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Decision-making desktop software and mobile app for wastewater treatment: selection of experimental parameters to estimate hydrogen peroxide production

Author

Listed:
  • Mário Mollo Neto

    (São Paulo State University (UNESP))

  • Mariana Matulovic

    (São Paulo State University (UNESP))

  • Ana Karollina M. Novaes

    (São Paulo State University (UNESP))

  • Livia V. Sanches

    (São Paulo State University (UNESP))

  • Juliane C. Forti

    (São Paulo State University (UNESP))

Abstract

In a decade marked by 4.0 technologies, using some of them for the optimization of effluent treatment processes is one of the objectives of the current researchers in this area. In this paper, we present two models as a fuzzy rule-based expert system, utilized in a computer desktop platform “Peroxide 1.0” and a mobile app “Peroxide App.” The objective is to select the best experimental parameters-electrodes type and potential-for the maximization of hydrogen peroxide (H2O2) electrogeneration. In situ H2O2 generation has as an auxiliary function to be used in the advanced oxidative processes for the degradation of persistent organic pollutants and emerging contaminants, which are not treated by traditional chemical and biological processes. For the construction of the proposed software in this study, the data were initially correlated using the MATLAB® platform Fuzzy toolbox, and the expert knowledge and literature were associated by a desktop and mobile knowledge system that weighs the variables according to their impact on the electrogeneration productivity. The desktop end-user interface was coded using Microsoft Visual Studio Rapid Application Development, and the mobile app was developed on the Android platform similar to Peroxide 1.0, adopting the specifics and particularity of the programming system. The developed systems were validated in different laboratory scenarios, and their performance were considered satisfactory, in agreement with the literature. Therefore, it is concluded that the Peroxide 1.0 and Peroxide App models can be a significant contribution to and advance the improvement in the processes for all types of industries that generate chemical effluents and require their treatment based on oxidative processes that use H2O2.

Suggested Citation

  • Mário Mollo Neto & Mariana Matulovic & Ana Karollina M. Novaes & Livia V. Sanches & Juliane C. Forti, 2022. "Decision-making desktop software and mobile app for wastewater treatment: selection of experimental parameters to estimate hydrogen peroxide production," Environment Systems and Decisions, Springer, vol. 42(2), pages 295-305, June.
    • Handle: RePEc:spr:envsyd:v:42:y:2022:i:2:d:10.1007_s10669-022-09850-6
    DOI: 10.1007/s10669-022-09850-6
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    References listed on IDEAS

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    1. Dejian Yu & Zeshui Xu & Wanru Wang, 2019. "A bibliometric analysis of Fuzzy Optimization and Decision Making (2002–2017)," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 371-397, September.
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