Applications of Artificial Intelligence in Building Development

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (30 July 2024) | Viewed by 10971

Special Issue Editors


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1. CIAUD, Research Centre for Architecture, Urbanism and Design, Rua Sá Nogueira, Polo Universitário do Alto da Ajuda, 1349-063 Lisbon, Portugal
2. Lisbon School of Architecture, Universidade de Lisboa, Rua Sá Nogueira, Polo Universitário do Alto da Ajuda, 1349-063 Lisbon, Portugal
Interests: bioclimatic design; passive design; sustainable architecture; building energy retrofit; building energy simulation; heritage buildings; NZEB; construction technology
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Guest Editor
Research Centre for Architecture, Urbanism and Design, University of Lisbon, Lisbon, Portugal
Interests: building physics; environmental comfort; building energy models (BEM); building energy simulation (BES); Internet of Things (IoT); digital twins (BEM + BES + IoT)
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Guest Editor
Institute of Civil Engineering, Warsaw University of Life Science, 02-787 Warszawa, Poland
Interests: architecture; construction; sustainability; interdisciplinary design; parametric design; energy saving
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Guest Editor
CIAUD, Research Centre for Architecture, Urbanism and Design, Lisbon School of Architecture, Universidade de Lisboa, 1349-063 Lisbon, Portugal
Interests: architecture; energy; computation; sustainability; building energy modeling; building information modeling; algorithmic design; parametric design; urbanism; design
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Guest Editor
Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via G. Ponzio n. 31, Milan, Italy
Interests: technology of architecture; construction systems’ innovation; sustainable building materials; eco-efficiency; environmental impact assessment; life cycle assessment; life cycle thinking; design for disassembling; design for re-manufacturing; design for reuse; embodied energy; lightweight building materials; architectural membranes; technical textiles for buildings
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Special Issue Information

Dear Colleagues,

In a world powered by artificial intelligence (AI), urban planning, neighbourhood revitalisation, tactical urbanism, community-led initiatives, transit-oriented development (TOD), green infrastructure, historic preservation districts, pocket parks, complete streets, micro-mobility solutions, local business support, and city management are undergoing a transformative revolution. Cities are increasingly becoming more efficient, sustainable, and liveable.

AI empowers urban managers and policymakers, equipping them with data-driven insights from extensive datasets encompassing all facets of a city's comprehensive societal ecosystem, ranging from traffic patterns to the demographics of community well-being. This augmented understanding enables the optimisation of land utilisation, implementation of sustainable practices, and improved resource management, ultimately fostering the development of resilient and thriving cities.

AI is an indispensable ally in today's architectural, engineering, and construction landscape, providing transformative support across the entire building lifecycle. From design to decommissioning, AI enhances architectural design, streamlines construction operations, optimises energy efficiency and occupant comfort, proactively maintains systems, and guides sustainable decommissioning. This comprehensive AI integration ensures buildings stay dynamic, efficient, and sustainable throughout their entire lifecycle.

AI aids architects in creating visually appealing and structurally sound designs, streamlines construction operations, enhances safety, and improves efficiency. As buildings enter their operational phase, AI ensures energy efficiency and occupant comfort. Predictive analytics prevent disruptions during maintenance and decommissioning, and AI guides sustainable strategies. This comprehensive AI support empowers professionals to deliver aesthetically pleasing, structurally robust, efficient, sustainable, and cost-effective buildings from inception to retirement.

This Special Issue explores AI's profound impact on urban development, city planning, building design, construction, maintenance, and energy efficiency. It offers a glimpse into a future wherein AI guides us towards more sustainable, efficient, and remarkable cities and structures.

The proposed Special Issue addresses the following research fields:

  1. AI in architectural design;
  2. AI-powered engineering solutions;
  3. Construction industry advancements with AI;
  4. Sustainable building design with AI;
  5. Structural engineering and AI;
  6. AI-assisted building construction;
  7. Building maintenance automation with AI;
  8. AI in infrastructure planning;
  9. Urban development with AI-driven construction;
  10. Resource optimisation in civil engineering with AI;
  11. AI for sustainable building practices;
  12. Reducing GHG emissions through AI-enhanced energy efficiency.

Dr. Carlos C. Duarte
Dr. Nuno D. Cortiços
Dr. Anna Stefańska
Dr. Daniel Mateus
Dr. Carol Monticelli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • smart buildings
  • smart urban grids
  • adaptive design
  • RES systems
  • building automation and maintenance
  • machine learning
  • smart construction
  • sustainable design

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Related Special Issue

Published Papers (2 papers)

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Research

14 pages, 260 KiB  
Article
Embracing Artificial Intelligence (AI) in Architectural Education: A Step towards Sustainable Practice?
by Dragan Komatina, Mirjana Miletić and Marija Mosurović Ružičić
Buildings 2024, 14(8), 2578; https://doi.org/10.3390/buildings14082578 - 21 Aug 2024
Cited by 1 | Viewed by 4070
Abstract
This study explores the impact of artificial intelligence (AI) on the behavior and knowledge of final-year architectural students in Serbia and Montenegro. It aims to describe how students approach sustainability in architecture and their use of AI tools within this context. The primary [...] Read more.
This study explores the impact of artificial intelligence (AI) on the behavior and knowledge of final-year architectural students in Serbia and Montenegro. It aims to describe how students approach sustainability in architecture and their use of AI tools within this context. The primary objective is to analyze how AI affects students’ understanding of sustainable architecture indicators and how sustainability challenges and concerns influence AI applications. Using a comparative analysis approach across the two countries, this research employs surveys to test various hypotheses regarding the effects of AI on students’ perceptions of sustainability and their use of AI to achieve sustainable outcomes. The findings highlight a significant relationship between students’ knowledge of sustainability and their use of AI, revealing different influencing factors. These insights are essential for predicting future AI usage in architectural practice and provide a theoretical foundation for assumptions about sustainability in architecture. This study’s findings offer valuable guidance for refining curricula at the universities involved, aiming to enhance the integration of AI and sustainability in architectural education. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Building Development)
26 pages, 14920 KiB  
Article
Enhancing Architectural Education through Artificial Intelligence: A Case Study of an AI-Assisted Architectural Programming and Design Course
by Shitao Jin, Huijun Tu, Jiangfeng Li, Yuwei Fang, Zhang Qu, Fan Xu, Kun Liu and Yiquan Lin
Buildings 2024, 14(6), 1613; https://doi.org/10.3390/buildings14061613 - 1 Jun 2024
Cited by 7 | Viewed by 5860
Abstract
This study addresses the current lack of research on the effectiveness assessment of Artificial Intelligence (AI) technology in architectural education. Our aim is to evaluate the impact of AI-assisted architectural teaching on student learning. To achieve this, we developed an AI-embedded teaching model. [...] Read more.
This study addresses the current lack of research on the effectiveness assessment of Artificial Intelligence (AI) technology in architectural education. Our aim is to evaluate the impact of AI-assisted architectural teaching on student learning. To achieve this, we developed an AI-embedded teaching model. A total of 24 students from different countries participated in this 9-week course, completing a comprehensive analysis of architectural programming and design using AI technologies. This study conducted questionnaire surveys with students at both midterm and final stages of the course, followed by structured interviews after the course completion, to explore the effectiveness and application status of the teaching model. The results indicate that the AI-embedded teaching model positively and effectively influenced student learning. The “innovative capability” and “work efficiency” of AI technologies were identified as key factors affecting the effectiveness of the teaching model. Furthermore, the study revealed a close integration of AI technologies with architectural programming but identified challenges in the uncontrollable expression of architectural design outcomes. Student utilization of AI technologies appeared fragmented, lacking a systematic approach. Lastly, the study provides targeted optimization suggestions based on the current application status of AI technologies among students. This research offers theoretical and practical support for the further integration of AI technologies in architectural education. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Building Development)
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