Students will gain in depth knowledge of mobile computing and introduce the Internet of Things (IoT). Students will further acquire knowledge of theories/models of mobile and pervasive computing applications, technologies and common research paradigms in mobile and pervasive computing such as context awareness, computing in an environment with limited resources, sensor-based interaction, and smart-device management. They will acquire skills in application design, architecture and implementation. Students will be expected to be able to analyse, discuss and critically reflect upon theories and research issues in mobile computing and internet of things.


A candidate who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The student...

  • has thorough knowledge of key paradigms and concepts in mobile computing such as context awareness, computing in an environment with limited resources, sensor-based interaction, and smart device management
  • has thorough knowledge of the Internet of Things from a systems perspective
  • has advanced knowledge of theories/models in mobile computing and internet of things
  • has advanced knowledge of the main challenges in mobile computing and internet of things


 The student...

  • can plan, describe and sketch a mobile computing architecture
  • can analyse different products within IoT (e.g., RFID, sensors, mobile devices, smart house, etc.) from a technical systems perspective and address technical challenges related to specific functions
  • can do proof-of-concept development, testing, and demonstration of an IoT system
  • can assess business value potential of a mobile computing solution

General competence

The student...

  • can describe and discuss research issues in mobile computing such as mobile architecture, mobile cloud computing, user interface and user experience related issues
  • can critically evaluate ethical issues related to mobile computing and internet of things
  • can describe and discuss research issues in and industry applications of Internet of Things (IoT)

Emnet inngår i

Master of Applied Computer Science - Software integration


Block teaching for four weeks. There will be class teaching three days a week for the two first weeks. The course is structured as a combination of class teaching, group collaboration and presentation in class. 

Anbefalt tidsbruk

Lectures and student guidance: 36 hours

Self-study: 64 hours

Preparation for presentation/discussion in class: 25 hours

Exercise: 25 hours

Assessment 50 hours

Total: 200 hours


Technologies to discussed and presented may offer RFID tags, Bluetooth devices, proximity/touch/temperature/light sensors, smart house kits, or electronic prototyping kits. 

Obligatorisk aktivitet

Arbeidskrav: Består av en eller flere oppgaver/aktiviteter som til sammen må vurderes godkjent 

Kvalifisert: G/IG (godkjent/ikke godkjent) 

Hjelpemidler: Alle hjelpemidler er tillatt 

Studenten må ha fått godkjent arbeidskravet i henhold til¿frister i retningslinjer for eksamen for å få lov til å avlegge eksamen.


Eksamensdel: Skriftlig individuell hjemmeeksamen 

Varighet: Tre uker

Gradering: Nasjonal karakterskala A - F (F er ikke bestått)

Vekting: 100 % av hel vurdering

Hjelpemidler: Alle hjelpemidler tillatt


See the learning outcome


Updated information on textbooks and other teaching materials is published per programme on our online learning platform before the semester starts. Information is also available per application on our website.


In addition to literature and other teaching material, scheduled teaching and other scheduled learning activities are always part of the syllabus.


In order to succeed in the course, the student should have intermediate programming skills, basic knowledge of distributed systems and/or computer networking.