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A Data-Driven Framework for Smart Urban Domestic Wastewater: A Sustainability Perspective

Auteur(s):


Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2019
Page(s): 1-15
DOI: 10.1155/2019/6530626
Abstrait:

With the continuous advancement of urbanization, the problem of urban domestic wastewater has become increasingly serious. Furthermore, information and communication technologies (ICTs) have flourished, providing smart ideas for the governance of urban problems, including smart urban domestic wastewater (SUDW), to improve efficiency and deliver smart cities. The framework of smart governance is vital for urban planning and development, but existing frameworks lack systematic characteristics. Therefore, this study aimed to systematically analyze the functions that SUDW can achieve from a sustainability perspective and to construct a framework of SUDW. This paper articulated the objectives of SUDW from the perspectives of service providers (mainly wastewater treatment plants, WWTPs), government, and public based on the goals of smart cities and sustainable development. Moreover, seven functions of SUDW were identified based on systematic literature analysis, such as the automation of WWTPs and operation and maintenance of sewer assets. Then, the information needed for the above functions was analyzed to clarify communication between the main stakeholders and functions, which were illustrated by an information chain model. The functions are interrelated and closely related to sustainable development, where information sharing is the foundation and key component. Based on the above analyses, a data-driven framework of SUDW consisting of five layers was proposed. The paper indicated that the core of SUDW is the perception, transmission, storage, analysis, and application of relevant data. The study not only contributes to the body of knowledge relating to smart cities but can also guide the planning of cities to realize SUDW, smart cities, and sustainable development.

Copyright: © 2019 Jing Du et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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  • Reference-ID
    10377616
  • Publié(e) le:
    05.11.2019
  • Modifié(e) le:
    05.11.2019