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Yee Sye Lee, Ali Rashidi, Amin Talei and Daniel Kong
In recent years, mixed reality (MR) technology has gained popularity in construction management due to its real-time visualisation capability to facilitate on-site decision-making tasks. The semantic segmentation of building components provides an attrac...
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Mihael Gudlin, Miro Hegedic, Matija Golec and Davor Kolar
In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements...
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Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
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Thabit Atobishi, Sahar Moh?d Abu Bakir and Saeed Nosratabadi
As public sector agencies face rising imperatives to digitally transform citizen services, data systems, and internal operations, questions persist as to whether investments in big data analytics and automation capabilities, evidenced to drive organizati...
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Rafael Moreno-Vozmediano, Rubén S. Montero, Eduardo Huedo and Ignacio M. Llorente
The adoption of edge infrastructure in 5G environments stands out as a transformative technology aimed at meeting the increasing demands of latency-sensitive and data-intensive applications. This research paper presents a comprehensive study on the intel...
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Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
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Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
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Ryszard Dindorf
This article presents the conceptual design, operation principle, dynamic modeling, and simulation results of a discrete incremental hydraulic positioning system (DIHPS) intended for use in high-precision, heavy-load industrial automation solutions. An o...
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Guoyu Zhang, Ye Tian, Wenhan Yin and Change Zheng
The use of automation technology in agriculture has become particularly important as global agriculture is challenged by labor shortages and efficiency gains. The automated process for harvesting apples, an important agricultural product, relies on effic...
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Beata Baziak, Marek Bodziony and Robert Szczepanek
Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimat...
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