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智能传感器在增强型电气实验中的应用

Smart Sensors for Augmented Electrical Experiments.

机构信息

Physics Education Research Group, Department of Physics, Technische Universität Kaiserslautern, 67663 Kaiserslautern, Germany.

Microelectronic Systems Design Research Group, Department of Electrical and Computer Engineering, Technische Universität Kaiserslautern, 67663 Kaiserslautern, Germany.

出版信息

Sensors (Basel). 2021 Dec 30;22(1):256. doi: 10.3390/s22010256.

DOI:10.3390/s22010256
PMID:35009805
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8749546/
Abstract

With the recent increase in the use of augmented reality (AR) in educational laboratory settings, there is a need for new intelligent sensor systems capturing all aspects of the real environment. We present a smart sensor system meeting these requirements for STEM (science, technology, engineering, and mathematics) experiments in electrical circuits. The system consists of custom experiment boxes and cables combined with an application for the Microsoft HoloLens 2, which creates an AR experiment environment. The boxes combine sensors for measuring the electrical voltage and current at the integrated electrical components as well as a reconstruction of the currently constructed electrical circuit and the position of the sensor box on a table. Combing these data, the AR application visualizes the measurement data spatially and temporally coherent to the real experiment boxes, thus fulfilling demands derived from traditional multimedia learning theory. Following an evaluation of the accuracy and precision of the presented sensors, the usability of the system was evaluated with n=20 pupils in a German high school. In this evaluation, the usability of the system was rated with a system usability score of 94 out of 100.

摘要

随着增强现实(AR)在教育实验室环境中的应用日益增多,我们需要新的智能传感器系统来捕捉真实环境的各个方面。我们提出了一种满足这一要求的智能传感器系统,可用于电气电路的 STEM(科学、技术、工程和数学)实验。该系统由定制的实验箱和电缆以及适用于 Microsoft HoloLens 2 的应用程序组成,可创建一个增强现实实验环境。这些盒子结合了用于测量集成电气组件的电压和电流的传感器,以及当前构建的电路以及传感器盒子在桌子上的位置的重建。通过组合这些数据,AR 应用程序以与真实实验箱空间和时间一致的方式可视化测量数据,从而满足传统多媒体学习理论所提出的要求。在评估了所提出的传感器的准确性和精度之后,我们使用德国一所高中的 20 名学生对该系统的可用性进行了评估。在这项评估中,系统的可用性被评为 100 分中的 94 分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/9a51c0e9eb84/sensors-22-00256-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/b6fa2dbd71fb/sensors-22-00256-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/0b7207583e61/sensors-22-00256-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/899e3f6b4c8f/sensors-22-00256-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/4dae1477ede5/sensors-22-00256-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/ab9fbceefcfd/sensors-22-00256-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/91084d6297b0/sensors-22-00256-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/7d564c868289/sensors-22-00256-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/3f94ca22e388/sensors-22-00256-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/65168282cda3/sensors-22-00256-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/9a51c0e9eb84/sensors-22-00256-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/b6fa2dbd71fb/sensors-22-00256-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/0b7207583e61/sensors-22-00256-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/899e3f6b4c8f/sensors-22-00256-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/4dae1477ede5/sensors-22-00256-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/ab9fbceefcfd/sensors-22-00256-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/91084d6297b0/sensors-22-00256-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/7d564c868289/sensors-22-00256-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/3f94ca22e388/sensors-22-00256-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/65168282cda3/sensors-22-00256-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f01/8749546/9a51c0e9eb84/sensors-22-00256-g011.jpg

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