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This paper introduces an augmented-reality system that provides navigation facilities, generation of itineraries and services delivery. The approach offers the possibility of combining real sceneries with digital representations of places of interest and services for a given itinerary. The first level of the approach supports the identification of...
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... is possible (e.g., changing the type of itinerary), and route directions are displayed (e.g., to turn left to reach a historical place). In order to provide additional locational information to the user (e.g., name and description of points of interest, estimated distance to reach a goal) when a user selects an icon, (e.g., Hemiciclo a Juarez, left side of Figure 6) the view changes and shows a set of images of the place with additional semantic information (Figure 7). Figure 8 shows the interface that suggests several possible landmarks in the user neighborhood. To the right, one can see a slidebar (in yellow) to increase or decrease the distance radius to show some places of interest (when the distance increases more icons are presented but buy taking into account display constraints). ...
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... During this phase, a focus was placed on developing engaging and interactive AR experiences for tourists [32]. The third phase, known as the Technological Convergence Period (2014-2017), is characterized by the emergence of wearable devices such as smart glasses, and the integration of AR with advanced navigation technologies such as GIS, as well as imageprocessing techniques such as 3D modeling and image recognition [33]. Heritage education and museums also gained prominence during this phase [34], coinciding with the growth of MAR, allowing visitors to better understand and appreciate cultural Our study has identified nine thematic clusters. ...
... During this phase, a focus was placed on developing engaging and interactive AR experiences for tourists [32]. The third phase, known as the Technological Convergence Period (2014-2017), is characterized by the emergence of wearable devices such as smart glasses, and the integration of AR with advanced navigation technologies such as GIS, as well as image-processing techniques such as 3D modeling and image recognition [33]. Heritage education and museums also gained prominence during this phase [34], coinciding with the growth of MAR, allowing visitors to better understand and appreciate cultural tourism experiences. ...
Augmented reality has emerged as a transformative technology, with the potential to revolutionize the tourism industry. Nonetheless, there is a scarcity of studies tracing the progression of AR and its application in tourism, from early exploration to recent advancements. This study aims to provide a comprehensive overview of the evolution, contexts, and design elements of AR in tourism over the period (2002–2022), offering insights for further progress in this domain. Employing a dual-method approach, a bibliometric analysis was conducted on 861 articles collected from the Scopus and Web of Science databases, to investigate the evolution of AR research over time and across countries, and to identify the main contexts of the utilization of AR in tourism. In the second part of our study, a systematic content analysis was conducted, focusing on a subset of 57 selected studies that specifically employed AR systems in various tourism situations. Through this analysis, the most commonly utilized AR design components, such as tracking systems, AR devices, tourism settings, and virtual content were summarized. Furthermore, we explored how these components were integrated to enhance the overall tourism experience. The findings reveal a growing trend in research production, led by Europe and Asia. Key contexts of AR applications in tourism encompass cultural heritage, mobile AR, and smart tourism, with emerging topics such as artificial intelligence (AI), big data, and COVID-19. Frequently used AR design components comprise mobile devices, marker-less tracking systems, outdoor environments, and visual overlays. Future research could involve optimizing AR experiences for users with disabilities, supporting multicultural experiences, integrating AI with big data, fostering sustainability, and remote virtual tourism. This study contributes to the ongoing discourse on the role of AR in shaping the future of tourism in the post COVID-19 era, by providing valuable insights for researchers, practitioners, and policymakers in the tourism industry.
... parking bays, charging stations, stations for rental bikes) and their current availability state is becoming more and more important. For instance, modern routing algorithms integrate this information to minimize travel times [1,5,13] and augmented reality applications use such data to assist users [7,10]. Additionally, it is often required to estimate future resource availability: Routing can be improved if states of parking bays at arrival time are known [4]. ...
Accurate spatio-temporal information is crucial for smart city applications such as modern routing algorithms. Often, this information describes the state of stationary resources, e.g. the availability of parking bays, charging stations or the amount of people waiting for a vehicle to pick them up near a given location. Predicting future states of the monitored resources is often mandatory because a resource might change its state within the time until it is needed. It is often not possible to obtain complete history of a resource's state. For example, the information might be collected from traveling agents visiting the resource with an irregular frequency. Thus, it is necessary to develop methods which work on sparse observations for training and prediction. In this paper, we propose time-inhomogeneous discrete Markov models to allow accurate prediction even when the frequency of observation is very rare. Our new model is able to blend recent observations with historic data and also provide useful probabilistic estimates for future states. Since resource availability in a city is typically time-dependent, our Markov model is time-inhomogeneous and cyclic within a predefined time interval. We propose a modified Baum-Welch algorithm capable of training our model with sparse data. Evaluations on real-world datasets of parking bay availability show that our new method indeed yields good results compared to methods designed for training on complete data and non-cyclic variants.
... AR can overlay walking instructions to the user in order to locate the final destination. Some studies in this direction can be found in [6], [7], [8]. Remote vehicle navigation is another branch of navigation that has been enhanced by using AR systems. ...
Scientific facilities usually require the use of vehicles controlled remotely by an operator relying on the information provided by a camera. However, the operator lacks of depth perception, which makes difficult the navigation. Providing additional information by means of Augmented Reality (AR) may enhance the safety and accuracy of the navigation. AR has been used in outdoor navigation systems. However, the technologies for outdoor systems cannot be directly ported to indoor environments and hence new techniques are required. Although several works for AR-based human indoor navigation have been proposed, to our best knowledge there are no similar studies for assisted indoor remote vehicle navigation. In this paper, a new prototype for assisted indoor remote vehicle navigation is proposed. The prototypeprovides the operator with an augmented view of the remote scene and complemented with additional features. The prototype has been tested in a small-scale setup with promising results.
Navigation assistance systems have become integral to our daily routines, helping us to find our way through unfamiliar environments. However, their use may come at a price, as empirical evidence suggests a potentially harmful impact of these systems on our spatial abilities, including the acquisition of spatial knowledge. This could be remedied by giving users more freedom and involving them in the decision-making process. Therefore, we present a navigation system that combines augmented reality and Beeline Navigation (BeeAR). Here, the location of the destination is overlaid with a digital landmark and permanently displayed to the user via a visual, translucent AR display (without a map). Since the digital content is integrated into the real world, no mapping between the device and reality is required, potentially lowering the workload. Making one's own decisions along the route is expected to increase engagement with the environment, leading to increased acquisition of spatial knowledge. We compare BeeAR with findings from a previous study comparing Free Choice Navigation (FCN) and Turn-by-Turn (TBT) navigation conducted along the same routes on the outskirts of Vienna, Austria. Although BeeAR and FCN do not provide users with a map, BeeAR users could better retrace the walked route and remembered more points of interest along the route than FCN users. Participants of all three navigation conditions achieved a high configuration similarity between drawn points of interest and their true locations, albeit only one navigation condition included a map.
In this chapter, synergies between augmented reality (AR) and shared experiences are explored. The shared experiences (such as visiting a cultural site or a museum) can benefit from computer-supported collaborative work done in the context of maintenance, training, and simulation. With the wide availability and use of AR-enabled smartphones, it is now possible to create collaborative experiences built upon the knowledge gained from such industry-oriented training applications. This novel approach allows for a greater user engagement fostered by the collaborative nature of an AR shared space. Recent AR works allow for many users to observe the same superimposed object as the group and interact collaboratively with it, as users can see not only the other users but their actions and effects in the virtual elements. This methodology allows for group interaction around tangible cultural points of interest at different scales (such as ruins or buildings but also statues and paintings).
In this study, we combine augmented reality (AR) with the technique of assisted global positioning system to construct a guiding system of AR and design the guiding graphs metaphorically, so that the system interface operation is used more intuitively. We further investigate the availability of the system, and present an empirical study to statistically show that the guiding system of AR significantly outperforms that of plane map in terms of the finishing time of mission and correctness. Finally, according to the results of questionnaire of the system availability, we induct six essential factors influencing the guiding system availability of AR, namely guiding service usability factor, user esthetics of design factor, guiding service technique factor, guiding service creativity factor, guiding service entertainment factor, and guiding service practicality factor. The results of the study could be extended to other related studies. In terms of task completion time and accuracy rate, AR navigation is obviously better than the two plane map navigation modes. The users can find the direction of the destination within 7 s on average, and the accuracy rate is as high as 97.73%. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
