Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
Ethics of artificial intelligence and robotics in the architecture, engineering, and construction industry
Artificial intelligence (AI) and robotics research and implementation emerged in the
architecture, engineering, and construction (AEC) industry to positively impact project …
architecture, engineering, and construction (AEC) industry to positively impact project …
[HTML][HTML] AIoT-informed digital twin communication for bridge maintenance
Y Gao, H Li, G **ong, H Song - Automation in Construction, 2023 - Elsevier
Digital twin (DT) has been moving progressively from concept to practice for bridge
operation and maintenance (O&M), but its issues of data synchronization and fault tolerance …
operation and maintenance (O&M), but its issues of data synchronization and fault tolerance …
Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers
The construction industry is among the riskiest industries around the world. Hence, the
preliminary studies exploring the consequences of occupational accidents have received …
preliminary studies exploring the consequences of occupational accidents have received …
[HTML][HTML] Enhancing construction safety: Machine learning-based classification of injury types
The construction industry is a hazardous industry with significant injuries and fatalities. Few
studies have used data-driven analysis to investigate injuries due to construction accidents …
studies have used data-driven analysis to investigate injuries due to construction accidents …
Exploring the additional value of class imbalance distributions on interpretable flash flood susceptibility prediction in the Black Warrior River basin, Alabama, United …
This study proposes a novel flash flood susceptibility prediction framework with a particular
emphasis on the extent of imbalance between the number of flooding and non-flooding …
emphasis on the extent of imbalance between the number of flooding and non-flooding …
[HTML][HTML] Review of advanced road materials, structures, equipment, and detection technologies
As a vital and integral component of transportation infrastructure, pavement has a direct and
tangible impact on socio-economic sustainability. In recent years, an influx of …
tangible impact on socio-economic sustainability. In recent years, an influx of …
A deep reinforcement learning framework for life-cycle maintenance planning of regional deteriorating bridges using inspection data
Determination of regional deteriorating bridges' maintenance strategies for minimizing life-
cycle risks and costs constructs a complex optimization problem. Improper maintenance …
cycle risks and costs constructs a complex optimization problem. Improper maintenance …
[HTML][HTML] Application of deep learning in damage classification of reinforced concrete bridges
Abstract Inspecting Reinforced Concrete (RC) Bridges is crucial to ensure their safety and
perform essential maintenance. The current research introduces the knowledge base for …
perform essential maintenance. The current research introduces the knowledge base for …
Role of national conditions in occupational fatal accidents in the construction industry using interpretable machine learning approach
K Koc - Journal of Management in Engineering, 2023 - ascelibrary.org
Current national occupational safety and health (OSH) initiatives follow reactive approaches,
ie, if it breaks, fix it. Existing accounts, however, failed to improve national OSH …
ie, if it breaks, fix it. Existing accounts, however, failed to improve national OSH …