Since the inception of Industry 4.0 in 2012, emerging technologies have enabled the
acquisition of vast amounts of data from diverse sources such as machine tools, robust and …

Human-robot collaborative (HRC) assembly combines the advantages of robot's operation
consistency with human's cognitive ability and adaptivity, which provides an efficient and …

Large volumes of used electronics are often collected in remanufacturing plants, which
requires disassembly before harvesting parts for reuse. Disassembly is mainly conducted …

Work-related musculoskeletal disorders are a very impactful problem, both socially and
economically, in the manufacturing sector. To control their effect, standardised methods and …

Human-robot collaborative assembly (HRCA) is one of the current trends of intelligent
manufacturing, and assembly action recognition is the basis of and the key to HRCA. A multi …

Assembly activity recognition and prediction help to improve productivity, quality control, and
safety measures in smart factories. This study aims to sense, recognize, and predict a …

Human activity recognition (HAR) is a popular and challenging research topic driven by
various applications. Deep learning methods have been used to improve HAR models' …

This paper introduces the Human Action Multi-Modal Monitoring in Manufacturing (HA4M)
dataset, a collection of multi-modal data relative to actions performed by different subjects …

In limited visibility human-machine environments, there has been little discussion on hand
motion parameter extraction, behavioral intention data analysis, and the effectiveness of 3D …

Human behaviour recognition is one of the most fundamental tasks in Industrial Internet of
Behaviour (IIoB) and is crucial for the safe and reliable IIoB. Existing methods lacks …