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Adaptive design of traditional residential buildings based on digital intelligence system under self-organization theory
Author(s)
Gan, Xin
Na Ayudhya, Thirayu Jumsai
Date Issued
January 1, 2024
Type
Article
Abstract
Adaptive design of traditional residential buildings that change in response to their surroundings, occupants, and things, as well as those that rely only on internal information, are the focus of adaptable construction, a multifaceted field. The primary problem with architectural design is the disparity between control and execution regarding cost comparisons. Another issue is that it is impossible to anticipate humans or conventional computer programs to analyze big datasets and identify trends using rule-driven approaches. The article proposed a Digital intelligence-based adaptive design of residential buildings under self-organization theory (DI-RB-SOT) for residential structures throughout their lifecycle, including conceptual, design, construction, operational, and maintenance stages. The DI simulate various design possibilities and estimates their impact on the structure's productivity, convenience, and security using data on the building's use, arrangement, operations, and environment. A crucial phase in the design process is using Artificial Intelligence (AI) algorithms to sift through this heap of data in search of trends and patterns. These models would assess potential improvements to the building's performance, user comfort, energy efficiency, and alternative design possibilities. The research examines the inner workings and motivating reasons underlying the emergence of home adaptive design by using self-organization theory as a framework. The study confirms the usefulness of Graph Converter generative adversarial network (GCGAN) computational models that facilitate the development of intelligent building design elements, which in turn permit the establishment of intelligent structures based on Digital intelligence. Managers and practitioners may be able to use solutions involving proactive thinking, improved efficiency, self-management, and satisfaction in residential buildings as a result of this work.
Citation
Pakistan Journal of Life and Social Sciences, 22(2), 5188-5202, 2024