Applications and effectiveness of augmented reality in safety training: A systematic literature review and meta-analysis

Metro construction poses significant risks and is prone to severe safety accidents. Safety training is critical to mitigate risks and reduce the number of accidents, as it allows workers to enhance their skills in risk identification, risk assessment, and risk response and ultimately reduce accidents. However, traditional training methods used today, such as slide presentations, videos, or text-based materials, provide a passive learning environment, which can limit their effectiveness in knowledge transfer. Augmented Reality (AR) has emerged as a promising tool for training, allowing trainees to have an active learning environment. Nevertheless, research on assessing the effectiveness of AR safety training while comparing it with traditional methods is still limited. This study aims to compare the short-term and long-term effects on objective performance measures and subjective evaluations of both traditional and AR training. This is done by developing a new AR safety training for metro construction and comparing it with an equivalent slide-based safety training with 72 participants divided into two training groups. The selected safety case study covers the entire safety risk management process, including risk identification, risk assessment, and risk response. Results indicate that AR training is more effective than traditional training in terms of short-term knowledge acquisition of risk identification and long-term knowledge retention of risk identification, risk assessment, and risk response. These findings can have implications for the design of future safety training guidelines and recommendations. 

Comparing the effectiveness of AR training and slide-based training: The case study of metro construction safety

—Scalable multi-user interactions on diverse extended reality (XR) devices are vital for the metaverse’s fruition. However, issues like broad user access, intensive interaction rendering, and limited device resources complicate existing interactions based on client-server and peer-to-peer structures. The metaverse’s demands for scalable access and detailed scene rendering intensify these problems. In response, we present SCAXR, a collaborative architecture enhancing multi-user interaction. SCAXR leverages three key components: an on-demand rendering module, a distributed rendering process, and edge-cloud synchronization. This module ensures timely communication between XR devices and edge servers. We tested SCAXR’s efﬁcacy with a Unity Render Streaming-based XR meeting prototype. Results show SCAXR boosts access capacity by 50% over traditional methods and enhances complex scene interaction performance by up to 7.8 times in rendering frequency.

SCAXR: Empowering Scalable Multi-User Interaction for Heterogenous XR Devices

Enabling Customizable Workflows for Industrial AR Applications

Augmented Reality (AR) as a technology in the business area is utilized in new frontiers such as collaborative real-time experiences and cloud-based solutions. However, there is still a strong tendency towards game engines, which hinders widespread adoption for businesses. We present a collaborative AR framework (Flutter plugin) aimed at lowering the entry barriers and operating expenses of AR applications. A cross-platform and cloud-based solution combined with a web-based content management system (cloud) is a powerful tool for non-technical staff to take over operational tasks such as providing 3D models or moderating community annotations. To achieve cross-platform support, the AR Flutter plugin builds upon ARCore (Android) and ARKit (iOS) and unifies the two frameworks using an abstraction layer written in Dart. In this extensive description we present an in-depth summary of the concepts to realize the framework and prove its performance being on the same level as the native AR frameworks. This includes application-level metrics like CPU and RAM consumption and tracking-level qualities such as keyframes per second used by the underlying SLAM algorithm, detected feature points, and area of tracked planes. Our contribution closes a gap in today’s technological landscape by providing an AR framework with the familiar development process of cross-platform apps. Building upon on a content management system (cloud) and AR can be a game changer to achieve business objectives, while being not restrained to stand-alone single-purpose apps. This will trigger a potential paradigm shift for previously complex-to-realize applications relying on AR, e.g., in production and planning. The AR Flutter plugin is fully open-source, the code can be found at: https://github.com/CariusLars/ar_flutter_plugin.

Cloud-based cross-platform collaborative augmented reality in flutter

If Mixed Reality applications are supposed to become truly ubiquitous, they face the challenge of an ever evolving set of hardware and software systems - each with their own standards and APIs–that need to work together and become part of the same shared environment (the application). A unified standard is unlikely so we can not rely on a single software development stack to incorporate all necessary parts. Instead we need frameworks that are modular and flexible enough to be adapted to the needs of the application at hand and are able to incorporate a wide range of setups for devices, services, etc. We identified a set of common questions that can be used to characterize and analyze Mixed Reality applications and use these same questions to identify challenges as well as present solutions in the form of three frameworks tackling the fields of tracking and inference (UbiTrack), interaction (Ubi-Interact) and visualization (UbiVis). Tracking and inference has been addressed for quite some time now while interaction is a current topic with existing solutions. Visualization will be focused more in the future. We present several applications in development together with their future vision and explain how the frameworks help realize these and other potential apps.

Frameworks Enabling Ubiquitous Mixed Reality Applications Across Dynamically Adaptable Device Configurations

Creating digital representations of industrial facilities presents substantial opportunities for the industry. The development of digital twins opens up many prospective applications for industrial plants, such as facilitating virtual training environments, streamlining change management, and providing real-time understanding of remote scenes. However, creating and maintaining these digital twins involves complex tasks, including scanning industrial plants and annotating their subsystems. Many use cases necessitate specifying a Volume of Interest (VoI) for further processing while presenting severe environmental challenges for segmentation quality and worker safety. Besides that, widespread adoption also depends on creating methods that are easy to use, even for workers with limited 3D interaction knowledge. Currently, no commonly implemented method fulfills all these diverse requirements. This paper introduces an approach for specifying a VoI in industrial scenarios. Our approach defines a volume by intersecting the projection of hand-drawn surroundings on a small number of pictures of the target volume, utilizing Augmented Reality and Voxel Carving. It can successfully handle various sizes of target volumes and delivers an appropriately detailed result. Applying qualitative discussions and a quantitative evaluation, we ensure our application meets all requirements posed by the scenarios. This simple interaction metaphor, tailored to specific use cases, can serve as a versatile pattern for various digital twin scenarios. It offers a valuable alternative to 3D primitive-based segmentation methods.

Specifying Volumes of Interest for Industrial Use Cases

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Frameworks Enabling Ubiquitous Mixed Reality Applications Across Dynamically Adaptable Device Configurations

Specifying Volumes of Interest for Industrial Use Cases