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General information
Embedded Systems / Internet of Things (IoT) AG
Embedded Systems / Internet of Things (IoT) AG
BK121
EmbedSysInte-01-BA-M
Prof. Dr. Patz, Ralf (ralf.patz@haw-kiel.de)
Prof. Dr. Patz, Ralf (ralf.patz@haw-kiel.de)
Sommersemester 2018
1 Semester
In der Regel jedes Semester
Englisch
Curricular relevance (according to examination regulations)
Study Subject Study Specialization Study Focus Module type Semester
B.Eng. - Wing - Wirtschaftsingenieurwesen - Elektrotechnik (PO 2017, V1) Nachhaltige Energiesysteme Wahlmodul
B.Eng. - E - Elektrotechnik (PO 2017, V3) Elektrische Energietechnik Wahlmodul
B.Eng. - E - Elektrotechnik (PO 2017, V3) Technische Informatik Wahlmodul
B.Eng. - Me (PO 2023) - Mechatronik (PO 2023, V4) Wahlmodul
B.Eng. - E - Elektrotechnik (PO 2017, V3) Kommunikationstechnik und Embedded Systems Wahlmodul
B.Eng. - Wing - Wirtschaftsingenieurwesen - Elektrotechnik (PO 2017, V1) Kommunikationstechnik Wahlmodul
Qualification outcome
Areas of Competence: Knowledge and Understanding; Use, application and generation of knowledge; Communication and cooperation; Scientific self-understanding / professionalism.
The sudents
- will understand the principles of embedded systems based on micrcontrollers and single-board computer.
- will be able the evaluate products and systems based on embedded systmes.
- will work in teams on tasks and will be able to defend and argue their positions against the other team members.
Content information
Embedded systems are used in most electronic systems nowadays. The term "Internet of Things" (IoT) as been coined as they get increasingly networked (Ethernet, Wifi, Bluetooth, etc.) via the Internet. This module exposes the students to embedded systems as well as to the IoT. The concepts and tools are conveyed via project work using different embeded system platforms (e.g. Ardunio/Energia, Raspberry PI, ARM Mikrocontroller, or similar). Different approaches are used in order to take into account the different levels of students.
• Charalampos Doukas, Building Internet of Things with the Arduino, CreateSpace Independent Publishing Platform, 2012.
• Charles Bell, Beginning Sensor Networks with Arduino and Raspberry Pi, Apress; Auflage: 2013
• E.F. Engelhardt, Sensoren am Raspberry Pi, Franzis Verlag GmbH, 2014.
• Texas Instruments Launchpad, www.ti.com/launchpad
Teaching formats of the courses
Teaching format SWS
Labor 4
Workload
4 SWS
5,0 Credits
48 Hours
102 Hours
Module Examination
Method of Examination Duration Weighting wird angerechnet gem. § 11 Absatz 2 PVO Graded Remark
Projektbezogene Arbeiten 100 %
Miscellaneous
The module is project orientated and offered every semester. This allows the student to work on the project for a longer time period. It is therefore possible, and encouraged, to enrol into the module for more than one semester. In this case the module is limited to a total of 5 CP.
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