Duration:
2 Semester | Turnus of offer:
each year, can be started in winter or summer semester | Credit points:
12 |
Course of studies, specific field and terms: - Master Entrepreneurship in Digital Technologies 2020 (advanced module), technology field computer science, Arbitrary semester
- Master Computer Science 2019 (optional subject), advanced module, Arbitrary semester
- Master Robotics and Autonomous Systems 2019 (advanced module), advanced curriculum, 1st or 2nd semester
- Master IT-Security 2019 (advanced module), Elective Computer Science, 1st or 2nd semester
- Master Entrepreneurship in Digital Technologies 2014 (advanced module), technology field computer science, 2nd and/or 3rd semester
- Master Computer Science 2014 (advanced module), advanced curriculum, 2nd and/or 3rd semester
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Classes and lectures: - CS5150 T: Organic Computing (lecture with exercises, 3 SWS)
- CS4504-S: Cyber Physical Systems (seminar, 2 SWS)
- CS5153 T: Wireless Sensor Networks (lecture with exercises, 3 SWS)
| Workload: - 120 Hours in-classroom work
- 20 Hours exam preparation
- 220 Hours private studies
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Contents of teaching: | - basic principles of organic computing / self-x system properties
- from motion to intelligent behavior and system/machine behavior
- design for self-organization, robustness, adaptivity, flexibility, trust
- analyzing, reverse-engineering, debugging machine behavior
- designing experiments and measuring behavior
- modeling system/machine behavior
- complexity, opacity, obscurity, trust of (AI) systems and explainable AI
- architecture of organic computing systems
- applications of self-x systems
- basics of wireless sensor networks
- hardware aspects of sensor nodes
- physics and protocols of wireless communication
- routing in wireless networks
- time synchronization and localization in wireless networks
- data management and data processing in wireless sensor networks
- applications of wireless sensor networks
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Qualification-goals/Competencies: - Students are able to utilize the principles of organic computing/self-x systems on exemplary designs.
- They are able to explain principles of organic computing/self-x systems.
- They are able to analyze system/machine behaviors in a structured, sound approach.
- Students are able to present the pros and cons of sensor networks.
- They are able to cope with analysis, design, and evaluation of protocols in sensor networks.
- They are able to interpret and pursue current research activities for sensor networks.
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Grading through: |
Responsible for this module: Teachers: - Dr. rer. nat. Javad Ghofrani
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Literature: - C. Müller-Schloer, S. Tomforde: Organic Computing Technical Systems for Survival in the Real World - Birkhäuser, 2017
- H. Karl, A. Willig: Protocols and Architectures of Wireless Sensor Networks - Wiley, 2005
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Language: |
Notes:Admission requirements for taking the module: - None Admission requirements for participation in module examination(s): - Successful completion of exercises as specified at the beginning of the semester. - Seminar lecture and elaboration according to the requirements at the beginning of the semester Module Exam(s): - CS4504-L1: Cyber Physical Systems, oral exam, 100% of the module grade. (Consists of CS5150 T, CS5153 T) |
Letzte Änderung: 26.10.2022 |
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