Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Equipment and workers are two important resources in the construction industry.
Performance monitoring of these resources would help project managers improve the …

Automated, real-time, and reliable equipment activity recognition on construction sites can
help to minimize idle time, improve operational efficiency, and reduce emissions. Previous …

Due to the unstructured, fast-changing environment of construction sites, robots require
human assistance to perform various tasks, especially those involving high dexterity and …

Understanding the state, behavior, and surrounding context of construction workers is
essential to effective project management and control. Exploiting the integrated sensors of …

The productivity of construction equipment plays an important role in completing
construction projects within schedule and under budget. However, the current productivity …

Human-technology interaction is concerned with trust as an inevitable user acceptance
requirement. As the applications of artificial intelligence (AI) and robotics emerge in the …

Along with the rapid development of infrastructure worldwide, traditional manual operations
have been a concern that restricts the high efficiency, safety, and quality of construction …

Activity identification is an essential step to measure and monitor the performance of
earthmoving operations. Many vision-based methods that automatically capture and explain …

Complex industrial problems coupled with the availability of a more robust computing
infrastructure present many challenges and opportunities for machine learning (ML) in the …