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Special Issue "Recent Advances Technologies for Intelligent Sensing in Augmented Reality Environments"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 August 2019).

Special Issue Editors

Prof. Dr. Ioannis Chatzigiannakis
Website
Guest Editor
Prof. Dr. Konstantinos Moustakas
Website
Guest Editor
Wire Communications Laboratory, Department of Electrical and Computer Engineering, University of Patras, GR - 26 500, Rion, Patras, Greece

Special Issue Information

Dear Colleagues,

Over the last decade, we have witnessed tremendous progress towards the interconnection of the digital and physical domains, giving rise to the “Internet of Things”. In this new era, everyday objects, each with a unique identifier, will automatically connect to affiliated networking interfaces and will upload unprecedented amounts of diverse data from a wide range of sensors. With the ever-increasing amount of sensor data that is inherent in an IoT world, the key to gaining real business value is effective communication among all elements of the architecture. As global telecommunication market shift towards the 5G era, it becomes obvious that it is now realistic to expect the delivery of new application experiences that utilize augmented reality (AR) technologies and provide end users with real time as well as real world information from the sensor data collected. Augmented reality, powered by the continuously increasing processing and sensing power of mobile processors and quality of emerging displays, is no longer an expensive specialized lab equipment, but has proven its applicability in many domains like health, automotive, manufacturing, art, education and more. The combinations of sensor data arriving from IoT deployments and AR technologies will enable us to seamlessly bridge the gap between the real and digital worlds around us.

In this Special Issue we invite authors to submit original research articles, surveys and viewpoint articles related to recent advances at all levels of the application stack and related technologies. We are particularly interested in presenting emerging technologies related to intelligent sensing in combination with augmented reality that may have a significant impact on the field for years to come. We are open to papers addressing a broad range of topics, from foundational topics regarding the operating principles of intelligent sensing/AR systems, and novel design principles for building future intelligent sensing/AR systems; to papers presenting advanced frameworks and technological platforms for developing intelligent sensing/AR applications; to pilots reporting innovative approaches for human engagement. Topics of interest for the Special Issue include (but are not limited to):

  • Networking technologies for low-latency, real-time communication in intelligent sensing deployments
  • Signal processing and machine learning techniques in intelligent sensing/AR environments
  • Networked, distributed (multiple sensors, cameras) geometry processing and reconstruction in AR
  • Middleware for the realization of intelligent sensing/AR applications
  • Unobtrusive vision-based and/or sensor-based AR registration techniques
  • New forms of interaction and dynamics simulation in AR spaces using intelligent sensor devices
  • Data management and knowledge extraction in intelligent sensing/AR services
  • Methodologies for studying, analysing and building intelligent sensing/AR systems
  • Novel application scenarios, challenges and opportunities
  • Development challenges and approaches for intelligent sensing/AR experiences
  • Prototype hardware for delivering intelligent sensing/AR experiences
  • Real-world deployments; pilots of intelligent sensing/AR applications
  • Evaluation of intelligent sensing/AR applications

Prof. Dr. Ioannis Chatzigiannakis
Dr. Konstantinos Moustakas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle
ARENA—Augmented Reality to Enhanced Experimentation in Smart Warehouses
Sensors 2019, 19(19), 4308; https://doi.org/10.3390/s19194308 - 04 Oct 2019
Abstract
The current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems [...] Read more.
The current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults. Full article
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Open AccessArticle
A Model to Support Fluid Transitions between Environments for Mobile Augmented Reality Applications
Sensors 2019, 19(19), 4254; https://doi.org/10.3390/s19194254 - 30 Sep 2019
Abstract
The adaptability between different environments remains a challenge for Mobile Augmented Reality (MAR). If not done seamlessly, such transitions may cause discontinuities in navigation, consequently disorienting users and undermining the acceptance of this technology. The transition between environments is hard because there are [...] Read more.
The adaptability between different environments remains a challenge for Mobile Augmented Reality (MAR). If not done seamlessly, such transitions may cause discontinuities in navigation, consequently disorienting users and undermining the acceptance of this technology. The transition between environments is hard because there are currently no localization techniques that work well in any place: sensor-based applications can be harmed by obstacles that hamper sensor communication (e.g., GPS) and by infrastructure limitations (e.g., Wi-Fi), and image-based applications can be affected by lighting conditions that impair computer vision techniques. Hence, this paper presents an adaptive model to perform transitions between different types of environments for MAR applications. The model has a hybrid approach, choosing the best combination of long-range sensors, short-range sensors, and computer vision techniques to perform fluid transitions between environments that mitigate problems in location, orientation, and registration. To assess the model, we developed a MAR application and conducted a navigation test with volunteers to validate transitions between outdoor and indoor environments, followed by a short interview. The results show that the transitions were well succeeded, since the application self-adapted to the studied environments, seamlessly changing sensors when needed. Full article
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