| Learning objectives |
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors:
- Understand the main technical concepts, models, and frameworks
of 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
(e.g., RFID/NFC, sensors, embedded systems, and smartphones) and
their applications
- Evaluate technical, ethical, privacy, and security issues
related to the Internet of Things
- 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 |
1) Strong knowledge of one or (preferably) more
programming languages.
2) Understanding of distributed computer systems
3) Prior knowledge of technologies such as IP; HTTP, XML, and JSON
4) Prior knowledge of data mining and big data algorithms |
| Examination |
|
Internet of
Things:
|
| Exam
ECTS |
7,5 |
| Examination form |
Oral exam based on written product
In order to participate in the oral exam, the written product
must be handed in before the oral exam; by the set deadline. The
grade is based on an overall assessment of the written product and
the individual oral performance. |
| Individual or group exam |
Individual exam |
| Size of written product |
Max. 15 pages |
|
One part of the assignment is for a more
self-chosen focus by the student. The second part of the assignment
is reserved to a technical focus, which is determined by the
semester assignment. |
| Assignment type |
Report |
| Duration |
Written product to be submitted on specified date and
time.
20 min. per student, including examiners' discussion of grade,
and informing plus explaining the grade |
| Preparation time |
No preparation |
| Grading scale |
7-step 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
The Internet of Things exam is an oral exam based on a written
product, which again is partly or fully based on a technical IoT
solution. The written product is based on two items. One item is a
topic that the student choose themselves and it counts for the
majority of the evaluation. The second item is a technical part
which counts for less, but ensures a good baseline of actual
technical content such as NFC, embedded data mining, mobile apps,
etc. At approx. the first half of the semester, the semester
assignment is uploaded and provided to the the
students.
|
|
| Course content and structure |
|
Main aim of the course
The basic technical idea of the Internet of Things 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.
|
| Teaching methods |
Classroom teaching.
Workshop. |
| 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 final literature is announced on the main forum for
the class on LEARN three weeks before the class starts.irst week of
the before they buy the books.
Selected Chapters from the Following Literature
(finalized on CBS Learn before the class starts):
- Pedersen, R. U. & Pedersen, M. K. (2013). Micro
Information Systems: New Fractals in an Evolving IS Landscape,
IDG Global (PDF distributed)
- Uckelmann, D., Harrison, M., & Michahelles, F. (2011).
Architecting the Internet of Things, Springer (students
must get this book)
- 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
- Chapter 19, Coulouris, G., Dollimore, J., & Kindberg, T.
(2011) Distributed Systems: Concepts and Design, 5th
edition, Addison-Wesley (PDF distributed or the students have
it.
- 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
- http://guidetodatamining.com/
- Students will select additional litterature (approx. 10-20
academic articles) for their individual semester
assignments.
|
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