second cycle 60 credits

Computer Science: Internet of Things, Master's Course

Summary

This Internet of Things master course involves advanced technologies and research in Computer Science.
Application areas include for instance: smart transportation, smart cities, smart living, smart energy, smart health, and smart learning.
Relevant research areas include for instance Self-Adaptive Systems, Cyber Physical Systems, Systems of Systems and Engineering of all such systems.
Within this master course the student has the possibility to deepen her/his own understanding of Computer Science and Internet of Things and to develop the basis to continue her/his studies after graduate level (PhD studies).

Admission requirements

  1. Bachelor of Science in Computer Science or Degree of Engineering in Computer Science, or a degree in a related field. All degrees must be equivalent to at least 180 higher education credits.
  2. At least 60 credits at advanced level in Computer Science, including at least a 15 credits master thesis.
  3. At least 15 credits of programming.
  4. The equivalent of English 6/English B in Swedish secondary school.

Selection:

credits 100%

Syllabus

Syllabus for students autumn 2017, autumn 2016

Course Code:
DA650A revision 1
Swedish name:
Datavetenskap: Sakernas internet, masterkurs
Level of specialisation
A2E
Main fields of study:
Computer Science
Language:
English
Date of ratification:
29 January 2016
Decision-making body:
Faculty of Technology and Society
Enforcement date:
29 August 2016

Entry requirements

  1. Bachelor of Science in Computer Science or Degree of Engineering in Computer Science, or a degree in a related field. All degrees must be equivalent to at least 180 higher education credits.
  2. At least 60 credits at advanced level in Computer Science, including at least a 15 credits master thesis.
  3. At least 15 credits of programming.
  4. The equivalent of English 6/English B in Swedish secondary school.

Specialisation and progression relative to the degree regulations

The course is part of the main field of study Computer Science and meets the degree requirement for the degree of Master of Science with a major in Computer Science (120 Credits).

Purpose

The aim of this course is that students should deepen their understanding of the Internet of Things (IoT) and how to design and engineer IoT-based systems. The students should also develop the basis to continue their studies after graduate level (PhD studies).

Contents

The course is given in project form based on relevant questions within IoT.

Module 1: Research Project in IoT (30 credits)

  • Problem/Research identification and formulation in the area of IoT
  • Design, planning and execution of advanced research and development projects in IoT
  • Validation, writing and presentation in IoT
  • Central concepts in the area of Cooperative Information Systems, Computer Mediated Collaboration and Interaction Technology
  • Main concepts and Technologies in the development of software for media applications

Module 2: Advanced topics within IoT (15 credits)
  • Relevant applications areas within IoT include for instance: smart transportation, smart cities, smart living, smart energy, smart health, and smart learning. Examples of research areas include for instance: Self-Adaptive Systems, Cyber Physical Systems, Systems of Systems, Software Architectures and Connectors, Software Interoperability, Big Data and Big Data Mining, Privacy and Security

Module 3: Thesis Work (15 credits)
  • Thesis project in Computer Science within IoT

Learning outcomes

Knowledge and understanding
On completion of the course the student shall demonstrate:

1. Broad knowledge within IoT and deep knowledge and understanding of current research and development work within at least one area as mentioned above
2. Ability to describe central concepts in the area of Cooperative Information Systems, Computer Mediated Collaboration and Interaction Technology

Skills and abilities
On completion of the course the student shall demonstrate:

3. Ability to critically integrate knowledge, analyze, evaluate and handle complex problems and situations also with limited information within Computer Science
4. Ability to independently identify and formulate problems/research, design, plan and carry out advanced tasks in Computer Science by selecting and using suitable research methods within given time frames independently and/or in group
5. Ability to clearly and critically present and discuss own conclusions and knowledge and the arguments these are based upon in Computer Science, both orally and through scientific writing and in dialog with different groups
6. Ability to apply main concepts and Technologies in the development of software for media applications
7. Skills required to participate in research and development work in Computer Science or to work with other qualified tasks (skills include for instance: engagement/motivation, collaboration and constructive criticism)

Judgement and approach
On completion of the course the student shall demonstrate:

8. Capability to make judgments within the Computer Science area, with a special focus on IoT and software for media applications, taking into account relevant scientific, societal and ethical aspects and demonstrate awareness of ethical aspects of research and development work
9. Understanding of the possibilities and limitations of science, its role in society and the responsibility of its use
10. The ability to identify the personal need for further knowledge and take responsibility for his or her ongoing learning

Learning activities

Tuition: approximately 80 h

Individual studies: approximately 1520 h

Assessments

The course will be assessed through assignments, project and thesis project.

Requirements for Pass (G)

  • Pass on the project in Module 1 (learning outcomes 1, 3, 4, 5, 7, 8, 9, 10)
  • Pass on all assignments in Module 1 (learning outcomes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
  • Pass in all assignments of Module 2 (1, 3, 4, 5, 6, 7, 10)
  • Pass on the thesis project in Module 3 (learning outcomes 1, 3, 4, 5, 6, 7, 8, 9, 10)

Requirements for Pass with distinction (VG):
  • Pass with distinction on the project in Module 1
  • Pass with distinction on at least one assignment in Module 1
  • Pass with distinction on at least one assignment of Module 2
  • Pass with distinction on the thesis project in Module 3

Grading system

Fail (U), Pass (G) or Pass with Distinction (VG).

Course literature and other teaching materials


Recommended literture
  • Greengard, S. (2015). The Internet of Things. The MIT Press. ISBN: 0262527731
  • McEwen, A. & Cassimally, H. (2013). Designing the Internet of Things. Wiley. ISBN: 9781118430620
  • Sommerville, I. (2015). Software Engineering - 10th Edition, Pearson. ISBN: 0133943038
  • Vermesan, O. & Friess, P. Editors. (2013). Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems. River Publisher (River Publishers' Series in Information Science and Technology). ISBN: 8792982735

Articles
  • Atzori, L., Iera, A. and Morabito, G. (2010). The Internet of Things: A survey. Comput. Netw. 54, 15 , 2787-2805
  • Boardman, J. & Sauser, B. (2006). System of systems – the meaning of of. In IEEE/SMC International Conference on System of Systems Engineering, page 6 pp
  • Derler, P., Lee, E. A. and Sangiovanni-Vincentelli, A. (2012). Modeling cyber-physical systems, Proceedings of the IEEE (special issue on CPS), vol. 100, no. 1, pp. 13 – 28
  • Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660
  • Kim, K-D. & Kumar, P. R. (2012). Cyber-Physical Systems: A Perspective at the Centennial, Proceedings of the IEEE, vol. 100, no. Special Centennial, pp. 1287–1308
  • Lee, E. A. (2008). Cyber physical systems: Design challenges, in Proc. of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing, ser. ISORC ’08. Washington, DC, USA: IEEE Computer Society, pp. 363–369
  • de Lemos, R. et al.: Software Engineering for Self- Adaptive Systems: A Second Research Roadmap. Software Engineering for Self-Adaptive Systems II, LNCS Vol. 7475, pp. 1-32, Springer Berlin Heidelberg
  • Maier, M. (1998). Architecting Principles for Systems-of-Systems, Systems Engineering, 1(4), 267–284
  • Miorandi, D., Sicari, S., De Pellegrini, F., and Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497-1516
  • Xu, L. D., He, W. and Li, S. (2014). Internet of Things in Industries: A Survey. IEEE Trans. Industrial Informatics VOL. 10, NO. 4, pp. 2233-2243

Additional literature is determined by agreement with the teacher/supervisor.

Course evaluation

The University provides all students who are participating in, or have completed, a course to express their experiences and views on the course through a course evaluation which is organized at the end of the course. The university will collate the course evaluations and provide information about their results and any actions prompted by them. The results shall be made available to the students. (HF 1:14).

Interim rules

When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.

Contact

The education is provided by the Faculty of Technology and Society at the department Computer Science and Media Technology.

Further information

Samuel Andersson, Student Services Assistant
Phone: 040-66 57759
Romina Spalazzese, Course Responsible
Phone: 040-66 57660

Application

28 August 2017 - 03 June 2018 Day-time 100% Malmö

Tuition fees

for non-EU students only

First instalment: 123000 SEK
Full tuition Fee: 123000 SEK

28 August 2017 - 03 June 2018 Day-time 100% Malmö Application code: mah-78059

National application round

Tuition fees

for non-EU students only

First instalment: 123000 SEK
Full tuition Fee: 123000 SEK

Open for late application

Apply

29 August 2016 - 04 June 2017 Day-time 100% Malmö Schedule

Tuition fees

for non-EU students only

First instalment: 120000 SEK
Full tuition Fee: 120000 SEK

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