significance. This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform. By constructing the attribute object mapping relationship, the correlation between the two indicators was analyzed and used to predict the future data. Firstly, the monthly mean and daily mean concentrations of More >

  • Open Access

    ARTICLE

    Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

    Ziwen Yu1, Jianjun Zhang1,*, Wenwu Tan1, Ziyi Xiong1, Peilun Li1, Liangqing Meng2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.4, No.2, pp. 135-143, 2022, DOI:10.32604/jbd.2022.031024 - 31 October 2022

    Abstract Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to More >

  • Open Access

    ARTICLE

    Design and Analysis of a Water Quality Monitoring Data Service Platform

    Jianjun Zhang1,*, Yifu Sheng1, Weida Chen2, Haijun Lin1, Guang Sun3, Peng Guo4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 389-405, 2021, DOI:10.32604/cmc.2020.012384 - 30 October 2020

    Abstract Water is one of the basic resources for human survival. Water pollution monitoring and protection have been becoming a major problem for many countries all over the world. Most traditional water quality monitoring systems, however, generally focus only on water quality data collection, ignoring data analysis and data mining. In addition, some dirty data and data loss may occur due to power failures or transmission failures, further affecting data analysis and its application. In order to meet these needs, by using Internet of things, cloud computing, and big data technologies, we designed and implemented a… More >

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