Internet of Things (elective) (WP)*
Niveau
second cycle, Master
Learning outcomes of the courses/module
The students:
- know basic IOT architectures.
- know methods of data generation.
- know the basics of data transmission.
- know the options of data storage.
- know the forms of data visualization.
- understand challenges of data security.
- know basic IOT architectures.
- know methods of data generation.
- know the basics of data transmission.
- know the options of data storage.
- know the forms of data visualization.
- understand challenges of data security.
Prerequisites for the course
none
Course content
Introduction
- IoT architecture (e.g. reference models)
- Requirements for IOT systems
- IOT data transmission protocols
- Use of IOT in an industrial context (examples)
- Basics of sensor technology
- Basics of embedded systems
Implementation
- Procedure for implementing IOT
- Prototypical implementation of IOT
- Selection of sensors
- Data collection, visualization and evaluation
- Challenges in implementation
- IoT architecture (e.g. reference models)
- Requirements for IOT systems
- IOT data transmission protocols
- Use of IOT in an industrial context (examples)
- Basics of sensor technology
- Basics of embedded systems
Implementation
- Procedure for implementing IOT
- Prototypical implementation of IOT
- Selection of sensors
- Data collection, visualization and evaluation
- Challenges in implementation
Recommended specialist literature
Perry L.; Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security; Birmingham; 2018
Sinclair B.; IoT Inc: How Your Company Can Use the Internet of Things to Win in the Outcome Economy; 2017
Thomas O., Nüttgens M., Fellmann M. (Herausgeber); Smart Service Engineering: Konzepte und Anwendungsszenarien für die digitale Transformation; Wiesbaden; 2017
Sinclair B.; IoT Inc: How Your Company Can Use the Internet of Things to Win in the Outcome Economy; 2017
Thomas O., Nüttgens M., Fellmann M. (Herausgeber); Smart Service Engineering: Konzepte und Anwendungsszenarien für die digitale Transformation; Wiesbaden; 2017
Assessment methods and criteria
Written exam or seminar thesis
Language
German
Number of ECTS credits awarded
4
Share of e-learning in %
15
Semester hours per week
2.0
Planned teaching and learning method
Lecture, individual work with software, group work, presentation and discussion of tasks
Semester/trimester in which the course/module is offered
3
Name of lecturer
Prof. (FH) Dipl.-Ing. Thomas Schmiedinger, PhD
Academic year
2. study year
Key figure of the course/module
WPF.3
Type of course/module
integrated lecture
Type of course
Compulsory elective
Internship(s)
not applicable