Forecasting the Weather and its Visualization using Augmented Reality

1 IntroductionNowadays, the institutes already use in the process of the advantages of mobile technology, such as portability (the students have easy access at any time to information), the use of digital assets (audio and video files) and huge amount of textual information. This study proposes a new system approach for improving the process by Mobile Augmented Reality. The features of this technology stimulate the environment and consider that the student's motivation is the most important factor in learning.The existing literature [1] highlights two different approaches for augmented reality (AR). Firstly, the authors consider that AR is a system which has the following characteristics: Combines real and virtual; Interactive in real time; Registered in 3-D. Secondly [1] considers Augmented Reality part of Virtual Continuum. This context is composed of two elements: Real Environment - which contains all representations from real life and Virtual Environment - which combines different elements from virtual life. ARs are considered closer to reality than virtual environment because this type of systems are supposed to extend the real objects with virtual elements.According to [2] Augmented Reality is a technology that extends the real world elements with 2D or 3D computer generated objects and lets the users interact with them. Also, the authors present three types of devices which can be used to view the result of AR technology: a Head Mounted Display (HMD), a mobile device - with at least one back camera and a desktop or a laptop computer.Similarly, [2] considers mobile technology as an alternative teaching resource because the users have easy access in real time to information. Also, mobile devices in the process two main problems of traditional are solved: the location and time. Likewise, [1] considers that mobile is a type of eLearning without restrictions of time and space and this technology improves the quality of classical environments, but does not replace them.Other researches, such as [3] and [4] highlight the benefits of a Mobile Augmented Reality system based on tracking objects. In [3] is proposed a mobile augmented reality system based on visual recognition. According to the authors the visual recognition consists into tracking objects identified in real world with the camera of the mobile device and augmenting the scene with virtual objects created by MAR technology. Similarly, [4] presents a Mobile Augmented Reality system bases on 3D registration technology. According to the authors the 3D registration represents the tracking of the position and pose of the mobile device in the real time and real life and finally use these information to insert in the real world the virtual scene created by MAR. The 3D registration technology is based on two type of approaches: markers and natural features. Recently, the 3D registration for MAR uses GPS and sensors from mobile devices to provide different information about position and pose of the camera and combine them with computer vision to improve the speed and accuracy of the system.Other studies, such as [5] propose a makerbased Mobile Augmented Reality solution. The application is used by a Vocational Educational and Training (VET) program for supporting the maintenance process of a car. The authors define VET as education programs that are designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation, trade or class of occupations or trades(p. 49-50). Moreover, in [5] is presented an AR application used by VET students for basic mathematics skills, which is based on videogames.More studies, such as [6] present a Mobile Augmented Reality solution for French language which is based on gamification didactic method. The author, Bernadette Perry, describes gamification as using gamebased mechanics, aesthetics and game thinking to engage people, motivate action, and promote learning (p. …

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.

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.

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.

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.

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

Advances in both parallel processing capabilities because of graphical processing units (GPUs) and computer vision algorithms have led to the development of deep neural networks (DNN) and their utilization in real-world applications. Starting from the LeNet-5 architecture of the 1990s, modern deep neural networks may have tens to hundreds of layers to solve complex problems such as license plate detection or recognition tasks. In this manuscript, we present a review of the state-of-the-art methods related to automatic license plate recognition. Since deep networks have demonstrated a remarkable ability to outperform other machine learning techniques, we focus only on neural network based license plate recognition methods. We highlight the particular types of networks, i.e., convolutional, residual recurrent, or long-short-term-memory, used for the specific tasks of license plate detection, extraction, or recognition in different existing works. The presented summary also highlights some of the most widely used data sets for comparison and shares the results reported in the reviewed papers. We also give an overview of the effects of fog, motion, or the use of synthetic data on license plate recognition. Finally, promising directions for future research in this domain are presented.

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.

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.

The purpose of this article is to propose a View Sharing Augmented Reality (AR) interface aimed at improving situation awareness (SA) during military operations. Battlefield Augmented Reality System (BARS), a mobile AR system, supports real-time battlefield situation awareness (SA) for mission execution through collaborative information sharing. Video-based View Sharing AR interface that provides the perspective of team members located remotely can enhance team-level SA. However, instances have been identified where providing the perspective of team members moving in directions different from the user’s path can lead to user confusion and have a negative impact on mission execution. In this study, we investigate the influence on SA when presenting the perspective of team members with different path direction through a View Sharing AR interface and to examine the impact of visual AR cues supporting spatial awareness on SA improvement. The study was designed to experience the View Sharing AR interface in a virtual reality (VR) environment using the Unity3D game engine. The experiments involved performing tasks to suppress enemies with three different path direction variances in perspective provision and receiving support from four visual AR cues. SA was measured through SA Global Assessment Technique (SAGAT) and Performance measurement. The research findings indicate that differences in path direction negatively affected SA, with the lowest SA observed when the path difference was 90°. Furthermore, visual AR cues, when providing Tramline cues, demonstrated the highest SA, showing interaction effects with path direction differences.

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

The purpose of this study was to investigate how a mobile collaborative augmented reality (AR) system affects learnersi¦ knowledge construction behaviors and learning performances. In this study, 20 undergraduate students were recruited and divided into dyads to discuss given questions with the assistance of mobile collaborative AR system named AR Physics. The participantsi¦ knowledge regarding elastic collision was evaluated through a pretest and a posttest that occurred right after the treatment. Learnersi¦ knowledge construction behaviors were qualitatively identified according to a selected coding scheme and then were analyzed by adopting sequential analysis. The results indicated that learners significantly gained their knowledge on the topic of elastic collision after completing the given task by manipulating AR Physics system. Furthermore, sequential patterns of learnersi¦ behaviors during knowledge construction activities were identified.

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.

The study of materials science concepts, such as crystallographic structures, poses well‐known pedagogical challenges due to the spatial visualization demands imposed by traditional two‐dimensional representations. To address these challenges, this paper presents CeldApp , a low‐cost mobile system that integrates interactive visualization and augmented reality to support the learning of core materials science topics. The system provides a set of modular 3D learning environments covering crystallization processes, crystal structures, and phase diagram analysis, enabling students to actively explore abstract concepts through direct manipulation and immediate visual feedback. The educational impact of the proposed system was investigated through a controlled pilot study employing a pretest–posttest design with parallel groups in an undergraduate materials science course. Learning gain, task completion time, and user experience were considered as evaluation measures. While between‐group differences in learning gain did not reach conventional levels of statistical significance, the experimental group exhibited a consistent positive trend with a moderate effect size. Notably, participants using the system demonstrated a statistically significant reduction in task completion time, suggesting improved efficiency in knowledge retrieval and problem‐solving. Qualitative feedback further indicated high perceived usability and strong educational value of the augmented reality components. Taken together, these findings suggest that accessible, low‐cost immersive visualization tools hold promise for mitigating spatial visualization challenges in materials science education and motivate further large‐scale investigation.