Visual data captured at construction sites is a rich source of information for the day-to-day
operation of construction projects. The development of deep-learning-based methods has …

Image-based analysis techniques offer a robust way to solve engineering problems due to
the availability of visual data (eg, surveillance cameras). Hence, research efforts have …

Dam displacements can effectively reflect its operational status, and thus establishing a
reliable displacement prediction model is important for dam health monitoring. The majority …

Construction sites are highly hazardous due to the dynamic interaction between workers
and moving equipment, with high fatality rates caused by collision and falling from height …

The establishment of smart construction sites employing smart technologies for real-time
interconnection, communication, and interaction has emerged as an interesting topic for …

Artificial intelligence (AI) and robotics research and implementation emerged in the
architecture, engineering, and construction (AEC) industry to positively impact project …

This paper proposes using Deep Neural Networks (DNN) models for recognizing
construction workers' postures from motion data captured by wearable Inertial Measurement …

To be successful in managing earthmoving projects, it is very important to monitor the
operational efficiency and productivity of heavy equipment. Researchers have investigated …

The unsafe behavior of construction workers is one of the main causes of safety accidents at
construction sites. To reduce the incidence of construction accidents and improve the safety …

Purpose The purpose of this study is to investigate the potential of using computer vision
and deep learning (DL) techniques for improving safety on construction sites. It provides an …