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- W3107696522 abstract "In recent years, the education sector has incorporated the use of new technologies and computing devices into classrooms, which allowed for implementing new ways for enhancing teaching and learning. One of these new technologies is augmented reality (AR), which enables creating experiences that mix reality and virtual elements in an attractive and visual way, thus helping teachers to foster student interest in learning certain subjects and abstract concepts in novel visual ways. This paper proposes to harness the potential of the latest AR devices in order to enable giving AR-enabled lectures and hands-on labs. Specifically, it proposes an architecture for providing low-latency AR education services in a classroom or a laboratory. Such a low latency is achieved thanks to the use of edge computing devices, which offload the cloud from the traditional tasks that are required by dynamic AR applications (e.g., near real-time data processing, communications among AR devices). Depending on the specific AR application and the number of users, the wireless link (usually WiFi) could be overloaded if the network has not been properly designed, and the overall performance of the application can be compromised, leading to high latency and even to wireless communication failure. In order to tackle this issue, radio channel measurements and simulation results have been performed by means of an in-house developed 3D ray-launching tool, which is able to model and simulate the behaviour of an AR-enabled classroom/laboratory in terms of radio propagation and quality of service. To corroborate the obtained theoretical results, a Microsoft HoloLens 2 teaching application was devised and tested, thus demonstrating the feasibility of the proposed approach." @default.
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- W3107696522 date "2020-11-14" @default.
- W3107696522 modified "2023-10-01" @default.
- W3107696522 title "Analysis, Design and Practical Validation of an Augmented Reality Teaching System Based on Microsoft HoloLens 2 and Edge Computing" @default.
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- W3107696522 doi "https://doi.org/10.3390/ecsa-7-08210" @default.
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