Augmented Reality Applications Research Articles

Augmented reality based android application for introduction of pneumatic hydraulic components

This study focuses on the utilization of augmented reality (AR) to enable comprehensive visualization of objects. Its primary objective is to develop and evaluate an AR application as a medium for introducing pneumatic hydraulic components. The research method employs a development research approach, following the assessment, design, development, implementation, and evaluation steps proposed by Lee and Owens. The feasibility of the product is determined through various assessments, including black box testing, validation by media experts, validation by content experts, and evaluation of initial user response. The outcome of this study is application software incorporating AR technology for the purpose of introducing pneumatic hydraulic components, along with a corresponding workbook. Whereas the application is compatible with the Android operating system and utilizes QR codes as markers for augmented reality objects, which are conveniently included within the workbook. Performance testing reveals that all application functions perform exceptionally well according to black box testing. Furthermore, the content expert feasibility assessment yields results categorized as “Good,” while both the media expert feasibility and initial user response tests indicate “Very Good” outcomes.

Trends in the Use of Augmented Reality in Character Development within Local Wisdom in Schools: A Bibliometric Study

This paper provides a thorough assessment and analysis of prior research literature. The objective of this review is to ascertain the disparities in research about the Application of Augmented Reality in character development and to determine the best actions to continue this research. This goal is achieved through bibliometric analysis and descriptive content. The keywords "Augmented reality" and "character" were Derived from the Scopus research database for bibliometric analysis. Publications from 2014 to 2024 can only be accessed. The data indicate a substantial rise in the amount Investigation carried out on the application of augmented reality in character development. Specifically, there were 22 papers published in 2022, marking the largest amount of studies and citations was documented during that year. The IEEE Transactions on Visualization and Computer Graphics journal is the most cited source. Quantitative methods are used more often than qualitative methods. Methods such as Descriptive Statistical Analysis and Regression Analysis are the most frequently used, with fifty and forty-five occurrences, respectively. This research could be a valuable reference for other academics exploring the implementation of augmented reality in character analysis. Moreover, the presence of research deficiencies can motivate other scholars to confront these deficiencies with the aim of enhancing the utilization of augmented reality in the cultivation of character in children.

The Impact of AI and VR/AR Technologies on Yuan Blue-and-White Porcelain Art

Yuan blue-and-white porcelain, a treasure of Chinese ceramic art, is renowned worldwide for its unique artistic value and cultural significance. With the continuous advancement of artificial intelligence (AI) technology, the artistic innovation of Yuan blue-and-white porcelain is experiencing new opportunities. AI technology not only improves the efficiency and quality of creation but also breaks through traditional physical limitations, enabling the creation of more diverse and creative artworks. By integrating augmented reality (AR) and virtual reality (VR) technologies, AI provides new ways to display and interact with Yuan blue-and-white porcelain art. In non-physical artistic innovation, AI generates new designs through deep learning algorithms, breaking free from the constraints of traditional handmade processes and creating diverse works. Technologies like generative adversarial networks (GANs) can produce highly realistic Yuan blue-and-white designs, while convolutional neural networks (CNNs) can quickly generate design sketches, enhancing creative efficiency. AI can also optimize designs, improving the artistic quality and visual effects of the works.AR and VR technologies offer immersive experiences and interactivity for the audience. Through virtual exhibition spaces and AR applications, viewers can appreciate Yuan blue-and-white artworks as if they were physically present, enhancing interactivity and visual appeal. VR technology, through virtual exhibitions and other means, enhances the viewing experience and impact of the artworks. The application of AI technology in the non-physical artistic innovation of Yuan blue-and-white porcelain not only enhances creation efficiency and quality but also brings limitless possibilities to artistic creation. The combination of AR and VR technologies further enhances the visual appeal and interactivity of Yuan blue-and-white art. As technology continues to advance, AI will play an increasingly important role in the artistic innovation of Yuan blue-and-white porcelain, creating more splendid artworks.

ADVANCING PRECISION

Augmented reality (AR) technology is revolutionizing spine surgery, offering unprecedented intraoperative image guidance and enhancing patient safety, particularly in complex procedures. This presentation explores the expanding applications of AR in spinal surgery, highlighting recent technological advances that have transformed surgical practices. In addition to improving surgical precision and accuracy, AR provides real-time visualization of critical anatomical structures, aiding in navigation and decision-making during intricate spinal procedures. This presentation will delve into the benefits that AR brings compared to classical techniques, including enhanced visualization, improved spatial awareness, and reduced radiation exposure for both patients and surgical teams. By overlaying virtual information onto the surgeon’s view of the patient, AR facilitates a more intuitive understanding of complex spinal anatomy and pathology, leading to optimized surgical outcomes. Furthermore, this session will cover the diverse applications of AR in a range of spinal conditions operated in Royal Hallamshire Hospital, Sheffield, UK - including spinal tumors, calcified disc herniation, spinal CSF-venous fistula etc. By showcasing the benefits of AR technology across various pathologies, this presentation aims to underscore its transformative potential in advancing spinal surgical care.

Embodied learning of science concepts through augmented reality technology

AbstractAugmented Reality (AR) revolutionizes educational approaches by providing an immersive experience that superimposes virtual 3D elements onto the physical environment. This integration of virtual and real worlds addresses the challenge of understanding abstract concepts by enabling three-dimensional visualization and interaction. This study aims to assess the role of embodied cognition in science learning through AR technology, analyze its impact on collaborative, inquiry-based learning in primary science, and understand students' perceptions of its influence on their engagement and comprehension in collaborative science tasks. Data collection methods for this study included three focus group interviews and five video observations involving ten grade 5 students, totaling 23 participants, in a primary science classroom. The analysis utilized content, thematic, and multimodal frameworks to evaluate student interactions. The findings indicated that the use of AR significantly enhanced the students' learning experiences. Students' comprehension of complex scientific concepts improved through active engagement with 3D models using the AR application. The AR app's 3D virtual shapes encouraged students to move around more during lessons, likely because these shapes were engaging and offered various perspectives. The use of embodied learning was enhanced with the support of AR technology, as students were constantly in motion around the table, using their fingers to manipulate objects and explore 3D forms from different angles.

Augmented reality for basic skills training in laparoscopic surgery: a systematic review and meta-analysis.

Augmented reality (AR) has emerged as a transformative technology in medical education, particularly in training basic laparoscopic skills. Despite its growing applications, the effectiveness of AR in this specific domain remains underexplored, with a lack of standardized assessment frameworks and inconsistent methodologies across studies. This systematic review and meta-analysis aimed to evaluate the effectiveness of AR in laparoscopic basic skills training for medical students and junior physicians. We conducted a systematic review and meta-analysis following PRISMA guidelines. Databases searched included PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov. Studies were selected based on their focus on AR applications in laparoscopic training, involving both randomized controlled trials and non-randomized studies. Inclusion criteria focused on medical students and novice surgeons, assessing educational outcomes such as Global Operative Assessment of Laparoscopic Skills (GOALS) Global, Objective Structured Assessment of Technical Skills (OSATS) Global, OSATS Specific, Training Time, and Subjective Workload. A total of 12 studies involving 434 participants met the inclusion criteria. The analysis revealed that AR technology significantly improved educational outcomes, with participants achieving higher GOALS and OSATS scores. Specifically, the mean difference for GOALS scores was 2.40 points (95% CI [1.30, 3.50], p < 0.001) and for OSATS scores, 7.71 points (95% CI [3.39, 12.03], p < 0.001). Additionally, AR-assisted training showed a reduction in subjective workload, with a mean decrease of 2.95 points (95% CI [- 4.95, - 0.95], p = 0.003). The findings indicate that AR significantly enhances laparoscopic training outcomes, facilitating improved technical skills, efficiency, and learner independence. However, variability in study designs and outcomes limits generalizability. Future research should focus on standardize AR training protocols and evaluate long-term effectiveness to fully leverage AR's potential in surgical education.

Semantic Segmentation Based on Geometric Calibration Using AI and AR in Health Care

In the medical field, medical imaging is essential for precise diagnosis, treatment planning, and condition monitoring. The goal of this work is to improve the field of healthcare imaging by investigating the complementary applications of augmented reality (AR) and artificial intelligence (AI) in semantic segmentation. More precise identification and delineation of anatomical structures and abnormalities in medical images is made possible by AI-driven semantic segmentation, opening the door to more precise diagnosis and treatment plans. Modern AI algorithms are employed in the suggested methodology to perform semantic segmentation in a variety of medical imaging modalities, including ultrasound, CT, and MRI scans. The detection of anomalies such as tumours, irregularities in organs, and neurological disorders is made easier by these algorithms. The foundation for integrating augmented reality technologies into the healthcare ecosystem is provided by the segmented medical images. AR enhances the interaction and visualization of segmented medical data in the context of healthcare. Real-time augmented reality overlays help surgeons by improving surgical navigation and precision. Additionally, AR apps help with medical education by offering professionals and students alike an immersive learning environment. AR provides interactive visualizations to help patients understand their medical conditions when they are going for therapy and rehabilitation. The difficulties in integrating these technologies in the healthcare industry are discussed in this paper, with a focus on the significance of data privacy, regulatory compliance, and easy integration with current healthcare systems. The successful deployment of AI technologies necessitates interdisciplinary collaboration among AI developers, healthcare professionals, and AR specialists to ensure compliance with ethical, legal, and clinical standards mandated in the healthcare domain. The proposed Segmentation mask is redefined with geometric calibration and used with U-Net for image segmentation. The segmentation is experimented on Cityscapes and PASCAL VOC 2012 datasets. The experimental results show that proposed semantic segmentation based on geometric calibration yields more accuracy than its counterparts.

Using Ethno-Pedagogy to Prepare Students for Civic Education in the Society 5.0 Era

This paper is the outcome of a review of the literature on ethno-pedagogy and education in the context of Society 5.0, gathered from various online reports, digital books, and journal articles. Society 5.0 can leverage technology in education to offer more individualized and interactive learning experiences. Examples include online learning and the application of augmented and virtual reality (AR and VR) to the classroom. Education must be adequately prepared in this day and age to assist people in gaining the abilities and knowledge required to meet obstacles in the future. In order to prepare education for the Society 5.0 era, this article aims to investigate the ethno-pedagogy method in greater detail. We refer to this method of teaching based on culture as ethno-pedagogy. The technique is highly pertinent to educating students for the increasingly varied and complicated Society 5.0 era. Using this method enables educators to create a curriculum that honors the cultural values of their students. Technology has the potential to be a helpful tool in the implementation of ethno-pedagogy. Keywords: educational management; ethno-pedagogical approach; Society 5.0 era

Impact of Augmented Reality-Based Learning on Preparing Children for Creative Reading Skills in Childhood Education Stage

This study investigated the impact of augmented reality (AR)-based learning on developing creative reading skills in early childhood education. Using validated instruments, including an AR-based learning guide, and a creative reading skills test, the study involved 254 primary school children from northern Jordan. The sample of the study was divided into an experimental group of 127 children who engaged with AR technology, and a control group of 127 children who received traditional teaching. Findings indicated that the experimental group scored significantly higher on the creative reading skills test than the control group. Statistical analysis using one-way ANOVA confirmed these differences as significant, underscoring the effectiveness of AR-based learning in improving creative reading skills. These results suggest that AR technology holds potential to develop learning outcomes in early childhood settings. Based on these findings, it is recommended to integrate AR technology into early childhood curricula to better support children’s creative reading abilities. As an engaging and interactive tool, AR can nurture creative thinking and cognitive skills that go beyond traditional teaching. Additionally, AR transforms learning into a stimulating, multidimensional experience that enhances children’s motivation to engage actively in the educational process. By creating virtual environments with interactive elements, AR aligns learning closely with real-world contexts, promoting innovative approaches to reading skill development. Further research should explore AR applications in other early childhood education areas, and expand AR-based educational tools, with an emphasis on adapting content to local cultural contexts to achieve effective, impactful results in children’s skills development.

Effectiveness of AR-Based Formative Peer Assessment on Chinese Writing Performance of Students with Different Cognitive Styles

The ability to communicate effectively in writing and produce clear and cohesive text is a necessary skill in both educational settings and the workplace, yet many young students struggle to organize their thoughts and engage in deep thinking. To address these challenges, an augmented reality (AR) application titled “Explore Wild Animals” has been used to help students organize information; however, it may not accommodate different cognitive styles. Integrating formative peer assessment (FPA) strategy into AR-based instruction can enhance knowledge construction and address diverse cognitive needs. This study, conducted from May to June 2023, empirically investigates the effects of FPA in an AR environment on the writing performance of learners with field-independent (FI) and field-dependent (FD) cognitive styles. A total of 89 fifth-grade pupils from China were randomly assigned to two groups: one group adopting FPA in an AR environment (AR-FPA), and the other group adopting FPA in a conventional PowerPoint (PPT) version 2410 environment (FPA). The results of a two-way analysis of covariance (ANCOVA) indicate that the AR-FPA group outperformed the FPA group in writing performance. Specifically, FI learners benefitted more from the AR-FPA approach, while FD learners performed better with the FPA approach. However, multiple linear regression analysis reveals that the peer feedback quality and features showed little to no significant correlation with feedback providers’ writing performance, regardless of cognitive style. These results highlight the effectiveness of integrating AR and FPA in enhancing educational outcomes, providing practical insights for promoting the sustainability of technology-enhanced learning and teaching practices.

Mapping Research Themes and Trends in Ergonomics within Industry 5.0: A Bibliometric Analysis

Abstract: Industry 5.0, the next stage of development after Industry 4.0, centers around the seamless integration of individuals and technology inside industrial processes to foster innovation that prioritizes human needs and experiences. Industry 5.0 diverges from Industry 4.0 by placing greater emphasis on the collaborative partnership between humans and machines rather than solely focusing on automation and advanced technologies like IoT and AI. The study employs bibliometric analysis to delineate the subjects and research areas in ergonomics within the context of Industry 5.0. The study analyzed literature from the Scopus database to identify trends and gaps in implementing ergonomic principles across different industrial sectors. The study addresses two distinct research inquiries: identifying overarching research subjects and emerging research themes. The results indicate the existence of four primary research clusters: the interaction between humans and advanced technology, the safety of work and collaboration between humans and robots, the optimization of multiple purposes and sustainable development, and the application of augmented reality in industrial design. The report emphasizes the growing importance of human-robot collaboration and artificial intelligence while acknowledging a decline in emphasis on user experience and virtual reality. The findings thoroughly analyze the present condition and development of ergonomics research in Industry 5.0 while providing significant recommendations for future investigations and real-world implementations.

Three-layer polarisation volume grating with enhanced diffraction efficiency and FOV in AR and VR applications

ABSTRACT In the rapidly evolving fields of Augmented Reality (AR) and Virtual Reality (VR), achieving high diffraction efficiency and a wide field of view (FOV) is critical for enhancing visual experience. This paper presents a three-layer Polarisation Volume Grating (TL-PVG) structure designed to address the limitations of single-layer PVGs in AR/VR applications. By stacking multiple PVG layers with different tilt angles, TL-PVG achieves an expanded angular bandwidth and improved diffraction efficiency, enabling brighter and more immersive displays. The proposed TL-PVG structure incorporates polarisation multiplexing to optimise the optical diffraction efficiency by approximately 75%, thereby enhancing image brightness and sharpness. The experimental results demonstrate that TL-PVG significantly outperforms traditional single-layer PVGs, offering a promising solution for waveguide elements in next-generation AR/VR displays. This study provides a comprehensive analysis of the fabrication process, optical properties, and applications of TL-PVGs, highlighting their potential to revolutionise the AR/VR technology.

Mobile Augmented Reality Application to Evaluate the River Flooding Impact in Coimbra

The downtown area of the city of Coimbra, Portugal, is at low altitude and has historically suffered floods that have caused serious economic losses. The present research proposes a mobile augmented reality (MAR) application aimed at visualising the effect of possible scenarios of flooding in an area of higher risk in the city. A realistic 3D model of the city was created, using data extracted with BLosm and processed through Blender, followed by its integration into Unity with Vuforia for AR visualisation. The methodology encompasses the extraction and simplification of 3D models, mapping real-world coordinates in Unity, analysing several datasets, obtaining a model through regression and implementing a workflow to manage interactions between various Unity objects. The MAR application enables users to visualise potential flood impacts on buildings, utilising colour-coded indicators to represent different levels of water contact. The system’s efficacy was evaluated by simulating various use-case scenarios, demonstrating the application’s capability to provide real-time, interactive flood risk assessments. The results underline the potential of integrating AR and machine learning for enhancing urban flood management and prevention.

Bibliometric analysis of augmented reality in chemistry education over the past decade

Numerous studies have delved into the application of augmented reality (AR) in chemistry education, focusing on specific topics, equipment requirements, and advantages. However, there remains a notable dearth of research examining the evolutionary characteristics of AR in this context. This study, employing bibliometric analysis on 66 articles spanning from 2012 to 2022, reveals that research primarily revolves around pedagogical approaches and AR technology development, particularly in kindergarten to 12th grade (K-12) education. Despite the United States exhibiting the highest publication frequency, there is a significant absence of studies addressing emotions, cognition, and physiological changes. Shedding light on these research gaps, this study underscores the need for further exploration into the cognitive, emotional, and physiological aspects of AR integration in chemistry education. Ultimately, the insights gleaned from this study offer valuable guidance for researchers, educators, and practitioners alike, facilitating the advancement and effective application of augmented reality in chemistry education (ARCE).

Teaching students with autism spectrum disorder how to use an augmented reality application and the vocabulary of the natural sciences

Technology-based interventions are considered evidence-based for teaching students with Autism Spectrum Disorder (ASD). The main purpose of this study is to teach students with ASD the use of augmented reality (AR) mobile applications through systematic instruction and to test the effectiveness of the presented AR mobile application in teaching science concepts. The secondary aim of this study was to examine the students’ and teachers’ views on the acceptability of the AR mobile application in teaching science vocabulary. Three primary and one secondary school students with ASD, aged 10-13 years, participated in the study. A multiple probe design across participants was used to evaluate the effects of the intervention package. The findings showed that systematic instruction using an AR mobile application is effective in science vocabulary for students with ASD. All students reported using an AR mobile application to learn science vocabulary words was socially acceptable. These results suggest that the AR mobile applications may be a promising instruction instrument that is effective, efficient, and cost-effective. Implications for future research and practice are then discussed.

Barrier height modulation in Amorphous IGZO/Metal interface using Trichlorosilane-Based Self-Assembled monolayers

Amorphous InGaZnO (a-IGZO) has become a key material for thin-film transistors (TFTs) due to its high mobility, low leakage current, and optical transparency. However, the increasing demands for ultra-high-resolution displays, such as those required for virtual and augmented reality applications, pose challenges related to contact resistance and Fermi level pinning at the a-IGZO/metal interface, as TFTs are scaled down. To address these challenges, we investigated trichlorosilane-based self-assembled monolayers (SAMs) as an interfacial layer between a-IGZO and metal contacts (Al, Ag, and Ni). By employing SAMs with varying carbon chain lengths—methyl trichlorosilane (MTS), octyl trichlorosilane (OTS), and octadecyl trichlorosilane (ODTS)—we aimed to improve interface properties and reduce contact resistance. Our study comprehensively analyzed thermionic emission characteristics, including barrier height, saturation current, ideality factor, and contact resistance, across different metal electrodes. The results show that the SAM layers effectively modulate barrier height and Fermi level pinning, depending on the combination of SAM layers (MTS, OTS, and ODTS) and metal electrodes (Al, Ag, and Ni). Additionally, the study provides insights into the influence of SAM carbon chain length on direct tunneling current and interface passivation, and contributes to a deeper understanding of conduction mechanisms at a-IGZO/metal interfaces.

HOIMotion: Forecasting Human Motion During Human-Object Interactions Using Egocentric 3D Object Bounding Boxes.

We present HOIMotion - a novel approach for human motion forecasting during human-object interactions that integrates information about past body poses and egocentric 3D object bounding boxes. Human motion forecasting is important in many augmented reality applications but most existing methods have only used past body poses to predict future motion. HOIMotion first uses an encoder-residual graph convolutional network (GCN) and multi-layer perceptrons to extract features from body poses and egocentric 3D object bounding boxes, respectively. Our method then fuses pose and object features into a novel pose-object graph and uses a residual-decoder GCN to forecast future body motion. We extensively evaluate our method on the Aria digital twin (ADT) and MoGaze datasets and show that HOIMotion consistently outperforms state-of-the-art methods by a large margin of up to 8.7% on ADT and 7.2% on MoGaze in terms of mean per joint position error. Complementing these evaluations, we report a human study (N=20) that shows that the improvements achieved by our method result in forecasted poses being perceived as both more precise and more realistic than those of existing methods. Taken together, these results reveal the significant information content available in egocentric 3D object bounding boxes for human motion forecasting and the effectiveness of our method in exploiting this information.

Expressive 3D Facial Animation Generation Based on Local-to-Global Latent Diffusion.

3D Facial animations, crucial to augmented and mixed reality digital media, have evolved from mere aesthetic elements to potent storytelling media. Despite considerable progress in facial animation of neutral emotions, existing methods still struggle to capture the authenticity of emotions. This paper introduces a novel approach to capture fine facial expressions and generate facial animations using audio synchronization. Our method consists of two key components: First, the Local-to-global Latent Diffusion Model (LG-LDM) tailored for authentic facial expressions, which can integrate audio, time step, facial expressions, and other conditions towards possible encoding of emotionally rich yet latent features in response to possibly noisy raw audio signals. The core of LG-LDM is our carefully designed Facial Denoiser Model (FDM) for aligning the local-to-global animation feature with audio. Second, we redesign an Emotion-centric Vector Quantized-Variational AutoEncoder framework (EVQ-VAE) to finely decode the subtle differences under different emotions and reconstruct the final 3D facial geometry. Our work significantly contributes to the key challenges of emotionally realistic 3D facial animation for audio synchronization and enhances the immersive experience and emotional depth in augmented and mixed reality applications. We provide a reproducibility kit including our code, dataset, and detailed instructions for running the experiments. This kit is available at https://github.com/wangxuanx/Face-Diffusion-Model.

Anatomical variations in 3D imaging: a case report of a dorsal metacarpal artery anomaly

This report presents a novel anatomical variant of the second dorsal metacarpal artery (SDMA). In this unique case, the SDMA abnormally penetrates the second dorsal interosseous muscle (SDIM), dividing into two major branches. A deep dorsal branch of the SDMA (dbSDMA) is located within the SDIM and extends to the distal end of the metacarpal. The other branch forms a perforating branch called the P-SDMA, which anastomoses with the palmar metacarpal artery branch (PMAb) and the deep palmar arch branch (DPAcb) in the deep palmar area. The discovery of this SDMA variant is significant for procedures involving complex hand surgeries such as DMA flaps. Understanding this anatomical variation is crucial for accurate surgical planning and can help avoid potential complications during surgery. To elucidate these unique variations, we employ three-dimensional (3D) imaging techniques, demonstrating the potential of these technologies to advance the visualization of anatomical structures and enhance medical education. 3D imaging also facilitates augmented reality applications and 3D printing. Our findings underscore the possible applications of 3D imaging in medical practice and education, potentially transforming anatomy education and surgical planning.

Robust Collaborative Visual-Inertial SLAM for Mobile Augmented Reality.

Achieving precise real-time localization and ensuring robustness are critical challenges in multi-user mobile AR applications. Leveraging collaborative information to augment tracking accuracy on lightweight devices and fortify overall system robustness emerges as a crucial necessity. In this paper, we propose a robust centralized collaborative rnulti-agent VI-SLAM system for mobile AR interaction and server-side efficient consistent mapping. The system deploys a lightweight VIO frontend on mobile devices for real-time tracking, and a backend running on a remote server to update multiple submaps. When overlapping areas between submaps across agents are detected, the system performs submap fusion to establish a globally consistent map. Additionally, we propose a map registration and fusion strategy based on covisibility areas for online registration and fusion in multi-agent scenarios. To improve the tracking accuracy of the frontend on agent, we introduce a strategy for updating the global map to the local map at a moderate frequency between the camera-rate pose estimation of the frontend VIO and the low-frequency global map optimization, using a tightly coupled strategy to achieve consistency of the multi-agent frontend poses estimation in the global map. The effectiveness of the proposed method is further confirmed by executing backend mapping on the server and deploying VIO frontends on multiple mobile devices for AR demostration. Additionally, we discuss the scalability of the proposed system by analyzing network traffic, synchronization frequency, and other factors at both the agent and server ends.