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Optimizing the Spatial Organization of Refugee Camps in Jordan Through Artificial Intelligence
Refugee camps are defined by the United Nations High Commissioner for Refugees (UNHCR) as “temporary facilities built to provide immediate protection and assistance to people who have been forced to flee their homes due to war, persecution, or violence”. The average lifespan of a refugee camp is seventeen years after which they organically transition into new towns. This is evident in Jordan, the country housing the majority of refugees since 1947. Daily practices by refugees subvert the initial planned camp into organic formations suitable for their changing needs, overriding the rigid built environment which no longer serves them. Addressing SDGs number 10: Reduced Inequalities, 11: Sustainable Cities and Communities, and 17: Partnerships of change, this ongoing research assesses the potential of artificial intelligence models to identify morphological patterns in the built environment and understand transient scenarios of a refugee camp’s spatial organization through an iterative process. By understanding patterns of spatial change, the inevitable transition from temporary to permanent settlement can be guided away from “slummification” towards creating adequate low-income housing for refugees in Jordan.
Optimizing the Spatial Organization of Refugee Camps in Jordan Through Artificial Intelligence
Refugee camps are defined by the United Nations High Commissioner for Refugees (UNHCR) as “temporary facilities built to provide immediate protection and assistance to people who have been forced to flee their homes due to war, persecution, or violence”. The average lifespan of a refugee camp is seventeen years after which they organically transition into new towns. This is evident in Jordan, the country housing the majority of refugees since 1947. Daily practices by refugees subvert the initial planned camp into organic formations suitable for their changing needs, overriding the rigid built environment which no longer serves them. Addressing SDGs number 10: Reduced Inequalities, 11: Sustainable Cities and Communities, and 17: Partnerships of change, this ongoing research assesses the potential of artificial intelligence models to identify morphological patterns in the built environment and understand transient scenarios of a refugee camp’s spatial organization through an iterative process. By understanding patterns of spatial change, the inevitable transition from temporary to permanent settlement can be guided away from “slummification” towards creating adequate low-income housing for refugees in Jordan.
Optimizing the Spatial Organization of Refugee Camps in Jordan Through Artificial Intelligence
Sustainable Development Goals Series
Rubbo, Anna (Herausgeber:in) / Du, Juan (Herausgeber:in) / Thomsen, Mette Ramsgaard (Herausgeber:in) / Tamke, Martin (Herausgeber:in) / Marji, Noor (Autor:in) / Kohout, Michal (Autor:in)
World Congress of Architects ; 2023 ; Copenhagen, Denmark
20.09.2023
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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