AI in Architecture and Urban Design and Planning: Case studies on three AI applications

Sajjad Naseri *

Department of Civil, Chemical, Environmental, and Materials Engineering – DICAM, Alma Mater Studiorum - Università di Bologna, Italy.
 
Research Article
GSC Advanced Research and Reviews, 2024, 21(02), 565–577.
Article DOI: 10.30574/gscarr.2024.21.2.0463
Publication history: 
Received on 17 October 2024; revised on 26 November 2024; accepted on 28 November 2024
 
Abstract: 
The use of artificial intelligence (AI) in the built environment is changing traditional methods by improving sustainability, efficiency, and innovation. This study examines the positive and negative aspects of adopting three AI technologies to improve design and planning processes: PlanFinder, TestFit, and Luma. PlanFinder's ability to generate multiple options for design in just a couple of seconds benefits both professional and beginner designers which is speeding up the creation of building designs. TestFit simplifies urban planning by swiftly generating site designs that consider cost and zoning which is allowing urban planners and real estate developers to make informed decisions. Luma enables the creation of realistic 3D animations from a simple models to enhance project visualization and presentation quality.
While these technologies provide major benefits to save time, lowering down costs, and allowing for greater experimentation, they also have drawbacks. These include dependency on accurate data, limited modification choices and potential compatibility issues with complex projects. Furthermore, the use of AI brings questions regarding the ethical implications of technology and its impact on the labor force. This study offers a helpful perspective for educators, architects, urban planners and designers considering using AI into their work.
 
Keywords: 
Architecture; Artificial Intelligence; Sustainability; Urban Design; Urban Planning
 
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