1 Department of Architecture, College of Environmental Sciences, Joseph Ayo Babalola University, Osun State, Nigeria.
2 Department of Architecture, Faculty of Environmental Studies, University of Nigeria, Nsukka, Enugu, Nigeria.
3 Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, India.
4 School of Environmental, Architectural Department, Lagos State University of Technology, Lagos, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(03), 2487-2498
Received on 14 November 2024; revised on 22 December 2024; accepted on 25 December 2024
The intersection of artificial intelligence and architectural design represents a significant technological advancement that fundamentally reshapes spatial creation and design methodologies. This research explores how computational approaches, specifically machine learning and parametric design algorithms, are transforming architectural practice by introducing novel capabilities for spatial exploration, performance optimization, and generative design.
Artificial intelligence emerges as a collaborative tool that expands architectural design possibilities. Advanced neural networks and generative design algorithms enable computational systems to analyze extensive datasets, generate complex design iterations, and optimize architectural solutions across multiple dimensions of structural integrity, environmental performance, and contextual responsiveness.
Empirical evidence from case studies of sustainable urban housing in Singapore and adaptive architectural systems in Madrid illustrates how computational technologies can produce design solutions that surpass traditional methodologies, addressing critical challenges in environmental sustainability and urban resilience.
The research critically examines the technological capabilities and limitations of AI in architectural design. It highlights the potential for algorithmic bias, challenges in capturing phenomenological experiences, and ethical considerations surrounding creative agency. By emphasizing the need for interdisciplinary collaboration and robust ethical frameworks, the study provides a nuanced approach that balances human intuition with technological innovation.
Parametric Design; Computational Intelligence; Generative Algorithms; Architectural Innovation; Machine Learning; Contextual Responsiveness
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Temitope Sunday Adeusi, Onah Louis Kachiside, Rajat Gupta and Ibrahim Musa Oyewole. Innovative architectural design practices enabled by AI-powered parametric and computational approaches. World Journal of Advanced Research and Reviews, 2024, 24(3), 2487-2498. Article DOI: https://doi.org/10.30574/wjarr.2024.24.3.3959