Artificial Intelligence and Deep Learning in Civil Engineering

Ocak, Ayla; Niğdeli, Sinan Melih; Bekdaş, Gebrai̇l; Işıkdağ, Ümit

doi:10.1007/978-3-031-34728-3_13

Cited by 2 publications

(1 citation statement)

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“…Architectural design often involves complex problem-solving and critical decision-making (Ivanova et al, 2023;Ouyang et al, 2023). ChatGPT or Bard can serve as a tool for analyzing design challenges and providing insights, suggestions, and potential solutions (Singh, 2023;Dumrak and Zarghami, 2023;Ocak et al, 2023). Designers present a problem scenario, and ChatGPT offers responses considering various factors and design considerations.…”

Section: Problem Solving and Decision Supportmentioning

confidence: 99%

Integrating ChatGPT, Bard, and Leading-Edge Generative Artificial Intelligence in Architectural Design and Engineering: Applications, Framework, and Challenges

Rane,

Choudhary,

Rane

2023

IJARP

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This research paper investigates the integration of advanced generative artificial intelligence (AI) models, such as ChatGPT, Bard, and similar architectures, in architectural design and engineering. The comprehensive study explores various aspects, including applications, frameworks, challenges, and prospective developments in the context of architectural design and architectural engineering. In architectural design, the paper investigates the transformative impact on Architectural Theory, highlighting how generative AI fosters creativity and innovation in design thinking. The Design Process is scrutinized, showcasing how AI models streamline ideation, iteration, and collaboration among design teams. Furthermore, the research examines the influence of generative AI in Interior Design, Urban Design and Planning, and considers nuanced aspects of Cultural and Social factors, elucidating how these technologies contribute to inclusive and context-sensitive design practices. In architectural engineering, the study assesses the integration of generative AI in Structural Engineering, demonstrating its potential to optimize and innovate structural analysis and designs for enhanced safety and efficiency. It explores applications in Building Systems and Construction Management, illustrating how AI can streamline project workflows and resource allocation. The impact of generative AI on compliance with Building Codes and Regulations is analyzed, emphasizing its potential for error reduction and adherence to standards. Additionally, the research probes into the influence of AI in Materials and Construction Technology, highlighting advancements in material selection and construction methodologies. The paper also investigates the role of generative AI in promoting Sustainability and Environmental Design, showcasing its potential to optimize energy efficiency, reduce environmental impact, and enhance overall sustainability. Finally, the paper outlines the challenges and future directions for development to fully harness the potential of generative AI in shaping the future of architectural design and engineering.

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