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As the next frontier in wireless technology, 6G represents the sixth generation of mobile communication. Expected to surpass the capabilities of 5G, 6G aims to provide unprecedented data speeds, ultra-low latency, and enhanced connectivity, unlocking new possibilities for advanced technologies like augmented reality, artificial intelligence, and the Internet of Things. It intertwines seamlessly with the Metaverse, a digital universe where users can interact with computer-generated environments, objects, and other users in real-time high-performance computing. This research attempts to explore the transformative domain of Metaverse integration in 6G Networks, delving into the potential landscape with a keen focus on emerging prerequisites, key performance indicators (KPIs), and future opportunities in the HPC environment. The integration of 6G and the metaverse signifies a fundamental shift in connectivity and user experiences, offering assurances of heightened data speeds, decreased latency, and inventive applications. Within this framework, the article introduces the all-encompassing structure of 6G Cloudification and Cloud Native Technologies, highlighting the critical role played by sophisticated cloud technologies in shaping the evolution of the metaverse ensuring the scalability, flexibility, and efficiency required to support the dynamic nature of immersive digital experiences. [ABSTRACT FROM AUTHOR]

Extended reality (XR) enables both new opportunities but also introduces new barriers for inclusion in society. Furthermore, XR is less researched than web, desktop and mobile applications. This position paper presents the concept of an XR platform for inclusion, with the purpose to make people on the autism spectrum and with other disabilities, more independent of help from others in everyday life situations. Based on previous research, our position is that, through current and future XR technologies combined with civic and artificial intelligence, it is possible to create individually personalised support for this purpose, grounded in practice to ensure validation. [ABSTRACT FROM AUTHOR]

Agriculture is the most crucial sector of the Indian economy. Lately, there has been a surge in the usage of technologies like deep learning and computer vision to make the process of agriculture modern and consequently, lessening the mistakes related to conventional processes. This work delivers a user-friendly, accessible, and novel approach for the detection, counting, and grading of tomatoes found on a farm. An Augmented Reality (AR) based mobile application is developed to obtain the images efficiently from a tomato farm in the pre-harvest stage subjected to open situations. The proposed approach uses Faster RCNN, a convolutional neural network model for detection of tomatoes from the input image on a large scale. The proposed model is trained and tested using 2083 images. The results are then analyzed for the overall performance of detection, segmentation, and classification of tomatoes. The results have examined the efficiency of the proposed mobile application and demonstrate the robustness it exhibits for the detection, grading and yield prediction of Tomatoes. [ABSTRACT FROM AUTHOR]

Augmented Reality has become a bridge from the virtual to the real world. This technology has been an implementable choice for fashion companies to provide more information and customization for their user's shopping experience. From the COVID-19 pandemic alongside technological globalization, fashion industries have to find a new way for customers to purchase products. All things considered, AR helped fashion industries keep customers attracted and satisfied. This paper is conducted in a Systematic Literature Review manner to review and compare the AR technologies used by fashion industries. Furthermore, the result would be a proposition of which Augmented Reality technology or platform option is feasible and implementable for the fashion industry. After comparing the technologies used in past papers and their technical and economic feasibility, we propose a 3-term plan. The short-term plan with zero cost and mobile platform-focused application, the medium-term plan with an upgraded version of the garment object from 2D images to 3D objects, and the long-term plan changing the platform used from mobile to a new device. We also conclude that artificial intelligence can also support and improve the augmented reality experience for customers in the fashion retail industry by implementing an AI-powered virtual assistant. [ABSTRACT FROM AUTHOR]

ICT tools based on abstract spaces can be considered as the "younger sibling" of GIS tools. While GIS tools based on real spaces, i.e. those that are easy for users to imagine, are developing more and more, tools based on abstract spaces are still in their infancy. The aim of this article is to show the possibilities and directions of application of ICT tools based on abstract spaces and to present the current state of their application. The article shows which elements of GIS technology can be used in tools based on abstract spaces and what differentiates the discussed types of spaces. The approach to the proposed tools was made from three points of view. First - the types of abstract spaces were presented. Second - the areas of their application were indicated along with the application of higher information functions (such as spatial data collection for abstract spaces, their single- and multi-area visualisation, environmental analysis and assessment, planning, inspiration and support of decision-making processes presented in abstract spaces). And thirdly, they were framed from the point of view of modern technologies such as AI (Artificial Intelligence), VR (Virtual Reality), AR (Augmented Reality) or hyperlinks. The reflections were concluded with an analysis of the current state of application of the technology in question in Polish public administration offices. The results of the surveys show that the proposed solutions are not currently used in city halls and are at the conceptual stage. The topic of AI is well known among the respondents. This is probably due to the popularity of the concept in popular science publications. Respondents show much less interest in the area of abstract spaces. Furthermore, they are of the opinion that their GIS solutions do not support this type of space, or if they do, they have no idea how to use it. [ABSTRACT FROM AUTHOR]

Intelligent Virtual Agents (IVAs) can provide users with a friendly experience and have a wide range of applications in the era of artificial intelligence. However, most of existing IVAs are designed for personal computers. Design and user studies of IVAs on smartphones are uncommon. Therefore, developing IVAs for smartphones is an interesting topic. Considering Augmented Reality (AR) technology can provide more potential application value for IVAs, we mainly investigate users' experiences of AR IVAs on smartphones in this paper. To make an IVA more suitable for a smartphone, a lightweight IVA's cognitive architecture is proposed. To find out the factors that affect users' interaction experiences, the effects of humanoid embodiment and emotional expressions of IVAs on users' perceptions and experiences are explored. A museum is used as a specific task scenario to measure users' experiences. Three forms of AR agents are evaluated in this scenario: a voice assistant without an entity, a humanoid IVA without emotional expressions, and a humanoid IVA with emotional expressions. The results show that compared with the voice assistant, a humanoid embodiment can significantly improve the user's experience, and compared with humanoid IVA without emotional expressions, a humanoid IVA with emotional expressions is more welcome. Moreover, we use the cloud model to describe the uncertainty of IVAs' actions (blinking and body orientation). The results show that the uncertainty of actions can increase the believability of IVAs. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) and Artificial Intelligence (AI) are technologies pioneers in innovation and alteration in several domains. AR allows the creation of an entirely new and interactive experience for users. However, there are several drawbacks in developing AR applications, such as the marker identification process and the creation of content itself. These are very time-consuming procedures and require ad-hoc development. The advantages of using AI to solve AR limitations have recently been explored in literature. Motivated by these findings, in this paper it is proposed DeepReality, a software toolkit plug-in for Unity 3D. It is conceived for allowing developers to integrate any Deep Learning (DL) models into Unity, through AR Foundation and Barracuda inference engine. DeepReality is aimed at simplifying and streamlining the usage of DL models in conjunction with AR. As such, users skilled in Unity and DL can easily create mobile applications (iOS and Android) to: extract visual features of real-world objects (framed with the device camera) via DL; Show on-screen content on top of those real-world objects, via AR. DeepReality performs object semantic processing within the scene, and extended semantic effects for incongruent objects, overcoming the environmental tracking, which is feature-based. In order to test DeepReality usability, experiments have been performed on the execution time and memory usage data, demonstrating the feasibility and possibility of integrating and using DNNs models in mobile applications for AR. The complexity analysis confirms that DeepReality can be completely executed on mobile devices. DeepReality is also open-source and it is freely available in the Unity asset store. By fostering accessible AI-AR integration, DeepReality addresses key shortcomings in existing approaches, encapsulating contributions such as versatile DL integration, open-source accessibility, operational validation, and comprehensive metrics analysis. DeepReality empowers developers to transcend boundaries, enriching AR applications with AI's transformative potential. Our proposed framework fosters benchmarking, comparison, and a future harmonised by AR-AI synergy. [Display omitted] • DeepReality is an open-source toolkit, freely available in the Unity asset store. • DeepReality integrates Deep Learning models for streamlined mobile apps. • DeepReality leverages AR Foundation and Barracuda inference engine. • It demonstrates efficient execution and memory usage in mobile AR. • Complexity analysis confirms that it can be fully executed on mobile devices. [ABSTRACT FROM AUTHOR]

The article discusses the directions and trends in the development of digitization and data analysis in industrial applications. Particular attention was paid to the issue of digitization of production, which gradually enters all layers of the production system, starting from the layer of investment management, production planning, control, communication up to the level of intelligent object devices. Digitization is one of the basic pillars of the Industry 4.0 initiative and at the same time a response to the growing requirements of the global industry by creating digital models of processes implemented in production companies and conducting simulations in order to improve and optimize them. Therefore, special attention was paid to the possibility of using modern tools supporting the registration of digital data and their quick processing, which include AR technology and artificial intelligence. [ABSTRACT FROM AUTHOR]

With the intensifying impacts of the climate crisis becoming more severe day by day, the industries have been compelled to accelerate the implementation of sustainable practices, especially in the fashion industry, as a motivation behind this study. Although, the utilization of digitalization and artificial intelligence as a means of sustainable applications is increasingly growing, the current literature is mainly focused only on conducting fashion shows using augmented reality googles, there is an obvious gap in the literature addressing the mobile applications capabilities in terms of artificial intelligence and augmented reality. Hence, the purpose of this study is to examine artificial intelligence/augmented reality - powered mobile applications from a consumer point of view. In pursuit of this aim, several alternative applications were reviewed, the factors affecting the consumer's decision were identified, and the Organization, Rangement et Synthese de Donnes Relationnelles (ORESTE) technique was utilized as a multi-criteria decision-making technique for the analysis as a contribution of artificial intelligence in the engineering applications. Additionally, the ORESTE technique has been extended with Fermatean Fuzzy sets to make a theoretical contribution to the literature as the main numerical achievement. The findings of the study illustrate that (i) the consumers prefer camera-assisted measurement applications, and (ii) the applications offering synchronized suggestions with existing fashion brand's products are preferred. Moreover, the study provides a significant illustration of the use of artificial intelligence powered mobile applications as an actual practical implication, and it creates a suitable ground for the sector authorities to take strategic decisions as a managerial implication. [ABSTRACT FROM AUTHOR]

Intelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major deployments concern in-person customer services, chatbots and messaging tools, business intelligence tools powered by machine learning, and virtual reality & augmented reality. Moreover, we performed a survey (n = 178), asking respondents about their perceptions and attitudes toward AI, including its implementation within a hotel space. The paper attempts to discuss how the hotel industry can be motivated by potential customers to apply selected AI solutions. In our opinion, these results provide useful insights for understanding the phenomenon under investigation. Nevertheless, since the results are not conclusive, more research is still needed on this topic. Future studies may concern both qualitative and quantitative methods, devoted to developing models that: a) quantify the potential benefits and risks of AI implementations, b) determine and evaluate the factors affecting the AI adoption by the customers, and c) measure the user (guest) experience of the hotel services, fueled by AI-based technologies. [ABSTRACT FROM AUTHOR]

Human cancer is a multifaceted decease. Throughout the years several techniques and technologies have been proposed for the diagnosis and treatment of such deceases. However, the technological advances in the field of Information and Communication Technologies (ICT), Augmented Reality (AR), and Artificial Intelligence (AI), can facilitate during the diagnosis and prediction processes. This paper presents a conceptual framework for the visualization of Magnetic resonance imaging (MRI) scans, the data acquisition and analysis from patients based on AI algorithms and AR. Furthermore, the preliminary development of the framework is presented, and future developments are discussed based on the implications faced. [ABSTRACT FROM AUTHOR]

The Industry 4.0 vision proposes a seamless integration of several modern concepts and technologies, such as the Internet of Things (IoT), artificial intelligence, or robotics, to capture and contextualize data to improve the manufacturing processes. In this respect, Industry 4.0 is all about information and connectivity. Mixed reality (MR) takes the data collected by IoT systems and helps workers by visualizing contextualized data in real time. Human-Computer Interaction research has shown that MR can be advantageous in various application scenarios. However, there is a gap between research and practice when it comes to real world scenarios. So the question arises whether MR is already suitable for efficiently supporting employees in their daily work in industrial settings. To answer this question, we examined two maintenance scenarios in the field of intralogistics: (i) the maintenance of roller conveyors and (ii) the alignments of containers in shuttle warehouses using the Microsoft HoloLens. This paper (i) describes the scenarios and the specific challenges they pose, (ii) presents the prototypes that have been developed, and (iii) discusses the results of user studies that have been conducted to evaluate the practical applicability by presenting inhibiting and facilitating factors. In summary, although MR technology itself seems to be very promising in the scenarios presented, further research on hardware ergonomics and intuitive interaction design is needed. [ABSTRACT FROM AUTHOR]

Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) can be considered as the cornerstones of the lifecycle of a manufacturing asset. Since the above-mentioned processes often involve multiple engineers, from different departments even from different companies, it is crucial to ensure the flawless communication between the different individuals as well as to make the design process more intuitive. In the era of digitalization and Internet of Things, digital technologies such as Mixed Reality (MR) are utilized from engineers in order to leverage the capabilities of existing computer aided tools (CAx). Therefore, in this research work, the design and development of a Cloud-based and Mixed Reality-based framework is presented. The purpose of the framework is to facilitate engineers during the design and manufacturing phase of new components by providing a mobile application and common design tools via MR graphical user interfaces (GUI). Further to that, taking into consideration the advanced capabilities of MR devices in terms of user interaction, special emphasis is given on the interaction of engineers with the holograms of the components via simple hand gestures. The resulting 3D geometries can be imported in CAD suites either for further development or for manufacturing the designed component. The applicability of the proposed framework is tested and validated in a laboratory-based machine shop. [ABSTRACT FROM AUTHOR]

Cerebrovascular Accident (CVA) is the second leading cause of death in the world while also being the plurality cause of disability in adults. A definitive factor for survivability and successful recovery of a patient is the time passage from the onset of symptoms to the administration of medical treatment. This paper introduces Stroke Help, a mobile application utilizing various mobile technologies together with Artificial Intelligence algorithms in order to quickly detect CVA in either the user or someone the user is concerned about. The application implements the well known F.A.S.T. test making use of real-time face detection, speech recognition, and other artificial intelligence techniques applied over common sensors found in modern mobile phones. In addition of detecting whether there is a high probability a patient is suffering from a stroke, the application will calculate an approximated Japan Urgent Stroke Triage (JUST) score utilized in identifying the specific type of stroke, very important information for medical staff to potentially reduce the time required to evaluate the patient before beginning the appropriate treatment. We will also present additional crucial functionalities such as notifying contacts, identifying the closest clinics capable of treating CVA, making our solution a complete approach. [ABSTRACT FROM AUTHOR]

The evolution of artificial intelligence (AI) and big data resulted in the full potential realization of technologies through convergence. Tremendous acceptance, adoption and implementation of the United Nations Sustainable Development Goals (SDG) Agenda 2030, has resulted in original equipment manufacturers (OEM) developing various designs of rotary machines in a bid to improve energy efficiency, with more improvements expected in the coming decade. An effective technique to manage energy efficiency in the smart grid is through integration of demand side management, inclusive of optimization of rewinding of an electric motor in a machine shop. This paper aims to conceptualize application of AI and augmented reality (AR) towards process visibility of remanufacturing rotary machine stators by robotic vision. SLT is the triangulation methodology used in laser scanning for 3D modelling, and instantaneous condition assessment of the core. A pre-defined robotic path is used towards identification of features for range image acquisition. Therefore, the potential of industry 4.0 in resuscitation of end-of-life products through service remanufacturers by RE in a rewinding shop are presented. [ABSTRACT FROM AUTHOR]

Disruptive innovation technologies have made their way in the field of academia during the past few years. A plethora of literature exists investigating the applications of various disruptive technologies in the field of engineering education. The directions for future research however are still obscured by the copious amount of literature having split opinions and conflicting results which necessitates a review of current state of the research. This paper clarifies the underlying concept of the theory. The authors then critique and summarize the research on present state of implementation mainly focusing on the field of engineering education. The future scope for the research is also discussed keeping in the mind the upcoming new technologies such as mobilecomputing, wearable technologiesand internet of things combined with machine learning. [ABSTRACT FROM AUTHOR]

Development in information technology has resulted in revolutionizing all aspects of life and this revolution has been realized as Industrial Revolution 4.0 (IR4.0). The IR4.0 will reduce the gap between digital and physical world. Keeping ultramodern developments in view, an amalgamation of physical and digital systems will prove to be revolutionary. To elevate from the current state universities are required to prepare curriculum, academicians and students alike. Thus academia should weigh their capabilities putting effort to equip our generations with latest knowledge and skills to face future realism. Universities are required to enhance their approach and methods of education. Latest technologies such as Big Data Analytics, Artificial Intelligence, Augmented Reality, and Internet of Things, Cloud Computing and other advancements need to be focused in order for students to learn its application. This paper is based on qualitative research along with a deductive approach focused towards redesigning curriculum and teaching practices in line with IR4.0 practices. The research is focused upon various emerging challenges related to fundamental elements and objectives in academia. Based on the qualitative research a curriculum matrix has been proposed, the suggested matrix will enable universities to enhance their current curriculum in line with the technological competencies required in the upcoming era of Industry 4.0. [ABSTRACT FROM AUTHOR]

In our generation the information systems evolve with new technologies: augmented reality (AR), IoT, artificial intelligence, blockchain etc. Anymore they perform information exchange by sensors. It is estimated that the systems will be in a state of extreme interaction and reach 50 billion devices connected in Internet in 2020. We know that everything around us will be in interaction and they will do everything without any need of human interference. For example, when our dishwasher is full, it will start to wash automatically, or when the run out of the gasoline, our car will drive to the nearest station, or even when a burglar is entered to our house, it will automatically be detected and be announced to the police office. In business life, the processes will be automatical in maximum level and this technology will increase productivity and efficiency. Next to mobile technology, it is thought that these new generation information systems (IS) will take the biggest place in our lives. AR also will be integrated to these systems to augment the information in real world. Humanity will augment its habitat in an innovative way thanks to these AR based IS. This paper surveys the current state-of-the-art AR systems related with aerospace & defense, industry, education, medical and gaming sectors. The connection of AR based IS and innovation is explained with a technological insight. In addition to international use cases HAVELSAN's use cases are also given that are performed from the aspect of applied open innovation strategy. This strategy is addressed specific to the implemented activities of AR based IS. [ABSTRACT FROM AUTHOR]

Development in information technology has resulted in revolutionizing all aspects of life and this revolution has been realized as Industrial Revolution 4.0 (IR4.0). The IR4.0 will reduce the gap between digital and physical world. Keeping ultramodern developments in view, an amalgamation of physical and digital systems will prove to be revolutionary. To elevate from the current state universities are required to prepare curriculum, academicians and students alike. Thus academia should weigh their capabilities putting effort to equip our generations with latest knowledge and skills to face future realism. Universities are required to enhance their approach and methods of education. Latest technologies such as Big Data Analytics, Artificial Intelligence, Augmented Reality, and Internet of Things, Cloud Computing and other advancements need to be focused in order for students to learn its application. This paper is based on qualitative research along with a deductive approach focused towards redesigning curriculum and teaching practices in line with IR4.0 practices. The research is focused upon various emerging challenges related to fundamental elements and objectives in academia. Based on the qualitative research a curriculum matrix has been proposed, the suggested matrix will enable universities to enhance their current curriculum in line with the technological competencies required in the upcoming era of Industry 4.0. [ABSTRACT FROM AUTHOR]

While the Industry 4.0 is idolizing the potential of an artificial intelligence embedded into ''things", it is neglecting the role of the human component, which is still indispensable in different manufacturing activities, such as a machine setup or maintenance operations. The present research study first proposes an Industrial Internet pyramid as emergent human-centric manufacturing paradigm within Industry 4.0 in which central is the role of a Ubiquitous Knowledge about the manufacturing system intuitively accessed and used by the manufacturing employees. Second, the prototype of a Service-oriented Digital Twin, which leverage on a flexible ontology-oriented knowledge structure and on augmented reality combined to a vocal interaction system for an intuitive knowledge retrieval and fruition, has been designed and developed to deliver this manufacturing knowledge. Two test-beds, complimentary for the problems in practice (the former on the maintenance-production interface in a large enterprise, the latter majorly focused in production and setups in a small and medium enterprise), show the significant benefits in terms of time, costs and process quality, thus validating the approach proposed. This research shows that a human-centric and knowledge-driven approach can drive the performance of Industry 4.0 initiatives and lead a Smart Factory towards its full potential. [ABSTRACT FROM AUTHOR]

This project is about design and implementation of Augmented Reality cloud recognition power platform for 3D Entity Objects. Typical power operations include equipment inspection, equipment maintenance, emergency repair, reverse brake operation, line operation and so on. Combining with the characteristics of electric power operation site, to improve the on-site operation mode, through the interactive collaboration such as terminal multidimensional exhibition, backstage data fusion, and custom services, the clouds recognition system will provide grid on-site an automatic and intelligent new solution based on AR. [ABSTRACT FROM AUTHOR]

Many intelligent systems, such as assistive robots, augmented reality trainers or unmanned vehicles, need to know their physical location in the environment in order to fulfill their task. While relying exclusively on natural landmarks for that task is the preferred option, their use is somewhat limited because the proposed methods are complex, require high computational power, and are not reliable in all environments. On the other hand, artificial landmarks can be placed in order to alleviate these problems. In particular, square fiducial markers are one of the most popular tools for camera pose estimation due to their high performance and precision. However, the state-of-the-art methods still perform poorly under difficult image conditions, such as camera defocus, motion blur, small scale or non-uniform lighting. This paper proposes a method to robustly detect this type of landmarks under challenging image conditions present in realistic scenarios. To do so, we re-define the marker identification problem as a classification one based on state-of-the-art machine learning techniques. Second, we propose a procedure to create a training dataset of synthetically generated images affected by several challenging transformations. Third, we show that, in this problem, a classifier can be trained using exclusively synthetic data, performing well in real and challenging conditions. Different types of classifiers have been tested to prove the validity of our proposal (namely, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN) and Support Vector Machine (SVM)), and statistical analyses have been performed in order to determine the best approach for our problem. Finally, the obtained classifiers have been compared to the ArUco and AprilTags fiducial marker systems in challenging video sequences. The results obtained show that the proposed method performs significantly better than previous approaches, making the use of this technology more reliable in a wider range of realistic scenarios such as outdoor scenes or fast moving cameras. [ABSTRACT FROM AUTHOR]

The integration of Augmented Reality and Building Information Modelling is a promising area of research; however, fragmentation in literature hinders the development of mature BIM-based AR platforms. This paper aims to minimise the fragmentation in the literature by identifying the key functions that represent the essential capabilities of BIM-AR platforms. A systematic literature review is employed to identify, categorise, and discuss the key functions. The outcome of this paper identifies six key functions: positioning (P), interaction (I), visualisation (V), collaboration (C), automation (A), and integration (T). These key functions act as the foundation for an evaluation framework that can assist practitioners, developers, and researchers with assessing the requirements of the targeted application area, and hence be better informed on the appropriate devices, software, and techniques to use. Finally, this paper emphasises the importance of industrial-academic collaboration in BIM-AR research and suggests prospects for automation through the application of artificial intelligence. [Display omitted] • BIM-AR platforms can be evaluated based on their key functions. • The key functions are the building blocks of any proposed BIM-AR platform. • Key functions are executed to varying levels of development based on the use case. • Future research is needed to define the maturity of each function for AR use cases. [ABSTRACT FROM AUTHOR]

Artificial Intelligence-based systems are required to interact with dynamic environments to continuously learn, retain and effectively utilize knowledge. Present AI-based systems scarcely exhibit this ability and mostly follow an isolated learning paradigm. In contrast, a human brain goes through a continual learning process by learning through experiences, retaining the learned knowledge, and using this knowledge on present tasks. Inspired by the learning of a human brain, we propose a continual learning methodology for point cloud registration which is a key component for 3D reconstruction and Augmented Reality (AR) localization. A major challenge that is faced in this context is the accurate correspondence of 3D points. Current learning-based registration techniques perform substantially, but these methods do not take into account the relations among point clouds obtained during sequential scans and perform registrations among point cloud pairs independently. Our proposed methodology increases the expressiveness of point clouds under consideration by using a novel continual graph network architecture with an attention mechanism that utilizes the learning from the association of the previous point cloud pairs to associate and register points in the current pair. The methodology implemented in PYTHON is evaluated on various challenging benchmark datasets including the Oxford, the 3DMatch, the KITTI, and the ETH dataset. The methodology is thoroughly evaluated under various scenarios including correspondence performance, registration performance, and generalization abilities. The results show a remarkable performance improvement as compared to the state-of-the-art methods. More critically, the proposed method offers exemplary globalization performance across unseen datasets and new scenarios. • Continual graph attention network for point cloud registration. • Brain inspired learning with knowledge consolidation, retention and reusability. • Generalized model capable of estimating registration on unseen data. • Performance analysis for point cloud registration in indoor and outdoor environment. • Significant performance increase as compared to other neural network methods. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is an augmented depiction of reality formed by overlaying digital information on an image of objects being seen through a device. Artificial Intelligence (AI) techniques have experienced unprecedented growth and are being applied in various industries. The combination of AR and AI is the next prominent direction in upcoming years with many industries and academia recognizing the importance of their adoption. With the advancements in the silicone industry that push the boundaries of Moore's law, processors will be less expensive, more efficient, and power-optimized in the forthcoming years. This is a tremendous support and necessity for an AR boom, and with the help of AI, there is an excellent potential for smart industries to increase the production speed and workforce training along with improved manufacturing, error handling, assembly, and packaging. In this work, we provide a systematic review of recent advances, tools, techniques, and platforms of AI-empowered AR along with the challenges of using AI in AR applications. This paper will serve as a guideline for future research in the domain of AI-assisted AR in industrial applications. • The trend of AR and AI applications in the industry is analyzed. • Types of AI techniques for mobile AR applications are provided. • Various platforms and frameworks for AR applications are illustrated. • Usage of AR/AI in various manufacturing sectors is reviewed. • Challenges for implementing AR & AI techniques in the industry are discussed. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) in the traditional systems have a problem that the drawn objects are always displayed in the foreground because 3D models by AR are superimposed later than the picture of the actual world. This paper proposed a system to produce a realistic picture of AR in accordance with every depth. We developed a prototype system to verify the effect of the method. The prototype system was developed by focusing on a human hand. This paper utilized a Leap Motion Controller as a motion capture device to acquire the depth data of the hand and fingers. [ABSTRACT FROM AUTHOR]

Abstract: The article presents a first hypothesis of a business model for an intelligent LBS for personal mobility. This business model has been developed inside FP7 i-Tour project. i-Tour stands for “intelligent Transport system for Optimized URban trips” and it is a so-called Collaborative Focused Research Project presented to the call on Surface Sustainable Transport topic “SST.2008.3.1.2 Intelligent mobility systems and multi-modal interfaces for transport of passengers”. In order to develop a business model for next generation personal mobility systems, an as-is analysis has been performed, resulting in a scenario characterized by the wide diffusion of wireless connections at urban and regional scale (e.g. UMTS, Wi-Fi or WiMax); by info-mobility services promoting multi-modal transport; by the development of transportation services based on localization technologies. The business model has been, then, proposed taking into account two different business strategies and two different organizations, and developing a financial analysis, including a break-even analysis useful to support a first feasibility study for a distinctive go-to-market strategy. [Copyright &y& Elsevier]

Abstract: In augmented reality systems, registration is one of the most difficult problems currently limiting their applications. In this paper, we propose a generalized registration method using projective reconstruction technique in computer vision. This registration method is composed of embedding and tracking. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In this stage, any arbitrary two unrelated images or any 3×4 projective matrices with rank 3 can be used to calculate the 3D pseudo-projective coordinates of the four specified points. In the tracking process, these 3D pseudo-projective coordinates are used to track the four specified points to compute the registration matrix for augmentation. The proposed method is simple, as only four points need to be specified at the embedding stage, and the virtual object can then be easily augmented onto a real scene from a video sequence. One advantage is that the virtual objects can still be superimposed on the specified regions even when the regions are occluded in the video sequence. Another advantage of the proposed method is that the registration errors can be adjusted in real-time to ensure that they are less than certain thresholds that have been specified at the initial embedding stage. Several experiments have been conducted to validate the performance of the proposed generalized method. [Copyright &y& Elsevier]

In the last decade, both Industry 4.0 technologies and the circular economy have expanded exponentially and they have received epistemological attention. However, there is a lack of studies about the influence that each of these technologies has on the main areas of action covered by the circular economy. This study responds to this gap by investigating the influence of the major technologies: Additive Manufacturing, Artificial Intelligence, Artificial Vision, Big Data and Advanced Analytics, Cybersecurity, Internet of Things, Robotics, and Virtual and Augmented Reality on the main areas of action covered by the circular economy. Namely, reduction of inputs consumption, reuse, recovery, recycling and reduction of waste and emissions. An initial study, based on a survey of 120 project managers, and a multiple case study of 27 projects, through 31 personal interviews and review of internal and external documentation have been conducted in order to investigate the real influence of each technology on the circular economy. Overall, the results confirm the existence of a wide range of influences that Industry 4.0 technologies offer to companies for improved circularity. These improvements are mainly related to reduce material and energy consumption, and waste and emissions generation. However, there are important differences between the potential impacts of each technology. In particular, there is most evidence of the positive impact of additive manufacturing and robotics. Likewise, the results obtained suggest the need to continue exploring the new impacts generated by the continuous development and integration of technologies. • I40Ts must serve to support the transition to a CE. • Mainly, these technologies facilitate reductions in consumption, waste and emissions. • Reuse, Recovery and Recycling deserve greater consideration when adopting I40Ts. • In addition to additive manufacturing, robotics positively influences the 5Rs • The integration of I40Ts is needed to maximize improvements to the CE. [ABSTRACT FROM AUTHOR]

Highway work zones are considered among the most hazardous working environments. In 2018 alone, 124 workers lost their lives to fatal accidents. The lack of predictive safety systems that notify workers of upcoming dangers in advance is a major reason to blame in the highway maintenance and operation community. This article presents an integrative design framework for bringing recent advances in Augmented Reality (AR) and Artificial Intelligence (AI) to enhance the safety of highway workers through real-time multimodal notifications on-spot. To this end, this article conceptualizes and co-designs three major pillars: (1) AR user interface design for multimodal notification, (2) real-time AI at the edge for vehicle detection/classification from distance, and (3) real-time wireless communication in work zone setting to enable latency-aware operation between AI and AR components. Our early results demonstrate that we can achieve 24.83 FPS end-to-end execution latency on the Xavier AGX Jetson board with 48.7% m AP on BDD100K dataset, and a real-time communication covering 120 meters with an average latency of 5.1 ms at the farthest distance. Our mixed-method user research also reveals an acceptable level of excitement and engagement from the body of highway workers toward both the proposed technology and the designed user interface. Overall, this article provides a proof-of-concept toward AI-enabled AR safety systems in highway work zones. [ABSTRACT FROM AUTHOR]

With the extensive adoption of artificial intelligence (AI), construction engineering and management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions in CEM has become the current research focus, it needs to be comprehensively understood. In this regard, this paper presents a systematic review under both scientometric and qualitative analysis to present the current state of AI adoption in the context of CEM and discuss its future research trends. To begin with, a scientometric review is performed to explore the characteristics of keywords, journals, and clusters based on 4,473 journal articles published in 1997–2020. It is found that there has been an explosion of relevant papers especially in the past 10 years along with the change in keyword popularity from expert systems to building information modeling (BIM), digital twins, and others. Then, a brief understanding of CEM is provided, which can be benefited from the emerging trend of AI in terms of automation, risk mitigation, high efficiency, digitalization, and computer vision. Special concerns have been put on six hot research topics that amply the advantage of AI in CEM, including (1) knowledge representation and reasoning, (2) information fusion, (3) computer vision, (4) natural language processing, (5) intelligence optimization, and (6) process mining. The goal of these topics is to model, predict, and optimize issues in a data-driven manner throughout the whole lifecycle of the actual complex project. To further narrow the gap between AI and CEM, six key directions of future researches, such as smart robotics, cloud virtual and augmented reality (cloud VR/AR), Artificial Intelligence of Things (AIoT), digital twins, 4D printing, and blockchains, are highlighted to constantly facilitate the automation and intelligence in CEM. Unlabelled Image • A systematic review under both scientometric and qualitative analysis for the topic is provided. • A scientometric review is performed on 4,473 journal articles published in 1997–2020. • AI's main benefits including modeling and pattern detection, prediction, and optimization • Special concerns have been put on six state-of-the-art applications of AI in CEM. • Key directions of future studies, like smart robotics, digital twins, and blockchains are provided. [ABSTRACT FROM AUTHOR]