A Foreign Language Learning Application using Mobile Augmented Reality

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

Augmented reality simulations aims to provide realistic blending between real world and virtual objects. One of the important factors for realistic augmented reality is correct illumination simulation. Mobile augmented reality systems is one of the best options for introducing augmented reality to the mass market due to its low production cost and ubiquitousness. In mobile augmented reality systems, the ability to correctly simulate in realtime the illumination direction that matches the illumination direction of the real world is limited. Developing a mobile augmented reality systems with the ability to estimate illumination direction presents a challenge due to low computation power and dynamically changing environment. In this paper, we described a new method that we have developed for realtime illumination direction estimation for mobile augmented reality systems, using analysis of shadow produced by a reference object that doubles as a 3D augmented reality marker. The implementation of the method could estimate the direction of a single strong light source in a controlled environment with a very good degree of accuracy, with angular error averaging lower than 0.038 radians. The current implementation achieved 2.1 FPS performance in a low-end Android mobile device, produced proper estimation within 15 seconds using a uniform surface, and demonstrated scalability potential.

This article presents a mobile Augmented Reality system, called DiedricAR, aimed at the learning of Descriptive Geometry. Thanks to its ability to recreate virtual models in real space, Augmented Reality is a technology suitable for making Descriptive Geometry comprehension and interpretation easier. The DiedricAR application allows students to learn in autonomously way by using their own mobile devices (smartphones and tablets), that work as Augmented Reality displays over training material (DiedricAR exercise workbook) specially designed for the new learning model defined by the European Higher Education System. Compared to some of the existing Augmented Reality systems used to learn Descriptive Geometry, DiedricAR offers the advantage of being specifically developed for mobile devices giving the students the possibility of using ubiquitous learning to its ultimate extent by interacting with the didactical content (i.e. showing the desired intermediate step when solving dihedral exercises). The presentation of DiedricAR is completed by exploring some key items such as the potential benefits for students' spatial ability, the relationship between application design and user experience, and software performance on several mobile devices.

IntroductionThe introduction of augmented reality (AR) in medical education has been demonstrated to improve learning of medical students and young clinicians. Use of AR is often linked to Head Mounted Displays (HMD), whose high costs and expertise demands make them less widely applicable.MethodsThe open-source application Medical Imaging XR (MIXR), developed by Medicalholodeck™, was used to visualize computed tomography examinations in augmented reality on mobile devices, including smartphones and tablets. Cases were presented during Radiology lectures. Clinical cases relevant to each lecture topic—thorax, abdomen, gynecology, musculoskeletal system, and emergency medicine—were selected from our local picture archiving system. The cases were demonstrated on mobile devices during a radiological lecture, either in person or via video conference. To evaluate the educational experience, students provided feedback through a structured questionnaire.ResultsMedical students received a demonstration with AR in the lecture and were asked to answer a questionnaire. 47 students replied to the questionnaire. Students rated their experience with MIXR in a positive manner. 36.2% of students considered AR images to be very comprehensible, whereas only 21.3% considered conventional images as very comprehensible. 32 out of 47 considered that AR demonstration contribute to better understanding of the case as whole. 91.8% of students would like to continue using AR in the studies and 80.9% would like to have similar tools available for future interactions with patients.Conclusion/DiscussionIntroduction of AR in radiology lectures is well received by medical students, who would be interested in continuing using AR tools in their studies and future career. Using mobile device-based AR proved viable, contributing to democratization of AR, in a low-cost manner and with no need for extended expertise.

-In the recent period, many real-world applications and institutions generates a huge amount of data which is unstructured i.e., in the form of images containing data, receipts, invoices, forms, statements, contracts etc. This rich and detailed information presented in the text is of great significance in computer vision-based applications (driverless cars, assisting blind and visually impaired people, detecting labels and packages, automatic number plate recognition etc.). Recently, there has been a hike in the efforts, This project presents AR Weather, a simulation application, which can simulate three types of precipitation: rain, snow, and hail. We examined a range of weather phenomenon and how they may be simulated in a mobile augmented reality system. AR Weather was developed and deployed on the Tinmith wearable computer system to enable autonomous and free movement for the user. The user can move freely inside the simulated weather without limitation. The result of this work, the AR Weather application, has been evaluated with a user study to determine the user’s acceptance and draw conclusions to the applicability of augmented reality simulated weather Keywords- Mobile augmented reality, environmental sensor networks, mobile visualization

The boom in the capabilities and features of mobile devices, like smartphones, tablets, and wearables, combined with the ubiquitous and affordable Internet access and the advances in the areas of cooperative networking, computer vision, and mobile cloud computing transformed mobile augmented reality (MAR) from science fiction to a reality. Although mobile devices are more constrained computationalwise from traditional computers, they have a multitude of sensors that can be used to the development of more sophisticated MAR applications and can be assisted from remote servers for the execution of their intensive parts. In this paper, after introducing the reader to the basics of MAR, we present a categorization of the application fields together with some representative examples. Next, we introduce the reader to the user interface and experience in MAR applications and continue with the core system components of the MAR systems. After that, we discuss advances in tracking and registration, since their functionality is crucial to any MAR application and the network connectivity of the devices that run MAR applications together with its importance to the performance of the application. We continue with the importance of data management in MAR systems and the systems performance and sustainability, and before we conclude this survey, we present existing challenging problems.

Efficient mobile AR technology using scalable recognition and tracking based on server-client model

The purpose of this study was to explore the perspectives of Australian educators on using augmented reality (AR) as a method for learning human anatomy in the undergraduate health sciences. This will determine the current value of AR and guide future research and development. This prospective qualitative study used a mixed-methods approach to gain detailed feedback from 10 anatomy educators at Curtin University. Educators interacted with mobile AR using an iPad and the Complete Anatomy application. A survey measured perceived usability through the System Usability Scale (SUS) and used Likert-scale responses and short-answer questions to determine educators' perspectives of AR. The SUS measured a mean usability score of 58.25, SD ± 15.41 (95% CI: 47.22, 69.28), translating to a 'D' grade. Educators demonstrated positive perspectives of new technology but found that AR presented more challenges than benefits. Recommendations focused on overcoming hardware difficulties and ensuring in-depth educational content with reference to the cadaveric study. Mobile AR does not currently hold substantial value for anatomy education; however, the benefits of AR may be optimized using a head-mounted display. Future research must consult all potential stakeholders to critically define how AR will provide measurable value for anatomy education.

A 3-level architecting approach to adaptive resource management in mobile augmented reality systems (MARS) is elaborated, which is based on comprehensive data structuring and analyzing of their specific hard- and software features. At the conceptual modeling level an ontology of adaptive MARS resources is constructed, and at the logical modeling level a generic algorithmic model is proposed, which can be instantiated in the collection of specific methods and metrics. As a physical model the reference software architecture for adaptive resource management in MARS is designed, and this approach is implemented partly as a software prototype. It is tested successfully to solve the task of adaptive image resolution on mobile device, according to changes of computational load that finally enables better video stream quality in MARS.

With the combination of deep learning and mobile edge computing, the accuracy of the computer vision task in mobile augmented reality (AR) applications can be significantly improved along with the enhancement on the end-to-end latency and energy efficiency. However, no architecture-based delay model for convolutional neural networks (CNNs) has been proposed in edge computing. In this paper, we first develop a new delay model to characterize the relation between the processing delay and the input image size of general CNN models. Then, we formulate a non-convex optimization problem to maximize the learning accuracy under the communication and computation resource constraints. By problem transformation, the optimal resource allocation policy is derived in closed-form and low-complexity search algorithm is also developed. Finally, test results validate the applicability of the delay model and demonstrate the learning accuracy improvement of the proposed algorithm.

This research aims to develop a tool for creating user-based design interfaces in mobile augmented reality (MAR) education. To develop a design interface evaluation tool, previous literature was examined for key design elements in the educational usage of MAR. The evaluation criteria identified were presence, affordance, and usability. The research used a focus group interview with 7 AR experts to develop a basic usability evaluation checklist, which was submitted to factor analysis for reliability by 122 experts in practice and academia. Based on this checklist, a MAR usability design interface test was conducted with seven fourth-grade elementary students. Then, it conducted follow-up structured interviews and questionnaires. This resulted in 29 questions being developed for the MAR interface design checklist.

Technology can change the way students learn, become a powerful motivation, and trigger the learning process. This article discusses mobile augmented reality technology in education. Mobile Augmented Reality (MAR) is more effective in providing students with a positive, effective, and powerful learning experience. The researcher looked for Google Scholar and Scopus articles from the year 2015–2020. This advanced technology can help people communicate with each other’s senses and experience applications, thereby stimulating consumers’ interest through natural interaction. Researchers have been studying ways to incorporate enhanced environments into education so that students can participate in real-world environments. Related topics of the study are also mainly discussed: the past reviewers of systematic reviews, augmented reality education, Mobile Augmented Reality software development kits, Augmented Reality technology, user interfaces in Mobile Augmented Reality, and the future of Augmented Reality in education. Mobile augmented reality has aroused increasing interest in academia and industry. The real world and virtual information work together to create new educational opportunities. The research results indicate that augmented reality has various potentials and advantages and can be added to the field of education.KeywordsMobile augmented realityEducationLearning

We present a mobile tracking system for hands and arms capable of detecting the full range of motion, suitable for use in mobile augmented reality systems. The hand position is tracked using orientation sensors attached to the upper and forearms. Using two or more orientation sensors, the natural movements of the human arm can be captured relative to the user's torso. This tracking technique allows unique interaction in a mobile augmented reality environment performing tasks such as selection and moving of 3D objects. Further, we have applied a non-linear scaling technique allowing out of arms reach interaction area.

A framework for context immersion in mobile augmented reality

Augmented reality (AR) is an emerging technology in mobile app design during recent years. However, usability challenges in these apps are prominent. There are currently no established guidelines for designing and evaluating interactions in AR as there are in traditional user interfaces. In this work, we aimed to examine the usability of current mobile AR applications and interpreting classic usability heuristics in the context of mobile AR. Particularly, we focused on AR home design apps because of their popularity and ability to incorporate important mobile AR interaction schemas. Our findings indicated that it is important for the designers to consider the unfamiliarity of AR technology to the vast users and to take technological limitations into consideration when designing mobile AR apps. Our work serves as a first step for establishing more general heuristics and guidelines for mobile AR.