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Showing 2 results for Ai (artificial Intelligence)
Volume 5, Issue 2 (8-2024)
Abstract
Aims: Today, the use of artificial intelligence has grown significantly, and is developing as a new field. The main goal of this research is to know the capabilities of artificial intelligence in advancing the design and implementation process in the artificial environment. The practical goal of research is the development and application of the most important achievements of machine learning in the field of design.
Methods: The main research method is "meta-analysis" research in the paradigm of "free research" with a critical approach and basic design, which examines the general knowledge field of this field using broad techniques. Then, to consolidate the literature on the topic, through searching three reliable knowledge bases of this field, we collected articles related to machine learning in the fields of unsupervised learning methods, semi-supervised learning, and reinforcement learning; The most important capacities and shortcomings, and strengths and weaknesses are reviewed.
Findings: Quantitative findings from the combined data indicate that supervised machine learning and directed deep learning can be the best option to recommend in the future of design. While the learning process in deep learning is gradual and slower, supervised machine learning works faster in the testing phase.
Conclusion: The research emphasizes that supervised machine learning is the best option for predicting answers in the design process. But if, in addition to prediction, the issue of creativity in design is desired, deep learning is more efficient.
Paria Taheri, Maryam Rasoolzadeh,
Volume 15, Issue 2 (7-2025)
Abstract
Aims: The development of AI tools in interior architecture has brought both opportunities and challenges. The primary objective of this research is to highlight the weaknesses and shortcomings in the professional application of artificial intelligence-based tools in interior architecture. The second objective is to introduce and explain the role of agent-based systems in enhancing the efficiency of artificial intelligence tools in interior architecture.
Methods: This research employs a descriptive-analytical method as its primary approach. In the descriptive phase, data were collected from existing sources to examine the impact of artificial intelligence on the interior design process. Subsequently, a questionnaire was designed to gather designers' opinions regarding the influence of artificial intelligence on interior architecture and the role of designers. The collected data were then statistically analyzed using SPSS.
Findings: More than 80% of the surveyed interior architects were familiar with artificial intelligence tools, with most identifying Midjourney as a key tool that reduces time and increases efficiency. The most significant challenges identified pertain to the healthy building domain, particularly in relation to indoor air quality, environmentally friendly materials, and the comfort and ergonomics of spaces.
Conclusion: The qualitative findings of this research indicate that agent-based systems play a crucial role in enhancing the efficiency of artificial intelligence tools in the interior architecture process. This is particularly important in the healthy building domain, as it provides a comprehensive model for understanding the interaction between Bauphysik, Bauchemie, Baubiologie, environmentally friendly materials, and occupant health.
