Artificial Intelligence for the Construction Industry - A Statistical Descriptive Analysis of Drivers and Barriers

Cisterna, Diego; Seibel, Simon; Oprach, Svenja; Haghsheno, Shervin

doi:10.1007/978-3-030-87687-6_27

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…AI-based document processing is used to scan and interpret documents, extracting the key data points that are needed for further analysis. (Cisterna, Seibel, et al, 2022) Optical Character Recognition (OCR) and Natural Language Processing (NLP) are two AI technologies that could have a substantial impact in the construction sector (Locatelli et al, 2021;Wolber et al 2021). OCR technology enables the conversion of scanned or digital images into text that is machine-readable, enabling the automation of human data entry and the digitalization of paper-based operations (Hamad & Kaya, 2016).…”

Section: Use Of Ai In Construction To Extract Information From Documentsmentioning

confidence: 99%

Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry

Martinez¹,

Cisterna²

2023

Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)

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Low-code is a new technology paradigm used to support digitalization in different industries. Nevertheless, there are no studies analyzing the implications of this technology in the construction industry context. Through action research, this paper explores the potential of lowcode to support continuous improvement of construction processes. The authors present the development and implementation of a low-code/artificial intelligence (AI)-based solution to automate data processing from paper delivery notes on-site. The as-is process was measured and compared against the low-code/AI powered process to verify efficiency gains. The development process of the digital solution was also analyzed to derive the findings of the study. The implementation of the digital solution resulted in 78% process time savings. The study also reveals the importance of involving people closer to operations in the development process, which resulted in efficient elicitation of requirements and the delivery of a solution meeting the needs of the end users. This paper highlights the potential of low-code productive development practices to support the digitalization in the construction industry. It also enlightens areas for further research and encourages the development of additional case studies to provide evidence of the benefits and limitations of using low-code to support continuous improvement in the construction industry.

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Section: Use Of Ai In Construction To Extract Information From Documentsmentioning

confidence: 99%

Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry

Martinez¹,

Cisterna²

2023

Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)

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“…Additionally, some studies focused on specific Construction 4.0 technologies and discovered implementation difficulties. For examples, low level of employee training and education, lack of expertise and experience transfer, lack of corresponding legislation for implementing Building Information Technology (BIM) (Mazurchenko and Zelenka, 2022); shortage of specialized workers, insufficient system and data security and high investment costs for implementing Artificial Intelligence (AI) (Cisterna et al, 2021); lack of skills and knowledge, markets risks, high energy consumption, the vulnerability of smart contracts and authorization issues for implementing block chain technology (Akinradewo et al, 2022) and; data security issues, data access restrictions, change resistance, distracted workers, skills and training issues for implementing Mobile Information and Communication Technology (M-ICT) (Atkinson et al, 2022) were identified as major challenges.…”

Section: Research Topic Within the Domainmentioning

confidence: 99%

Mastering the skills of Construction 4.0: a review of the literature using science mapping

Siriwardhana

Moehler

2023

SASBE

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PurposeSkills development among construction stakeholders has become an increasingly urgent necessity for the successful implementation of Construction 4.0 in recent years. There is a lack of comprehensive analysis on the domain of Construction 4.0 implementation, with a focus on skills development. This study aims to address this gap through the use of the science mapping approach to show the gaps of research domain and propose future directions.Design/methodology/approachThis study adopted a three-step holistic review approach, comprising bibliometric review, scientometric analysis, and qualitative discussion, to obtain a comprehensive overview of research in the field of Construction 4.0 skills development. f on a total of 57 articles published in three databases, the influential sources, keywords, scholars, and articles in the domain were analysed. A follow-up discussion aimed to identify main-stream research topics, research gaps, and future research directions.FindingsFindings discovered that the topics were concerned about Construction 4.0 whilst skills development aspect was lacking in creation of policies, frameworks, strategies in different contexts. The study revealed research gaps such as presence of skills gaps and shortages in some countries, the lack of frameworks and roadmaps for successful Construction 4.0 implementation, and the lack of readiness assessments from professional, company and industry viewpoints.Originality/valueThis study contributes to the knowledge in the domain of Construction 4.0 and the contribution of skills development for its implementation and a comprehensive overview with research gaps and future research directions in the domain.

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Artificial Intelligence for the Construction Industry - A Statistical Descriptive Analysis of Drivers and Barriers

Cited by 2 publications

References 12 publications

Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry

Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry

Mastering the skills of Construction 4.0: a review of the literature using science mapping

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