| Learning objectives |
- Understand strategic commercial drivers including IoT business
ecosystems and business models
- Understand the main technical concepts, models, and frameworks
of the Internet of Things
- Evaluate selected technical, ethical, privacy, and security
issues related to the Internet of Things
- Analyse, using different Internet of Things frameworks:
Strategic and operational implications, user centered design, and
technical challenges in particular related to form and function (of
embedded, pervasive, and ubiquitous systems)
- Assess pros/cons of different Internet of Things technologies
and their applications
- Design/develop (parts of) a technical Internet of Things
solution such as an embedded data mining algorithm and/or hardware
platform to solve a given relevant problem
|
| Course prerequisites |
Prior knowledge and understanding of the
following is advantageous:
• Programming
• Distributed computing systems
• Technologies such as IP, HTTP, XML and JSON
• Data mining and big data algorithms |
| Examination |
|
Internet of
Things:
|
| Exam
ECTS |
7,5 |
| Examination form |
Home assignment - written product |
| Individual or group exam |
Individual exam |
| Size of written product |
Max. 15 pages |
| Assignment type |
Project |
| Duration |
Written product to be submitted on specified date
and time. |
| Grading scale |
7-point grading scale |
| Examiner(s) |
Internal examiner and second internal
examiner |
| Exam period |
Spring |
| Make-up exam/re-exam |
Same examination form as the ordinary exam
|
Description of the exam
procedure
In addition to the home assignmet, the students should upload a
short video (max 5 minutes) demonstrating the IoT artefact that
they have constructed.
|
|
| Course content, structure and pedagogical
approach |
|
Main aim of the course
The basic technical idea of the Internet of Things is that
virtually every physical thing in this world can also become a
small computer that is connected to the Internet. When they do so,
they are often called 'smart things', and these smart
things use embedded data mining to achieve their goals. Students
will gain advanced technical knowledge of key theories, algorithms,
models, frameworks, and technical solutions of the Internet of
Things. In business, the Internet of Things can also create new
business models, improve business processes, enhance supply chains,
and reduce costs and risks. The student will acquire
specialised problem-solving technical skills, being able to analyse
and design new solutions based on Internet of Things
technology. They shall take responsibility to conduct design and
implementation of new Internet of Things solutions both on the
hardware side and on the software side.
Technology, tools, and platforms
Internet of Things involve a number of different technologies:
Programming, RFID, NFC tags, Bluetooth devices,
proximity/touch/temperature/light sensors, IPv6 network, Zigbee
etc.
|
| Description of the teaching methods |
Classroom teaching.
Workshops. |
| Feedback during the teaching period |
Office hours: Office hours will provide feedback
to all the students who will discuss some aspects of the material
in more depth.
After class: In continuation of the class there is also the
possibility of discussing with the teacher to get feedback on both
the material and the semester assignment.
Workshop: The class features a large workshop where the students
get a lot of feedback from the teacher. This workshop also allows
some students to present to the rest of the class for peers
feedback.
Mail: Students can (and do) send e-mail with questions and drafts
of their assignments during the semester to get quick feedback on
key questions or concerns. |
| Student workload |
| Lectures |
24 hours |
| Prepare to class |
100 hours |
| Workshops |
19 hours |
| Exam and prepare |
63 hours |
| Total |
206 hours |
|
| Expected literature |
|
The literature can be changed before the semester starts.
Students are advised to find the final literature on Canvas
before they buy the books.
Selected Chapters from the Following Literature
(finalized on CBS Learn before the class starts):
- Uckelmann, D., Harrison, M., & Michahelles, F. (2011).
Architecting the Internet of Things, Springer.
- Pedersen, R. U. & Pedersen, M. K. (2013). Micro
Information Systems: New Fractals in an Evolving IS Landscape,
IDG Global.
- Chun-Wei Tsai, Chin-Feng Lai , Ming-Chao Chiang, Laurence T.
Yang (2013) Data Mining for Internet of Things: A Survey, IEEE
Communications Surveys & Tutorials, (16)1.
- Coulouris, G., Dollimore, J., & Kindberg, T.
(2011) Distributed Systems: Concepts and Design, 5th
edition, Chapter 19, Addison-Wesley
- Other articles that supplement the main coursebook
Optional Reading List (finalized on CBS Learn before
the class starts):
- Porter, M. & Heppelmann, J. (2015). How
smart, conected products are transforming industry. Harvard
Business Review
- Porter, M. & Heppelmann, J. (2014). How
smart, connected products are transforming competition.
Harvard Business Review
- Students will also select additional litterature (approx. 10-20
academic articles) for their individual semester
assignments.
|
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