ArticleSensors (Basel, Switzerland)2024
Optimizing DG Handling: Designing an Immersive MRsafe Training Program.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid growth of e-commerce has significantly increased demands on logistics providers, particularly in the areas of product handling and shipment. One of the most challenging and critical aspects of this process is the handling of dangerous goods (DG). This is a complex and time-intensive operation that requires safety measures and proper packaging and labelling, because mishandling DG can lead to severe injuries, property loss, and legal liability. This puts additional pressure on logistics providers to efficiently manage DG while maintaining speed and safety in the context of e-commerce. To meet this challenge, there is an urgent need to advance training programs and enhance the operational efficiency for DG handling. The use of mixed reality (MR) technology offers a promising solution. By seamlessly integrating virtual elements with real-world environments, MR has the potential to greatly improve the effectiveness and efficiency of the training of DG handling. Earlier research has examined MR in various fields, while there is still a research gap in applying MR specifically to the training of DG handling. This paper seeks to address the current research gap by presenting a novel MR model, named "MRSafe," for a training program on the safe handling of DG. The model offers users virtual experiences and comprehensive guidance to provide operational decision support.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.