OOIR: Observatory of International Research

Papers

(The H4-Index of Automation in Construction is 75. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
Towards a semantic Construction Digital Twin: Directions for future research	499
Roles of artificial intelligence in construction engineering and management: A critical review and future trends	398
Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities	277
Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms	240
Public and private blockchain in construction business process and information integration	234
From BIM to extended reality in AEC industry	222
A BIM-data mining integrated digital twin framework for advanced project management	219
Deep learning for site safety: Real-time detection of personal protective equipment	210
Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning	208
Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance	200
Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications	195
Integrated digital twin and blockchain framework to support accountable information sharing in construction projects	192
XGBoost algorithm-based prediction of concrete electrical resistivity for structural health monitoring	177
Digital twin and its implementations in the civil engineering sector	176
3D printing of a post-tensioned concrete girder designed by topology optimization	166
Cloud computing in construction industry: Use cases, benefits and challenges	164
Virtual reality applications for the built environment: Research trends and opportunities	161
Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning	159
An integrated approach to automatic pixel-level crack detection and quantification of asphalt pavement	146
Integrated project delivery with blockchain: An automated financial system	141
Construction quality information management with blockchains	133
BIM-based immersive Virtual Reality for construction workspace planning: A safety-oriented approach	133
Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression	132
On-site autonomous construction robots: Towards unsupervised building	125
Structural crack detection using deep convolutional neural networks	122

Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods	118
A real-time detection approach for bridge cracks based on YOLOv4-FPM	116
Additive manufacturing: Technology, applications, markets, and opportunities for the built environment	113
Expertise-based bid evaluation for construction-contractor selection with generalized comparative linguistic ELECTRE III	112
A semantic differential transaction approach to minimizing information redundancy for BIM and blockchain integration	111
Integrating three-dimensional road design and pavement structure analysis based on BIM	106
Deep convolution neural network-based transfer learning method for civil infrastructure crack detection	106
Development of BIM, IoT and AR/VR technologies for fire safety and upskilling	105
A smart contract system for security of payment of construction contracts	105
An integrated UGV-UAV system for construction site data collection	104
Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology	103
Deep learning-based road damage detection and classification for multiple countries	103
Securing interim payments in construction projects through a blockchain-based framework	102
A spatial-channel hierarchical deep learning network for pixel-level automated crack detection	102
A 3D concrete printing prefabrication platform for bespoke columns	102
BIM compatibility and its differentiation with interoperability challenges as an innovation factor	102
Pavement distress detection using convolutional neural networks with images captured via UAV	101
Text mining-based construction site accident classification using hybrid supervised machine learning	101
Construction payment automation using blockchain-enabled smart contracts and robotic reality capture technologies	99
Ultra-rapid delivery of specialty field hospitals to combat COVID-19: Lessons learned from the Leishenshan Hospital project in Wuhan	98
Complete coverage path planning using reinforcement learning for Tetromino based cleaning and maintenance robot	97
Detection and localization of rebar in concrete by deep learning using ground penetrating radar	96
Semantic segmentation of point clouds of building interiors with deep learning: Augmenting training datasets with synthetic BIM-based point clouds	94
LiDAR-equipped UAV path planning considering potential locations of defects for bridge inspection	94
Applications of distributed ledger technology (DLT) and Blockchain-enabled smart contracts in construction	91
Attention-based generative adversarial network with internal damage segmentation using thermography	90
Combining multi-criteria decision making (MCDM) methods with building information modelling (BIM): A review	90
Voxel-based representation of 3D point clouds: Methods, applications, and its potential use in the construction industry	89
Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings	88
Modular composite building in urgent emergency engineering projects: A case study of accelerated design and construction of Wuhan Thunder God Mountain/Leishenshan hospital to COVID-19 pandemic	86
Automatic detection of moisture damages in asphalt pavements from GPR data with deep CNN and IRS method	85
Data mining in the construction industry: Present status, opportunities, and future trends	84
Computer vision applications in construction: Current state, opportunities & challenges	83
Indoor 3D reconstruction from point clouds for optimal routing in complex buildings to support disaster management	82
Intelligent contract adoption in the construction industry: Concept development	82
Automated pixel-level pavement distress detection based on stereo vision and deep learning	81
An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference	81
Deep learning and network analysis: Classifying and visualizing accident narratives in construction	81
Improving progress monitoring by fusing point clouds, semantic data and computer vision	81
Semi-automated generation of parametric BIM for steel structures based on terrestrial laser scanning data	79
Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network	79
BIM for facilities management: A framework and a common data environment using open standards	78
Real-time monitoring of construction sites: Sensors, methods, and applications	78
Sensor-based safety management	77
Real-time railroad track components inspection based on the improved YOLOv4 framework	77
Trajectory control of electro-hydraulic position servo system using improved PSO-PID controller	76
Automatically learning construction injury precursors from text	76
Interoperability in building information modeling for AECO/FM industry	76
Leakage detection in water pipelines using supervised classification of acceleration signals	76
Structural Health Monitoring with Distributed Optical Fiber Sensors of tunnel lining affected by nearby construction activity	75

Pavement asset management systems and technologies: A review	75
Measurement and visualization of strains and cracks in CFRP post-tensioned fiber reinforced concrete beams using distributed fiber optic sensors	75
Modelling and interpreting pre-evacuation decision-making using machine learning	75
Hazard identification, risk assessment and control for dam construction safety using an integrated BWM and MARCOS approach under interval type-2 fuzzy sets environment	75
The classification of construction waste material using a deep convolutional neural network	75
Exploring smart construction objects as blockchain oracles in construction supply chain management	75