Human-centered intelligent construction for sustainable cities

H Kang, H Kim, J Hong, J Jeoung, M Lee… - Automation in …, 2024 - Elsevier
Automatic technologies are a developing trend in the construction industry and have
emerged by leveraging intelligent technologies. In automated construction, a human …

Revealing the coupled evolution process of construction risks in mega hydropower engineering through textual semantics

K Cao, S Chen, C Yang, Z Li, L Luo, Z Ren - Advanced Engineering …, 2024 - Elsevier
Mega hydropower engineering (MHE) involves complex construction processes, harsh
environments, and highly mobile personnel, equipment, and other resources, resulting in a …

Automatic repetitive action counting for construction worker ergonomic assessment

X Chen, Y Yu - Automation in Construction, 2024 - Elsevier
Work-related musculoskeletal disorders are the primary cause of nonfatal occupational
injuries in the construction industry. Accurate ergonomic assessment is essential to reduce …

Contextual multimodal approach for recognizing concurrent activities of equipment in tunnel construction projects

G Jeong, M Jung, S Park, M Park, CR Ahn - Automation in Construction, 2024 - Elsevier
In order to accurately track progress and improve efficiency in complex construction projects,
it's important to effectively monitor individual tasks and measure the time taken to complete a …

Dual attention-based deep learning for construction equipment activity recognition considering transition activities and imbalanced dataset

Y Shen, J Wang, C Feng, Q Wang - Automation in Construction, 2024 - Elsevier
With the advancement of sensor and data acquisition technology, the development of multi-
sensor integrated construction equipment has become increasingly prominent. Activity …

The rise of digitalization in constructions: State-of-the-art in the use of sensing technology for advanced building-assistance systems

J Suo, S Waje, VKT Gunturu, A Patlolla… - Frontiers in Built …, 2024 - frontiersin.org
The construction sector is traditionally affected by on-site errors that significantly impact both
budget and schedule. To minimize these errors, researchers have long hypothesized the …

Vision-based multi-label detection framework for capturing occupant action and clothing information using large-scale dataset

S Jung, J Jeoung, T Hong, H Jang - Building and Environment, 2024 - Elsevier
Capturing occupant action and clothing information is important for applying occupant-
centric control (OCC) to mitigate energy overuse and improve indoor environment quality …

A Scalogram-based CNN approach for audio classification in construction sites

M Scarpiniti, R Parisi, YC Lee - Applied Sciences, 2023 - mdpi.com
The automatic monitoring of activities in construction sites through the proper use of acoustic
signals is a recent field of research that is currently in continuous evolution. In particular, the …

Leveraging convolutional neural networks for efficient classification of heavy construction equipment

MS Yamany, MM Elbaz, A Abdelaty… - Asian Journal of Civil …, 2024 - Springer
Effective classification and detection of equipment on construction sites is critical for efficient
equipment management. Despite substantial research efforts in this field, most previous …

Improving single‐stage activity recognition of excavators using knowledge distillation of temporal gradient data

A Ghelmani, A Hammad - Computer‐Aided Civil and …, 2024 - Wiley Online Library
Single‐stage activity recognition methods have been gaining popularity within the
construction domain. However, their low per‐frame accuracy necessitates additional post …