• Urban Scale Digital Twins Vis-à-Vis Complex Phenomena: Datafication and Social and Environmental Equity

    Author(s):
    Marianna Charitonidou (see profile)
    Date:
    2023
    Item Type:
    Conference paper
    Conf. Title:
    Digital Design Reconsidered, Proceedings of the 41st eCAADe conference
    Conf. Org.:
    Graz University of Technology
    Conf. Loc.:
    Graz, Austria
    Conf. Date:
    20-22 September 2023
    Permanent URL:
    https://doi.org/10.17613/8ebv-wq50
    Abstract:
    The paper analyses the role of the urban scale digital twins in conceiving and designing urban spaces. Urban scale digital twins are virtual replicas of cities. Within the current context of data-driven societies, they are often used to test scenarios related to sustainable environmental design. An important reorientation concerning the role of the urban scale digital twins in urban planning is that from technical to the socio-technical perspectives. The debates on Smart Cities often focus on technical issues, neglecting the social issues concerning urban planning. At the core of the paper is the idea that in order to combine environmental equity and social equity, it is pivotal to bring together the social and the technical viewpoints of urban planning. This can become possible through the adoption of socio-technical perspectives. The paper explores the role of complexity perspectives based on new types of urban data in reshaping urban planning decision making methods. It pays special attention to datafication, Smart Cities, digital exclusion, Big Data, IoT, AI, Machine Learning, automated data collection, and data analytics. It also investigates how urban scale digital twins can measure, describe and analyze complex phenomena. Particular emphasis is placed on how urban scale digital twins help develop new data driven scenarios, promote sustainable development goals, and shape new participatory design methods. At the center of the paper are the following main characteristics of urban scale digital twins: firstly, their ‘scalability’; secondly, their ‘predictability’, which becomes possible thanks to the use of simulation algorithms; thirdly, their capacity to integrate new elements thanks to the use of IoT sensors, and data undated concerning in situ real-time data, and, finally, their capacity to enhance cooperation due to the fact that they can be broadly accessible.
    Metadata:
    Published as:
    Conference proceeding    
    Status:
    Published
    Last Updated:
    5 months ago
    License:
    Attribution

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