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Data-driven development in the smart city: Generative design for refugee camps in Luxembourg

Author

Listed:
  • Elie Daher

    (Luxembourg Institute of Science and Technology, Luxembourg)

  • Sylvain Kubicki

    (Luxembourg Institute of Science and Technology, Luxembourg)

  • Annie Guerriero

    (Luxembourg Institute of Science and Technology, Luxembourg)

Abstract

The paper addresses computational design as a key technological asset in the development of the smart city. In particular, the research targets context-aware adaptation to usage requirements at urban fragment level. Indeed, cities’ policy makers have to take into account many factors in a development policy, such as situational, technical or human-related factors as well as anticipating future usages. Moreover, nowadays, cities are key resources to answer growing humanitarian needs in terms of sheltering and camps. Indeed these situations are increasing due to different factors related to the nature, climate change or human activities. Resilience is therefore essential at the levels of districts, cities and territories. In Luxembourg, a public program aims to develop three container villages for refugees. The objective of this work is to help policy makers and humanitarians in the optimization of the spatial design of camps. The use of parametric modeling approach enables the optimization of space layout planning. It is applied on a case study allowing policy makers to explore scenarios for the decision-making in the camp space planning.

Suggested Citation

  • Elie Daher & Sylvain Kubicki & Annie Guerriero, 2017. "Data-driven development in the smart city: Generative design for refugee camps in Luxembourg," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 4(3), pages 364-379, March.
  • Handle: RePEc:ssi:jouesi:v:4:y:2017:i:3:p:364-379
    DOI: 10.9770/jesi.2017.4.3S(11)
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    Citations

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    Cited by:

    1. Ling Yang & Jian Li & Hsiao-Tung Chang & Zhiqing Zhao & He Ma & Libin Zhou, 2023. "A Generative Urban Space Design Method Based on Shape Grammar and Urban Induction Patterns," Land, MDPI, vol. 12(6), pages 1-21, June.
    2. Zhanna A. Mingaleva & Marina Sheresheva & Matvey Oborin & Tatyana Gvarliani, 2017. "Networking of small cities to gain sustainability," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 5(1), pages 140-156, September.
    3. Elena Oleinik & Alyona Zakharova, 2019. "City: economic growth and social attractiveness issues," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(1), pages 454-470, September.

    More about this item

    Keywords

    smart city; computational design; data-driven development; parametric modeling; humanitarian need; generative alghorithm; space planning; usage requirements;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations

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