Review on the Integration of Artificial Intelligence in Parametric Urban Design and Outdoor Thermal Comfort

Mohammed Lamine; Nassira BENHASSINE; Atef Ahriz

doi:10.38027/smart.v2n1-4

Authors

Mohammed Lamine Department of Architecture, Faculty of Sciences and Technology, University of Tebessa, Echahid Cheikh Larbi Tebessi, Algeria Author https://orcid.org/0009-0008-0089-2594
Nassira BENHASSINE Department of Architecture, Faculty of Architecture and Urban Planning, University of Constantine 3 Salah Boubnider, Algeria Author https://orcid.org/0000-0001-9866-8647
Atef Ahriz Department of Architecture, Faculty of Sciences and Technology, University of Tebessa, Echahid Cheikh Larbi Tebessi, Algeria Author https://orcid.org/0000-0001-5891-0275

DOI:

https://doi.org/10.38027/smart.v2n1-4

Keywords:

Universal Thermal Climate Index, Algorithmic Architecture, Urban Morphology, Generative Design, Climate-responsive cities, Machine Learning

Abstract

Artificial Intelligence (AI) is increasingly recognised for its ability to accelerate physics-based simulation tasks, making it particularly promising in urban design processes, where simulation often hinders iterative development. This review explores the intersection of AI, parametric urban design (PUD), and outdoor thermal comfort (OTC), assessed using the Universal Thermal Climate Index (UTCI) or other indices. We identify emerging methods and tools used to optimise comfort outcomes through intelligent design frameworks. By systematically analysing 40 studies from 2018 to 2025 and leveraging bibliometric analysis, the review categorises contributions into predictive modelling, generative design, parametric optimisation, and integration strategies. The limitation is the niche and novel nature of the subject, which reduces the number of eligible studies. We highlight how AI, particularly machine learning, acts as both a surrogate for environmental simulation and a driver for design generation. Although full integration of AI with parametric and comfort modelling remains limited, recent progress suggests strong potential. This paper presents a conceptual pipeline for integrating AI into PUD to support comfort optimisation, emphasising the need for open datasets, interpretable models, and design tool interoperability. This review establishes the first interdisciplinary synthesis of parametric urban design, artificial intelligence, and outdoor thermal comfort research, providing urban planners with a framework to leverage emerging technologies for climate-resilient cities. Limitations include the niche nature of AI-PUD-OTC integration (41 studies met criteria) and the lack of longitudinal validation in built projects.

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