Integrated BLE and PDR Indoor Localization for Geo-Visualization Mobile Augmented Reality

Unlike traditional visualization methods, augmented reality (AR) inserts virtual objects and information directly into digital representations of the real world, which makes these objects and data more easily understood and interactive. The integration of AR and GIS is a promising way to display spatial information in context. However, most existing AR-GIS applications only provide local spatial information in a fixed location, which is exposed to a set of problems, limited legibility, information clutter and the incomplete spatial relationships. In addition, the indoor space structure is complex and GPS is unavailable, so that indoor AR systems are further impeded by the limited capacity of these systems to detect and display location and semantic information. To address this problem, the localization technique for tracking the camera positions was fused by Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). The multi-sensor fusion-based algorithm employs a particle filter. Based on the direction and position of the phone, the spatial information is automatically registered onto a live camera view. The proposed algorithm extracts and matches a bounding box of the indoor map to a real world scene. Finally, the indoor map and semantic information were rendered into the real world, based on the real-time computed spatial relationship between the indoor map and live camera view. Experimental results demonstrate that the average positioning error of our approach is 1.47 m, and 80% of proposed method error is within approximately 1.8 m. The positioning result can effectively support that AR and indoor map fusion technique links rich indoor spatial information to real world scenes. The method is not only suitable for traditional tasks related to indoor navigation, but it is also promising method for crowdsourcing data collection and indoor map reconstruction.

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

At present, indoor location-based service has become a hot topic. The traditional approaches that rely on professional equipment and expertise to collect indoor maps has limited the rapid development of indoor location-based services. Adopting low-cost crowdsourcing methods to construct and maintain indoor maps with various sensors integrated in smart phones by common users is a development trend of constructing indoor map. The existing crowdsourcing-based indoor topology construction methods mostly use the pedometer based PDR (Pedestrian Dead Reckoning) to infer user trajectories, which suffers from the problem of accumulated estimation errors. To reduce the error of pedestrian dead reckoning and improve the accuracy of the indoor topology construction, we propose a novel indoor topology construction algorithm based on the user closed trajectory fusion. The algorithm requires the user to start and end a trajectory loop at the same location when collecting data. Based on this trajectory loop, we can perform the forward and backward dead reckoning starting from the starting and the ending point of the path, respectively. For instance, after completing the forward path inference, we can swap the starting point with the ending point, and then perform the reverse path inference. Last, we aggregate the coordinates obtained from the forward and reverse path inferences with the different weight. The weight is defined to be proportional to the confidence of the PDR, i.e., inversely proportional to the walking time from the starting location of path inference. Compared to the traditional unidirectional trajectory inference method, our proposed algorithm can greatly reduce the accumulated error of dead reckoning by aggregating the bidirectional trajectory inference. To improve the accuracy of heading estimation of each step, we Ieverage a radial Gaussian function to filter the compass noise, and adopt the multi-strategy fusion mechanism based on the difference of direction estimation using the gyroscope and compass. The paper further introduces the external contour of the building to calibrate the direction of the indoor topological path, and improves the accuracy of the indoor topological path construction. The experimental results shows that our proposed crowdsourcing-based indoor topology construction algorithm using the bidirectional trajectory fusion scheme outperforms the traditional indoor topology construction algorithm that uses only the forward PDR and can obtain an average map accuracy of 0.40-meter.

Recupera algunos de los elementos menos estudiados y reconocidos en el ensayo latinoamericano: su profunda vocación de reflexión, diálogo y mediación intelectual; su plasticidad y apertura a la búsqueda del sentido; su vínculo con la sociabilidad, la conversación y la generación de un espacio simbólico de encuentro; su capa cidad de establecer una nueva retroalimentación entre lectura y escritura.

The present study investigated the impact teaching academic vocabulary through an augmented reality (AR) approach had on acquisition and retention as compared to using a more traditional flash card based approach. 29 high school students ranging from 9th to 11th grade followed the pattern of a 10 word vocabulary pre-test, being taught those words through respective alternating AR and traditional vocabulary methods, and post-tested one week from the date of teaching. At the end of the testing and teaching process, the unit scores were compared to find if any differences occurred. Analysis revealed that there is a significant difference between the two teaching methods. Participants scored better in the AR unit as compared to the traditional unit. Furthermore, participants also reported greater satisfaction with the AR method because it held their attention, gave them something to focus on, and was overall more engaging. Comparatively, participants found the traditional method not engaging, however, they were comfortable with the traditional method because it is what they are comfortable with in the classroom. Given the curiosity of using AR in the classroom, more research could be conducted to find patterns in participant performance across all academic content areas as well as other uses for AR in the classroom. 

This study presents a method for analyzing workers’ behavior using indoor positioning technology and field test in the workplace. Recently, various indoor positioning methods, such as Wi-Fi, Bluetooth low energy (BLE), visible light communication, Japan’s indoor messaging system, ultra-wide band (UWB), and pedestrian dead reckoning (PDR), have been investigated. The development of these technologies allows tracking of movement of both people and/or goods in indoor spaces, people and/or goods behavior analysis is expected as one of the key technologies for operation optimization. However, when we use these technologies for human tracking, there are some problem as follows. 1) Many cases need to use dedicated facilities (e.g. UWB). 2) When we use smartphone as sensing device, battery depletion is one of the big problem (especially using PDR). 3) the accuracy is instability for tracking (e.g. Wi-Fi). Based on these matters, in this study we designed and developed an indoor positioning system using BLE positioning. And, we adopted smartphone for business use as sensing device, developed a smartphone application runs on android OS. Moreover, we conducted the field test of developed system at Itoki Corporation’s ITOKI Tokyo Innovation Center, SYNQA, office (Tokyo, Japan). Over 40 workers participated in this field test, and worker tracking log data were collected for 6 weeks. We analyzed the characteristics of the workers’ behavior using this log data as a prototyping.

Mobile and pervasive computing enabled a new realm of possibilities into the indoor positioning domain. Although many candidate technologies have been proposed, no one can still adapt to every use case. A case centered design and the implementation of the solution within the specific domain is the current research trend. With the rise of Bluetooth Low Energy (BLE) Beacons, i.e., platforms used to interact digitally with the real world, more standard positioning solutions are emerging in different contexts. However the reachable positioning accuracy with this technology is still unacceptable for some real applications (e.g., in the healthcare sector or the emergency management). In this paper, an hybrid localization application coupling a real time model based Pedestrian Dead Reckoning (PDR) technique and the analysis of the Received Signal Strength Indicator (RSSI) of BLE beacons is proposed. In particular, the smartphone application is composed by three main real time threads: a model based step length estimation, heading determination and the fusion of beacon information to reset the position and the drift error of the PDR. In order to give soundness to our approach we firstly validated the step length smartphone app with a stereo-photogrammetric system. The whole proposed solution was then tested on fifteen healthy subjects.

The Covid-19 pandemic has hit Indonesia since the beginning of 2020 and is still continuing. The education sector has experienced a considerable impact, face-to-face learning must be replaced with all-online activities. Many problems arise from online learning, such as inadequate infrastructure, an ineffective learning system and difficulties in understanding the material. Medical education has an impact on the current situation because most of the learning uses infrastructure and direct practice, it is necessary to have alternative learning methods that can improve the quality of learning. Currently, video conference media technology can assist learning activities so that instructors can still explain material to students through virtual media. For medical students who need practice and infrastructure facilities, this technology is still not enough to support their learning media. The idea came up “Application of Learning Module in Health Field based on Extended Reality (sub chapter: Augmented Reality)” This application combines Virtual Reality, Augmented Reality, and Mixed Reality. Augmented reality is a technology that is suitable to be implemented in medical learning because students do not need to prepare anything to perform simulations, just devices and internet networks. For feeding and drinking to the elderly, some items are needed to start the practicum, with this augmented reality there is no need to prepare all of these items, and also reduce contact with other people during a pandemic like this. Users can connect to each other in different devices and environments according to their respective devices. In this application, Augmented Reality acts as a technology that combines the real and virtual worlds by adding virtual objects into the real world. Users can use devices that have cameras such as cellphones or laptops so they can see virtual objects. This virtual object can be seen by all users and each user is able to interact with it in real time. As for the temporary test results, it was found that Augmented Reality has been tested and integrated with other immersive technologies with Web-XR. Interaction in Augmented Reality on Web-XR using a touch screen as well as several nursing SOP have been created and simulated using Augmented Reality technology. As for the final test in this final project, Augmented Reality technology based on WebXR has been running smoothly according to the specifications of the device used to open WebXR. If the device used to access WebXR has a high specification, then WebXR will run optimally, otherwise when the device specification is low, WebXR will not run optimally. The interaction used in WebXR-based Augmented Reality is touchscreen. The author tested this system to the user, the user here is a medical student. testing proves that this system is very helpful in terms of efficiency, users don't need to prepare tools repeatedly when they want to do simulations, just open WebXR and users can do the simulations provided. In testing the system, the author uses the PIECES framework (Performance, Information, Economics, Control and Security, Efficiency, Service) and produces an average score of 4.1. Then the user is categorized as satisfied with the system that was built.

SemanticFormer: Hyperspectral image classification via semantic transformer

Augmented Reality (AR) technology offers innovative ways in order to visualize and manipulate a 3D model of an object by superimposing computer-generated images onto another object interactively. The ability to interact with digital and spatial information in real-time offers new opportunities to manipulate and process medical data easily and efficiently. During surgical interventions, surgeons face various challenges dealing with digital patient data. Several methods are used to visualize the operative areas, such as fluoroscopy and ultrasound techniques. These techniques have several limitations. Thus, the augmented reality technique could serve as a better alternative to project a three-dimensional model of the target organ into the surgeon's perspective and field of view to improve the accuracy and efficiency of the medical intervention intraoperatively. In this paper, a new AR method is proposed in order to visualize and simulate the biomechanical model of the liver organ during open hepatic surgery. In this regard, the 3D model based on the patient's preoperative CT scans is first reconstructed. Then, the reconstructed model is projected using the AR headset. After that, the biomechanical model is generated and prepared for the simulation. The proposed approach is validated using acquired CT scans of the human organ.

Augmented reality imaging technology for orthopaedic surgery

Almost all human outdoor activities is closely related to geographical position, thus the development of GIS is more rapidly. From the perspective of spatial information visualization, GIS is a digital description of objective geographical world. As abstract models of geographical environment, analog maps and 2D electronic maps have respective limitations in vivid representing spatial information. Simultaneously, the vast majority of HCI is limited to plane display and is difficult to users to integrate into it. Relation between outdoor AR (augmented reality) technology and spatial information visualization representation embodies in the common basic cognition and mobility. Emergence of outdoor AR and mobile GIS provides the combination of outdoor AR technology and spatial information visualization representation with powerful theoretical foundation and technical channel, which offers new ideas and new interface to spatial information visualization representation and is committed to enhance and expand user's spatial cognition by overlaying virtual geographic objects on real scene. The paper firstly analyzes its research status, feasibility of the combination, basic characteristics and structure. Secondly, it discusses existing technologic prototypes from application-driven perspective and puts forward a research framework and discusses four key technologies: display device, tracking and positioning, virtual-real combination and HCI. Furthermore, it propose core algorithms including a hybrid registration method based on GPS and 3D electronic compass, registration methods using affine representation and geographical objects modeling etc. Lastly, it expatiate the applications and significance.

Spatial thinking skills, which encompass the ability to mentally perceive, manipulate, and find meaning in spatial information, are essential to student success across science, technology, engineering, and mathematics (STEM) disciplines, including meteorology. Atmospheric data are inherently spatial, with meteorology coursework requiring students to comprehend, interpret, and predict meteorological data across spatial scales. Spatial skills are known to improve over time in response to instruction, but the rate and nature of that progression in meteorology students as they move through the curriculum have yet to be characterized. In this study, the Spatial Thinking Abilities Test (STAT) was used to quantify spatial thinking skills in undergraduate students in 10 courses required for the meteorology major at a single institution. The STAT was administered twice a semester over a three-semester period at the start and end of each course. Gains in spatial reasoning skills were typically modest for a single semester, though overall levels of spatial skills were sensitive to declared major; meteorology and STEM majors scored significantly higher than nonmeteorology and non-STEM majors. Additionally, meteorology majors regularly exhibited improved performance on questions evaluating the skill of disembedding, which is particularly important for interpreting meteorological maps. Even so, disembedding was the weakest spatial thinking skill for all cohorts of meteorology majors. Longitudinal analysis of meteorology majors revealed that novice students progressed the least in their spatial skills, while students in the middle of curriculum exhibited the strongest gains, likely tied to an increased number of required meteorology courses and their specific content.

In today’s world, people increasingly rely on mobile apps to do their day-today activities, like checking their Instagram feed and online shopping from websites like Amazon and Flipkart. People are depending on WhatsApp and Instagram stories to communicate with local businesses and to leverage the said platforms for online advertising. Using Google Maps to find their way when they travel and finding out the immediate road and traffic conditions with digital banners around the road, has obviously led to a boom in advertising and marketing. Recently, internet users have increasingly desired to immerse themselves in a Metaverse-like platform where they can interact and socialize. Meta’s Metaverse is a tightly connected network of 3D digital spaces that allow users to escape into a virtual world. It is designed to change the way you socialize, work, shop, and connect with the real and virtual world around you. These platforms are not fully submerged in the real world; they are inclined toward virtual spaces only, making it obvious to fill this gap. Thus, the proposed framework in this chapter would be a new kind of system that may develop a socio-meta platform, powered by augmented reality and other technologies like photogrammetry and LiDAR. Augmented reality provides an interactive way of experiencing the real world, where the objects of the natural world are enhanced by computer-generated perceptual vision. One of the significant problems with augmented reality is the process of building virtual 3D objects that can be augmented into real spaces, which could be solved with photogrammetry and LiDAR. Photogrammetry is the technique of producing 3D objects using 2D images of a physical object taken from different angles and orientations. LiDAR, on the other hand, is another 3D reconstruction technology used widely by Apple’s eco-system. The functioning of LIDAR is very similar to sonar and radar, and the detection and ranging part are where it stands out from the others. The idea behind this platform is to open tons of virtual dimensions in the real world using the principles of mixed reality and geographic mapping tools such as Google Maps, MapBox, and GeoJSON; it would consequently transition the way people spend their time on social media by opening a portal for generating 3D objects that can be augmented to the real-world location using photogrammetry and cloud anchors by just a few 2D digital photographs taken from their camera.

Augmented Reality (AR) is a growing research area in virtual reality and generates a composite view for the user. It is combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene with additional information. About 80 percent information in the real world is related with spatial location. The combination of Geographical information system (GIS) and AR technologies would promote the development of outdoor AR systems, and also would explore a new research direction for GIS. The key technologies of outdoor augmented reality GIS, including basic tracking methods, display devices, typical applications and registration processes, are discussed. In indoor augmented reality's closed environments the tracking of position and head orientation as well as the presentation of information is much more unproblematic than the same task in an outdoor environment. The main application task of outdoor augmented reality GIS is the presentation of information to a user while moving through an unknown region. The system helps to detect automatically objects in sight of a person who need its information. It compares the conventional solutions of 3D registration with, while it discusses their algorithm procedure to basic parameters to give out their advantages and disadvantages at different condition. While affine transformation approach uses the idea of computer graphics and vision technology for reference. Its accuracy is mainly based on the precision and speed of scene feature point extracted from natural or artificial feature.