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IK1332 Internet of Things 7.5 credits

Students of the course gets a broad introduction to the technology and use of internet of things.

Information per course offering

Termin

Information for Spring 2026 Start 13 Jan 2026 programme students

Course location

KTH Campus

Duration
13 Jan 2026 - 13 Mar 2026
Periods

Spring 2026: P3 (7.5 hp)

Pace of study

50%

Application code

60367

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Min: 25

Target group
Open to all programmes as long as it can be included in your programme.
Planned modular schedule
[object Object]
Schedule
Schedule is not published

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus IK1332 (Spring 2026–)
Headings with content from the Course syllabus IK1332 (Spring 2026–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • Infrastructure, system architectures and communication protocols for IoT.
  • Operating systems and programming environments for embedded devices, such as Linux and FreeRTOS.
  • Protocols for transferring sensor data, such as MQTT and CoAP.
  • Protocols for communication between IoT processors, sensors and actuators, such as I2C and SPI.
  • Sensor data processing and machine learning on IoT devices.
  • Application areas and associated system requirements.
  • Sustainability, security, privacy, energy, and ethics of IoT systems.

Intended learning outcomes

After passing the course, the student should be able to

  • describe at a general level the system architecture for various existing technologies for the Internet of Things (IoT)
  • describe communication protocols related to IoT, machine to machine communication (M2M) and communication with sensors and actuators
  • configure and design IoT services with existing technologies
  • describe and implement simpler methods for local sensor data processing on IoT devices, including the use of ready-made simple machine learning models
  • explain challenges regarding sustainability, security, privacy and ethics for IoT technology from a broad perspective.

For higher grades, the student should also be able to

  • analyse and compare different IoT architectures and communication protocols based on performance, security and energy efficiency
  • motivate the choice of technologies and design decisions when designing IoT systems for different applications
  • adapt and optimise methods for local data processing and machine learning on IoT devices for specific needs
  • analyse IoT systems with respect to sustainability, security, integrity and ethics.

Literature and preparations

Specific prerequisites

Knowledge in computer networks, 6 credits, equivalent to completed course EP1100/IK1203/IK2218/EP2120.

Knowledge and skills in programming, 6 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/DD1333/DD100N/ID1018/ID1022

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

Grading scale

A, B, C, D, E, FX, F

Examination

  • LABA - Laborative Work, 3.0 credits, grading scale: P, F
  • PROA - Project Work, 3.0 credits, grading scale: P, F
  • TENA - Written Exam, 1.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Technology

Education cycle

First cycle

Supplementary information

In this course, the EECS code of honor applies, see: http://www.kth.se/en/eecs/utbildning/hederskodex.