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<p>As urbanization accelerates and environmental protection standards rise, wastewater treatment plants (WWTPs) urgently need to enhance wastewater treatment efficiency (WWTE). Within the framework of Industry 4.0, technologies such as real-time monitoring, the Internet of Things (IoT), and intelligent scheduling have marked significant advancements in wastewater treatment. Nonetheless, the precise mechanisms through which these digital intelligence technologies (DITs) bolster WWTE remain largely uncharted. This study endeavors to demystify the intelligent pathways that driving WWTE, focusing on the effective integration of DITs. Key highlights include: (i) Twelve emerging DITs and seven key drivers contributing to WWTE enhancement are identified through literature review and expert interviews. (ii) A novel DEMATEL-ISM method, improved by Grey theory and the OTSU algorithm, explores the significance and interrelationships of these factors. (iii) DITs indirectly enhance WWTE by fostering organizational robustness, flexibility, and technical intelligence. (iv) The synergy between proactive deployment and automated status assessment is identified as crucial for WWTE. (v) Four intelligent pathways are proposed for driving WWTE across varied scenarios, offering strategic insights for WWTP managers. These findings provide a framework for WWTP managers to strategically integrate DITs, driving significant improvements in WWTE.</p> Graphical Abstract <p></p>

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Intelligent pathways for driving wastewater treatment efficiency: an integrated analysis approach

  • 期刊论文

  • 发表日期：

    2025年5月17日

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  • Lugang Yu,
  • Dezhi Li,
  • Jinbo Song,
  • Shenghua Zhou,
  • Wentao Wang,
  • Haibo Feng

摘要

As urbanization accelerates and environmental protection standards rise, wastewater treatment plants (WWTPs) urgently need to enhance wastewater treatment efficiency (WWTE). Within the framework of Industry 4.0, technologies such as real-time monitoring, the Internet of Things (IoT), and intelligent scheduling have marked significant advancements in wastewater treatment. Nonetheless, the precise mechanisms through which these digital intelligence technologies (DITs) bolster WWTE remain largely uncharted. This study endeavors to demystify the intelligent pathways that driving WWTE, focusing on the effective integration of DITs. Key highlights include: (i) Twelve emerging DITs and seven key drivers contributing to WWTE enhancement are identified through literature review and expert interviews. (ii) A novel DEMATEL-ISM method, improved by Grey theory and the OTSU algorithm, explores the significance and interrelationships of these factors. (iii) DITs indirectly enhance WWTE by fostering organizational robustness, flexibility, and technical intelligence. (iv) The synergy between proactive deployment and automated status assessment is identified as crucial for WWTE. (v) Four intelligent pathways are proposed for driving WWTE across varied scenarios, offering strategic insights for WWTP managers. These findings provide a framework for WWTP managers to strategically integrate DITs, driving significant improvements in WWTE.

Graphical Abstract