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      Web AR Solution for UAV Pilot Training and Usability Testing

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          Abstract

          Data and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.

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          A taxonomy of mixed reality visual displays

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            UAV-Based IoT Platform: A Crowd Surveillance Use Case

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              Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                19 February 2021
                February 2021
                : 21
                : 4
                : 1456
                Affiliations
                [1 ]Computer Science and Communication Research Centre, School of Technology and Management, Polytechnic Institute of Leiria, Campus 2, Morro do Lena-Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal; eng.rob.ribeiro@ 123456gmail.com (R.R.); jr.joaoramos@ 123456outlook.com (J.R.); davidsafadinho.12@ 123456gmail.com (D.S.); carlos.rabadao@ 123456ipleiria.pt (C.R.)
                [2 ]INESC TEC, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal; ars@ 123456utad.pt (A.R.); jbarroso@ 123456utad.pt (J.B.)
                [3 ]INOV INESC Inovação, Institute of New Technologies, Leiria Office, Campus 2, Morro do Lena-Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal
                Author notes
                [* ]Correspondence: apereira@ 123456ipleiria.pt
                Author information
                https://orcid.org/0000-0003-1547-4674
                https://orcid.org/0000-0001-5361-9809
                https://orcid.org/0000-0001-5700-7893
                https://orcid.org/0000-0002-9818-7090
                https://orcid.org/0000-0001-7332-4397
                https://orcid.org/0000-0003-4847-5104
                https://orcid.org/0000-0001-5062-1241
                Article
                sensors-21-01456
                10.3390/s21041456
                7922183
                33669733
                678413c3-bf19-4176-bc06-8ffc36f0013b
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 January 2021
                : 11 February 2021
                Categories
                Article

                Biomedical engineering
                augmented reality,ar obstacle courses,human–drone interaction,marker-based ar,unmanned aerial vehicles,uav control interfaces,uav pilot training,web ar

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