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Since the end of 2022, ChatGPT and other chatbots continue to revolutionise the way we work, and especially in scientific and academic fields, this is both an opportunity and a challenge for both students and lecturers. Custom chatbots can also be easily created to suit specific applications and purposes. In addition, there are many other AI tools, e.g.,for image and video generation and manipulation, scientific work or presentations. This study evaluates some of these AI tools besides ChatGPT with regard to different applications for academic purposes, both from the students' and lecturers' point of view. As part of an interdisciplinary project, students, in collaboration with the lecturer, selected several AI tools based on possible application scenarios and investigated the basics and functionalities of the tools. In the next step, they analysed these tools with regard to possible teaching and learning scenarios. Based on these scenarios, they used the tools to develop detailed applications in different teaching-learning scenarios to check the suitability, effectiveness and correctness and to evaluate the results.Teaching material of a dedicated lecture, including presentations, videos, textbook and more was used as demonstrator for the different AI tools.
The emergence of automotive-grade LiDARs has given rise to new potential methods to develop novel advanced driver assistance systems (ADAS). However, accurate and reliable parking slot detection (PSD) remains a challenge, especially in the low-light conditions typical of indoor car parks. Existing camera-based approaches struggle with these conditions and require sensor fusion to determine parking slot occupancy. This paper proposes a parking slot detection (PSD) algorithm which utilizes the intensity of a LiDAR point cloud to detect the markings of perpendicular parking slots. LiDAR-based approaches offer robustness in low-light environments and can directly determine occupancy status using 3D information. The proposed PSD algorithm first segments the ground plane from the LiDAR point cloud and detects the main axis along the driving direction using a random sample consensus algorithm (RANSAC). The remaining ground point cloud is filtered by a dynamic Otsu’s threshold, and the markings of parking slots are detected in multiple windows along the driving direction separately. Hypotheses of parking slots are generated between the markings, which are cross-checked with a non-ground point cloud to determine the occupancy status. Test results showed that the proposed algorithm is robust in detecting perpendicular parking slots in well-marked car parks with high precision, low width error, and low variance. The proposed algorithm is designed in such a way that future adoption for parallel parking slots and combination with free-space-based detection approaches is possible. This solution addresses the limitations of camera-based systems and enhances PSD accuracy and reliability in challenging lighting conditions.
Die Erfindung betrifft ein Bussystem enthaltend Busleitungen, an denen eine Anzahl von Busteilnehmern über einen Transceiver anschließbar sind, wobei der Transceiver eine bidirektionale Kommunikation zwischen mindestens zwei Busteilnehmern bewirkt, wobei auf einer busabgewandten Seite des Transceivers sich an denselben eine Zwischenbrückeneinheit anschließt, die mindestens zwei Sender-/Empfänger-Paare enthaltend jeweils einen Sender und einen Empfänger aufweist, wobei der Sender einen Senderoszillator, eine Amplituden- und/oder Phasen- und/oder Frequenzmodulator sowie eine Antenne aufweist und wobei der Empfänger einen Mischer aufweisenden Demodulator sowie eine Antenne aufweist, wobei ein erstes Sender-/Empfänger-Paar über eine Funkschnittstelle mit dem zweiten Sender-/Empfänger-Paar miteinander gekoppelt sind.
The integration of sensors is one of the major tasks in embedded, control and “internet of things” (IoT) applications. For the integration mainly digital interfaces are used, starting from rather simple pulse-width modulation (PWM) interface to more complex interfaces like CAN (Controller Area Network). Even though these interfaces are tethered by definition, a wireless realization is highly welcome in many applications to reduce cable and connector cost, increase the flexibility and realize new emerging applications like wireless control systems. Currently used wireless solutions like Bluetooth, WirelessHART or IO-Link Wireless use dedicated communication standards and corresponding higher protocol layers to realize the wireless communication. Due to the complexity of the communication and the protocol handling, additional latency and jitter are introduced to the data communication that can meet the requirements for many applications. Even though tunnelling of other bus data like CAN data is generally also possible the latency and jitter prevent the tunnelling from being transparent for the bus system. Therefore a new basic technology based on dual-mode radio is used to realize a wireless communication on the physical layer only, enabling a reliable and real-time data transfer. As this system operates on the physical layer it is independent of any higher layers of the OSI (open systems interconnection) model. Hence it can be used for several different communication systems to replace the tethered physical layer. A prototype is developed and tested for real-time wireless PWM, SENT (single-edge nibble transmission) and CAN data transfer with very low latency and jitter.
Wireless CAN
(2018)
Das vorgestellte System zu Wireless CAN bietet die Möglichkeit, CAN kabellos zu übertragen. Beide vorgestellten und entwickelten Konzepte funktionieren korrekt und ermöglichen den Auf-bau von kabellosen CAN Schnittstellen. Durch den kleinen Aufbau kann diese Technologie auch für eingebettete Systeme verwendet werden. Zudem bietet dieser Ansatz die Möglichkeit, durch die Entwicklung von geeigneten ICs die Größe des Systems bis auf Bauteilgröße zu reduzieren, um eine noch bessere Integration in eingebettete Systeme zu ermöglichen. Dadurch wird die Technologie attraktiv für Einsatzgebiete, wo die oben aufgelisteten Vorteile zum Tragen kommen können. Diese Einsatzgebiete können sowohl im Automobil als auch im Industriebereich liegen.
Embedded Systems für IoT
(2019)
