Towards a well-being-oriented framework for urban digital twins

Bibliographic Data

ID6419772
AuthorsUrva Rajnikant Patel (Auckland University of Technology, corresponding author), Amirhosein Ghaffarianhoseini (0000-0002-3189-0566, Auckland University of Technology), Ali Ghaffarianhoseini (0000-0002-0787-8399, Auckland University of Technology), Andrew Burge, Andrew Burgess (0000-0001-9270-2939, Auckland University of Technology)
Year2025
Volume169
Pages106579-106579
Publication date2025-10-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCities (JOURNAL)
Journal identifiersISSN: 0264-2751 • E-ISSN: 1873-6084
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.cities.2025.106579
OpenAlexW4415439200
LanguageEN
Citations received1
References cited39

Urban well-being is gaining prominence as a critical pillar of sustainable development practice and urban planning; however, digital twin technology continues to focus predominantly on physical infrastructure. This paper introduces an exploratory conceptual framework for incorporating urban well-being indicators into urban digital twin platforms, utilizing New Zealand's Living Standards Framework (LSF) and adopting a policy-oriented approach to selecting well-being indicators. Through consultation with experts and a literature review, we identified six policy-relevant proxies: carbon emissions, drinking water quality, road fatalities, crime rates, work commute times, and internet access, which reflect the environmental, social, and economic dimensions of well-being. Historical data from 2017 to 2023 was operationalised in a Python-based analytical dashboard, which generates descriptive statistics, benchmarks, correlations, and Autoregressive Integrated Moving Average (ARIMA) forecasts. The study also assessed the technical feasibility of urban well-being indicators using publicly available open-source digital twin platforms such as Eclipse Ditto and FIWARE. The results indicate that integration is technically feasible; however, they are constrained by schema incompatibilities, limited native analytics capabilities, and questions of scalability regarding how proxies relate to urban well-being. As a proof-of-concept study, it explored how digital twin technology could be reshaped to support holistic, citizen-oriented objectives for well-being and complement participatory and multi-criteria approaches. • Introduces a framework to embed well-being indicators in urban digital twins. • Uses New Zealand's Living Standards Framework for indicator selection. • Develops a Python dashboard with descriptive, correlation, and ARIMA analyses. • Tests feasibility with Eclipse Ditto and FIWARE open-source DT platforms. • Proposes a hybrid architecture linking socio-economic data with DT systems.

Analytics · Autoregressive integrated moving average · Cloud computing · Conceptual framework · Information and Communications Technology · Python (programming language) · Sustainability · The Internet · Urban planning · Digital Transformation in Industry · Smart Cities and Technologies

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Open DOIOpen Access