During the last decade the development of modern digital media such as smartphones and tablet computers has enabled new experimental possibilities in STEM education. Besides these now nearly ubiquitous devices, the fields of virtual reality (VR) and augmented reality (AR) also made huge progress and reached education. In this paper we introduce an AR experiment alongside the basic idea of this column and following prior work. In the experiment high school students use smartglasses and real-time measurement data to study Kirchhoff’s circuit laws in electrical DC circuits.
Recent progress in quantum computers severely endangers the security of widely used public-key cryptosystems and of all communication that relies on it. Thus, the US NIST is currently exploring new post-quantum cryptographic algorithms that are robust against quantum computers. Security is seen as one of the most critical issues of low-power IoT devices—even with pre-quantum public-key cryptography—since IoT devices have tight energy constraints, limited computational power and strict memory limitations. In this paper, we present, to the best of our knowledge, the first in-depth investigation of the application of potential post-quantum key encapsulation mechanisms (KEMs) and digital signature algorithms (DSAs) proposed in the related US NIST process to a state-of-the-art, TLS-based, low-power IoT infrastructure. We implemented these new KEMs and DSAs in such a representative infrastructure and measured their impact on energy consumption, latency and memory requirements during TLS handshakes on an IoT edge device. Based on our investigations, we gained the following new insights. First, we show that the main contributor to high TLS handshake latency is the higher bandwidth requirement of post-quantum primitives rather than the cryptographic computation itself. Second, we demonstrate that a smart combination of multiple DSAs yields the most energy-, latency- and memory-efficient public key infrastructures, in contrast to NIST’s goal to standardize only one algorithm. Third, we show that code-based, isogeny-based and lattice-based algorithms can be implemented on a low-power IoT edge device based on an off-the-shelf Cortex M4 microcontroller while maintaining viable battery runtimes. This is contrary to much research that claims dedicated hardware accelerators are mandatory.
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.
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