Article
Challenges of Data Refining Process during the Artificial
Intelligence Development Projects in the Architecture,
Engineering and Construction Industry
Seokjae Heo, Sehee Han , Yoonsoo Shin and Seunguk Na *
Citation: Heo, S.; Han, S.; Shin, Y.;
Na, S. Challenges of Data Refining
Process during the Artificial
Intelligence Development Projects in
the Architecture, Engineering and
Construction Industry. Appl. Sci. 2021,
11, 10919. https://doi.org/10.3390/
app112210919
Academic Editors: Nikos D. Lagaros
and Vagelis Plevris
Received: 30 October 2021
Accepted: 15 November 2021
Published: 18 November 2021
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4.0/).
Department of Architectural Engineering, College of Engineering, Dankook University, 152 Jukjeon-ro,
Yongins-si 16890, Gyeonggi-do, Korea; mill@dankook.ac.kr (S.H.); edu.hansh@gmail.com (S.H.);
shinys@dankook.ac.kr (Y.S.)
* Correspondence: drseunguk@dankook.ac.kr; Tel.: +82-31-8005-3727
Abstract:
The paper examines that many human resources are needed on the research and develop-
ment (R&D) process of artificial intelligence (AI) and discusses factors to consider on the current
method of development. Labor division of a few managers and numerous ordinary workers as a form
of light industry appears to be a plausible method of enhancing the efficiency of AI R&D projects.
Thus, the research team regards the development process of AI, which maximizes production effi-
ciency by handling digital resources named ‘data’ with mechanical equipment called ‘computers’, as
the digital light industry of the fourth industrial era. As experienced during the previous Industrial
Revolution, if human resources are efficiently distributed and utilized, no less progress than that
observed in the second Industrial Revolution can be expected in the digital light industry, and human
resource development for this is considered urgent. Based on current AI R&D projects, this study
conducted a detailed analysis of necessary tasks for each AI learning step and investigated the
urgency of R&D human resource training. If human resources are educated and trained, this could
lead to specialized development, and new value creation in the AI era can be expected.
Keywords:
digital light industry; fourth Industrial Revolution; artificial intelligence; human resource
development; work index; architecture; engineering and construction industry
1. Introduction
For half a century, entrepreneurs of South Korea have transformed the originally
agriculture-focused country into one with a focus on light and heavy industries, and fol-
lowing the third Industrial Revolution era, South Korea gained a state-of-the-art electronic
industry. Furthermore, some South Korean corporate companies that emerged after the
2000s are now top ranking on the global scale. Not only have they established artificial
intelligence (AI) research and development (R&D) centers, but they have also aggressively
developed professional human resources in order to become global leading companies in
the fourth Industrial Revolution era. Notably, amongst construction and transportation
industries, the AI-based indoor mapping and positioning technologies developed by Naver
Labs are acknowledged as top-tier technologies [
1
], and KAKAO BRAIN has developed
a technology that allows world-class performance of learning of images without the im-
age labeling process [
2
,
3
]. According to King et al. [
4
], AI will soon be applied to all the
industrial sectors around the globe at a fast pace.
The South Korean government-initiated Data Dam project focused on digital infras-
tructure investment since the mid-2020s [
5
]. The South Korean government announced
that the Data Dam project would have a total budget of KRW 292.5 billion (equivalent to
approximately USD 252 million) for the first half of 2021 and is planning to collect the
training data from 84 areas, including vision, geographic information, healthcare, and
construction. The aim of this project is to enable research institutes and private companies
Appl. Sci. 2021, 11, 10919. https://doi.org/10.3390/app112210919 https://www.mdpi.com/journal/applsci
