The research has chosen the workers in construction-related companies in South Korea and the United Kingdom (UK) as research subjects in order to analyse factors that influence their usage intention of Artificial Intelligence (AI) based technologies. The perceived usefulness had a positive impact (+) on technological satisfaction and usage intention in terms of the commonalities shown by the construction industry workers in both countries, South Korea and the UK, in adopting AI-based technologies. Moreover, the most remarkable differences were personal competence and social influence when choosing AI-based technologies. It was analysed that in the case of South Korea, personal competence had a positive impact (+) on perceived ease of use, whereas the UK had a positive impact (+) on perceived usefulness and perceived ease of use. This study holds particular significance in the domain of cross-cultural research within the construction industry. It conducts an analysis of the factors influencing the adoption of AI-driven technologies or products, with a specific focus on the cultural differences between two nations: South Korea and the UK, which represent Eastern and Western cultural paradigms, respectively.

This research addresses the factors that impact the acceptance of AI-based technologies or products depending upon firm size in the construction industry, in which various corporates exist. In order to achieve the research goals, a technology acceptance model was applied to investigate the influencing factors in respect to adopting AI-based technologies or products. From the research results, technological and organizational factors were found to positively influence perceived usefulness and perceived ease of use. Corporate users perceived that technology is useful to their work and is easy to use when enough capital and education were invested prior to the company adopting AI-based technologies or products. It was found that perceived ease of use and perceived usefulness indicate satisfaction with new technology, and the higher the intention to use, the higher the satisfaction. In addition, as various information sharing and distribution channels increase, the frequency of use of new technologies or products also increases, not through traditional marketing, but through viral marketing via social media or promotion by influential persons or organizations. Furthermore, there are differences in the adoption of AI-based technologies or products depending on the size of the company.

In the rapidly advancing field of construction, digital site management and Building Information Modeling (BIM) are pivotal. This study explores the integration of drone imagery into the digital construction site management process, aiming to create BIM models with enhanced object recognition capabilities. Initially, the research sought to achieve photorealistic rendering of point cloud models (PCMs) using blur/sharpen filters and generative adversarial network (GAN) models. However, these techniques did not fully meet the desired outcomes for photorealistic rendering. The research then shifted to investigating additional methods, such as fine-tuning object recognition algorithms with real-world datasets, to improve object recognition accuracy. The study’s findings present a nuanced understanding of the limitations and potential pathways for achieving photorealistic rendering in PCM, underscoring the complexity of the task and laying the groundwork for future innovations in this area. Although the study faced challenges in attaining the original goal of photorealistic rendering for object detection, it contributes valuable insights that may inform future research and technological development in digital construction site management.

This paper introduces a modified A* pathfinding algorithm that can be used in building Mechanical Electronic Plumbing (MEP) path design by revising nodes selection process and post-processing. The pathfinding algorithm is used when a computer calculates the optimal path in a given space by algorithmizing how humans intuitively calculate the optimal path. As construction technology is gradually advancing, buildings with large and complex internal structures are increasing, so there is a need to automatically optimize existing design methods that rely on human intuition for a more efficient design. In the case of building MEP design, it is time and money consuming to design paths since they are complexly arranged throughout the building, and designs are frequently changed in response to the nature of the construction industry, where construction errors are frequent. Therefore, an MEP path design optimization module, MEPAutoroute, was developed by implementing a modified A* pathfinding algorithm to solve these problems. Algorithm was applied to seven different exemplary structures with MEP equipment, and the results are analyzed to determine its efficiency.

This study evaluates the vibration data of high-rise buildings during a typhoon by measuring the vibration data and using international serviceability standards. In order to do this, the horizontal vibration serviceability evaluation standards of each country were surveyed, but the standards that could be applied were limited to ISO10137 and ISO 6897. Despite the trend that the discomfort of residents increases as the number of high-rise buildings increases, the current standards are for high-frequency vibrations, such as machine vibrations or vertical floor vibrations, so there is an urgent need for research on new evaluation methods for low-frequency horizontal vibrations. As a result of analyzing the effects of typhoons on buildings, the study’s target building had low natural frequencies of less than 1 Hz, and the highest acceleration was observed to be amplified up to about 160 times due to the effects of Typhoon Danas and Chaba, but there was no change in the natural frequency. When this result was applied to the horizontal vibration serviceability evaluation, it was found that the likelihood of residents perceiving vibration was low during constant vibration, but during strong winds, the size of the top-floor horizontal vibration exceeded the average level of vibration perception proposed by ISO standards, so most residents of high-rise buildings would be likely to perceive the vibration as uncomfortable.

한국전산구조공학회 논문집 제38권 제3호(2025.6) 139 1. 서 론 1.1 연구의 배경 및 목적 포트홀은 아스팔트 도로 포장이 파손되어 노면 일부가 항아 리 모양으로 움푹 패인 구멍을 의미하며, 이는 차량의 주행 효 율성을 저하시킬 뿐만 아니라 운전자 안전을 위협하여 교통사 고의 원인이 된다(Jo and Ryu, 2016). 이러한 이유로 포트홀은 "도로 위의 지뢰"라고도 불리며, 차량 파손을 유발하여 재산 상의 피해를 초래하기도 한다. 포트홀의 발생 원인은 주로 동절기나 장마철에 눈과 비로 인해 아스팔트 균열에 물이 스며들고, 반복된 차량 하중으로 포장의 일부가 파손되는 데 있다(Fig. 1). 아스팔트 균열은 도 로의 노후화와 기상 조건뿐만 아니라 제설 목적으로 사용하는 염화칼슘에 의해서도 발생한다. 특히 최근 일부 지방자치단체 에서 눈이 오기 전에 염화칼슘을 미리 도포하는 사례가 증가 하면서, 도로 균열과 포트홀의 발생이 크게 증가하였다. 이러한 문제는 통계적으로도 확인된다. 최근 2년 2개월 (2022년 1월~2024년 2월) 동안 국민권익위원회의 민간분석시 스템으로 분석한 "포트홀" 관련 민원은 총 52,262건으로 집계 되었으며, 특히 2024년 1월부터 민원이 급증하여 전년 동기간 대비 약 5.8배 증가하였다(Fig. 2).