From raw to refined: Data preprocessing for construction machine learning (ML), deep learning (DL), and reinforcement learning (RL) models
As the use of predictive models in construction rapidly increases, the need for preprocessing
raw construction data has become more critical. This systematic review investigates data …
raw construction data has become more critical. This systematic review investigates data …
Monitoring and evaluating the status and behaviour of construction workers using wearable sensing technologies
Wearable sensing technologies (WSTs) are valuable in monitoring status and behaviour of
construction workers, providing insights into their response under varying conditions and …
construction workers, providing insights into their response under varying conditions and …
Blockchain-based on-site activity management for smart construction process quality traceability
Onsite construction activities (OCAs) are essential components affecting construction
process quality. Tracing OCAs can control the construction process with high-resolution …
process quality. Tracing OCAs can control the construction process with high-resolution …
Real-time machine learning-based recognition of human thermal comfort-related activities using inertial measurement unit data
The real-time detection of indoor thermal comfort can bring significant benefits for energy-
efficient controls over the heating, ventilation and air conditioning (HVAC) systems. At …
efficient controls over the heating, ventilation and air conditioning (HVAC) systems. At …
[HTML][HTML] Deep learning-based automated productivity monitoring for on-site module installation in off-site construction
Effectively monitoring and analyzing on-site module installation for modular integrated
construction (MiC) is essential to properly coordinating the MiC process. In this study, the …
construction (MiC) is essential to properly coordinating the MiC process. In this study, the …
Identifying Unsafe Behavior of Construction Workers: A Dynamic Approach Combining Skeleton Information and Spatiotemporal Features
H Wu, Y Han, M Zhang, BD Abebe… - Journal of …, 2023 - ascelibrary.org
Vision-based methods for action recognition are valuable for supervising construction
workers' unsafe behaviors. However, current monitoring methods have limitations in …
workers' unsafe behaviors. However, current monitoring methods have limitations in …
[HTML][HTML] Automated recognition of construction worker activities using multimodal decision-level fusion
This paper proposes an automated approach for construction worker activity recognition by
integrating video and acceleration data, employing a decision-level fusion method that …
integrating video and acceleration data, employing a decision-level fusion method that …
Recognizing sitting activities of excavator operators using multi-sensor data fusion with machine learning and deep learning algorithms
Recognizing excavator operators' sitting activities is crucial for improving their health, safety,
and productivity. Moreover, it provides essential information for comprehending operators' …
and productivity. Moreover, it provides essential information for comprehending operators' …
Activity sampling in the construction industry: a review and research agenda
Purpose Activity sampling is a technique to monitor onsite labourers' time utilisation, which
can provide helpful information for the management level to implement suitable labour …
can provide helpful information for the management level to implement suitable labour …
A teacher–student deep learning strategy for extreme low resolution unsafe action recognition in construction projects
A large proportion of construction accidents are caused by workers' unsafe actions. Due to
the complexity of the work environment and excessive demands of safety supervision on …
the complexity of the work environment and excessive demands of safety supervision on …