Applicability of Artificial Intelligence (AI) Methods to Construction Manufacturing: A Literature Review

Hatami, Mohsen; Paneru, Suman; Flood, Ian

doi:10.1061/9780784483961.136

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…Over the past few decades, in the construction, researchers have published articles on implementing AI and its subdomains to address industry-specific challenges. These studies demonstrate AI and machine learning applications across the construction management spectrum, including safety management [12][13][14][15][16][17], cost predictions [18][19][20][21][22], schedule optimization [1,4,23,24], progress monitoring [25][26][27][28][29], quality control [30,31], supply chain management [32][33][34][35][36], logistics management [37,38], project risks management [39][40][41][42][43][44], disputes resolution [45,46], waste management [47][48][49], sustainability assessments [50][51][52][53][54], visualization [55,…”

Section: Introductionmentioning

confidence: 99%

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Ghimire,

Kim,

Acharya

2024

Buildings

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In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags in adoption. Recently, the emergence and rapid adoption of advanced large language models (LLMs) like OpenAI’s GPT, Google’s PaLM, and Meta’s Llama have shown great potential and sparked considerable global interest. However, the current surge lacks a study investigating the opportunities and challenges of implementing Generative AI (GenAI) in the construction sector, creating a critical knowledge gap for researchers and practitioners. This underlines the necessity to explore the prospects and complexities of GenAI integration. Bridging this gap is fundamental to optimizing GenAI’s early stage adoption within the construction sector. Given GenAI’s unprecedented capabilities to generate human-like content based on learning from existing content, we reflect on two guiding questions: What will the future bring for GenAI in the construction industry? What are the potential opportunities and challenges in implementing GenAI in the construction industry? This study delves into reflected perception in literature, analyzes the industry perception using programming-based word cloud and frequency analysis, and integrates authors’ opinions to answer these questions. This paper recommends a conceptual GenAI implementation framework, provides practical recommendations, summarizes future research questions, and builds foundational literature to foster subsequent research expansion in GenAI within the construction and its allied architecture and engineering domains.

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Section: Introductionmentioning

confidence: 99%

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Ghimire,

Kim,

Acharya

2024

Buildings

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Limitations for the Implementation of Artificial Intelligence in Construction Health and Safety in Ghana

Mustapha,

Kurbom Tieru,

Boahene Akomah

et al. 2024

Baltic Journal of Real Estate Economics and Construction Management

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Building accidents and fatalities are prevalent, especially in rising nations like Ghana, despite rapid technical developments. Weak regulations, training, and change resistance typically undermine traditional safety measures. This study aimed to identify potential obstacles that prevent the implementation of artificial intelligence (AI) in construction health and safety in Ghana. A survey research approach was employed to get the study population, which consisted of 110 construction experts made up of project managers, site engineers, skilled workers, and safety officers complete the questionnaire. Data analysis included descriptive statistics, chi-square, and regression. According to varied demographic responses, AI increases design and engineering, safety and security, and human resources efficiency, decision-making, and safety. Lack of innovation culture, training, and regulation harms health and safety. Using AI promises to overcome these hurdles by minimising risks, improving worker well-being, and safe work environment. The Ghanaian industry study focus and small sample size may prejudice, as the limitations of the study. Samples must be larger and more diversified to generalise. The practical implication is that Ghanaian builders may use the study’s findings. Understanding AI’s potential and limitations helps them develop AI solutions and problem-solving methodologies. Safety, cost, and worker well-being can improve. The successful integration of AI in construction health and safety can affect society. AI can reduce workplace accidents and improve productivity, well-being, and healthcare costs. This work adds to the growing body of knowledge on AI’s building safety applications in emerging economies like Ghana. It identifies environmental restrictions and enables governments, industry leaders, and researchers to develop and implement AI solutions.

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Applicability of Artificial Intelligence (AI) Methods to Construction Manufacturing: A Literature Review

Cited by 2 publications

References 25 publications

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Limitations for the Implementation of Artificial Intelligence in Construction Health and Safety in Ghana

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