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Embedded Systems
Last Updated: 2026-06-01 11:31:01
Abstract
An embedded system is a combination of hardware and software, either fixed in function or programmable, that is designed for a specific application scenario or for a specific task within a larger system. They are part of industrial machines such as agricultural and manufacturing equipment, automotive systems, medical equipment, household appliances, sensor networks, and the Internet of Things.
Objective
Understanding the specific requirements and problems that arise in embedded system applications. Understanding the hardware structure of a microcontroller and an embedded system; memory architecture and memory map, internal and external peripherals, low-power and low-energy design as well as instruction sets and computational accelerators. Understanding the firmware structure of a microcontroller and an embedded system; low-level instruction set, hardware-software interfaces, communication between components, embedded real-time operating systems, real-time scheduling, shared resources, low-power and low-energy programming as well as computational accelerators. Using formal models and methods for designing and optimizing embedded systems. Gaining experience with practical applications of the C programming language, embedded real-time operating systems, and debug functionalities of the associated design environment to design, implement, and verify embedded firmware. Through project-based activities, students will gain substantial experience in applying the C programming language in the context of embedded systems. Projects will involve developing and implementing firmware, utilizing embedded real-time operating systems, and exploring the debugging functionalities within design environments. This hands-on approach aims to bridge the gap between theoretical knowledge and practical application, allowing students to experience the full lifecycle of embedded system development from design to implementation and verification.
Content
This lecture focuses on the design of embedded systems using formal models and methods. Besides the theoretical lecture, the course contains laboratory sessions where students transfer the learned theoretical aspects into praxis by programming a microcontroller and interfacing it with sensors and actuators. Students will be exposed to a commercial microcontroller, and the development board extend with a custom-designed embedded systems educational platform. Specifically, the following topics will be covered in the course: hardware and software structures of embedded systems, low-level instruction set, memory architecture and memory map, peripherals, hardware-software interfaces, communication between components, firmware design methodologies, firmware design using the C programming language, embedded real-time operating systems, real-time scheduling, shared resources, low-power, and low-energy designs well as computational accelerators.
Resources
Lecture Notes
Lecture material, publications, exercise sheets, and laboratory documentation will be available on the course's Moodle page.
Literature
Yifeng Zhu: Embedded Systems with Arm Cortex-M Microcontrollers in Assembly Language and C - Fourth Edition, E-Man Press LLC, ISBN: 978-0982692677, 2023 Giorgio C. Butazzo: Hard Real-Time Computing Systems. Predictable Scheduling Algorithms and Applications, Springer, ISBN 978-1-4614-3019-3, 2011
Learning Materials (Links)
- Main link
- Course Webpage
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- 20 single-sided or 10 double-sided A4 pages of personal notes or printouts, and a calculator without communication capabilities.
Registration & Places
- Max Places
- 400
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Embedded Systems
The exercises in the first week will not take place.
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|
4 h weekly |
Offered In
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Robotics, Systems and Control (Fokus-Koordinator: Prof. Robert Katzschmann)
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Wahlfächer (Es können auch Lehrveranstaltungen aus dem Master-Studiengang in Informatik gewählt werden. Es liegt in der Verantwortung der Studierenden, sicherzustellen, dass sie die Voraussetzungen für diese Lehrveranstaltungen erfüllen.)
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5. Semester: Kernfächer des 3. Jahres (Kurswahl kann frei zusammengestellt werden, eine Liste mit detaillierten Empfehlungen findet sich unter )
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Vertiefung: Computer und Netzwerke (Diese Kernfächer werden insbesondere für den Bereich "Computer und Netzwerke" empfohlen, aber die Studierenden können Kernfächer aus allen Bereichen frei wählen.)
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Vertiefung: Elektronik und Photonik (Diese Kernfächer werden insbesondere für den Bereich "Elektronik und Photonik" empfohlen, aber die Studierenden können Kernfächer aus allen Bereichen frei wählen.)
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Wahlfächer (Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden. Als Wahlfächer für Rechnergestützte Wissenschaften Master gelten automatisch (ohne Anrechnungsgesuch) auch alle Kernfächer/Vertiefungsfächer (aber nicht Wahlfächer!) aus folgenden Studiengängen: Informatik Master Mathematik Master Physik Master Elektrotechnik und Informationstechnologie Master Data Science Master Robotics, Systems and Control Master Statistik Master Neural Systems and Computation Master gemäss den angegebenen Abschnittsreferenzen.)
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Vertiefung: Computers and Networks (The core courses and specialisation courses below are a selection for students who wish to specialise in the area of "Computers and Networks", see . The individual study plan is subject to the tutor's approval.)
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Kernfächer (These core courses are particularly recommended for the field of "Computers and Networks". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
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Foundation Core Courses (Fundamentals at bachelor level, for master students who need to strengthen or refresh their background in the area.)
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Fachspezifische Vertiefung (Es müssen mindestens 20 KP aus den Deep Track Lerneinheiten absolviert werden. Überzählige KP können für Wahlfächer angerechnet werden.)
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Vertiefungsfächer Aerospace Engineering (Diese LE's können sowohl als Vertiefungsfach als auch als Wahlfach angerechnet werden.)
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Vertiefungsfächer Robotics (Diese LE's können sowohl als Vertiefungsfach als auch als Wahlfach angerechnet werden.)
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