AI integration in construction safety: Current state, challenges, and future opportunities in text, vision, and audio based applications

ABK Rabbi, I Jeelani - Automation in Construction, 2024 - Elsevier
High occupational injury and fatality rate in the construction industry is a serious global
concern. Recognizing AI as a solution to enhance safety performance, this study reviews …

[HTML][HTML] CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children

J Kunhoth, S Al Maadeed, M Saleh, Y Akbari - Expert Systems with …, 2023 - Elsevier
Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing
skills in children, resulting in poor writing abilities. Poor or underdeveloped writing skills in …

[HTML][HTML] Keypoints-based Heterogeneous Graph Convolutional Networks for construction

S Wang, L Yang, Z Zhang, Y Zhao - Expert Systems with Applications, 2024 - Elsevier
Artificial intelligence algorithms employed for classifying excavator-related activities
predominantly rely on sensors embedded within individual machinery or computer vision …

[HTML][HTML] Late acceptance hill climbing aided chaotic harmony search for feature selection: An empirical analysis on medical data

A Naskar, R Pramanik, SKS Hossain, S Mirjalili… - Expert Systems with …, 2023 - Elsevier
In today's era of data-driven digital society, there is a huge demand for optimized solutions
that essentially reduce the cost of operation, thereby aiming to increase productivity …

Visual–auditory learning network for construction equipment action detection

S Jung, J Jeoung, DE Lee, H Jang… - Computer‐Aided Civil …, 2023 - Wiley Online Library
Action detection of construction equipment is critical for tracking project performance,
facilitating construction automation, and fostering construction efficiency in terms of …

A new one-dimensional testosterone pattern-based EEG sentence classification method

T Keles, AM Yildiz, PD Barua, S Dogan… - … Applications of Artificial …, 2023 - Elsevier
Electroencephalography (EEG) signals are crucial data to understand brain activities. Thus,
many papers have been proposed about EEG signals. In particular, machine learning …

Artificial intelligence enhanced automatic identification for concrete cracks using acoustic impact hammer testing

MN Alhebrawi, H Huang, Z Wu - Journal of Civil Structural Health …, 2023 - Springer
Impact hammer testing is a regular structure inspection method for detecting surface and
internal damages. Inspectors use the sound from impact hammer testing to determine the …

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 …

Machine learning-based optimisation in a two-echelon logistics network for the dry port operation in China

Q Li, Y Wang, Y Xiong, S Zhang… - International Journal of …, 2023 - Taylor & Francis
Efforts of creating economic recovery after the COVID-19 pandemic stipulate international
logistics demands in the countries and regions affected by China's Belt and Road initiative …

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children

K Jayakanth, S Al Maadeed, M Saleh, Y Akbari - 2023 - qspace.qu.edu.qa
Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing
skills in children, resulting in poor writing abilities. Poor or underdeveloped writing skills in …