Ambient Intelligence and Assisted Living

Course Description

Holistic approach to the design, engineering and implementation of supported living systems that rely on ambient intelligence is based on integration of knowledge acquired during the bachelor's education as well as some topics from master's curriculum. Attention is paid to ambient intelligence, sensors and actuators, user interfaces, industrial communication interfaces, communication protocols, system software and software tools. In addition students acquire skills to analyze users' need through "design thinking", project work and project documentation as well as popular an technical reporting. All this enables students to build systems assisting users in their living and working environment and daily activities from components of highest level of integration like personal and industrial computers, specialized measurement and control equipment as well as communication equipment of general purpose. The whole course is embedded in the concept of service learning.

Learning Outcomes

  1. Design a device or a system assiting user in his daily work and life
  2. Compose systems as a netowrk of dedidated devices
  3. Use standardized protocols, interfaces and components
  4. Assess and appropriatly leverage properties of industrial devices, subsystems and methods
  5. Define project requirements
  6. Plan and organize a simple project from idea to realisation
  7. Criticize and argument decisions and ideas in communication with other teams whose projects comprise a bigger whole with students' project
  8. Choose appropriate sensors.
  9. Analyze users' needs.
  10. Publicly present their results.

Forms of Teaching


Lectures are held weekly.

Seminars and workshops

Within the course students prepare practical projects in groups of up to 4 students on a topic related to ambient intelligence and assisted living chosen by them or assigned by course lecturer.


Laboratory exercises are held at the University with the available equipment.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 50 % 30 % 0 % 0 %
Seminar/Project 50 % 40 % 50 % 40 %
Mid Term Exam: Written 0 % 1 % 0 %
Final Exam: Written 50 % 29 %
Exam: Written 50 % 60 %

Week by Week Schedule

  1. Course introduction
  2. Ambiental intelligence and supported living
  3. Sensors
  4. Actuators
  5. Industrial interfaces
  6. Communication protocols
  7. User interfaces and user experience 1
  8. Midterm exam
  9. User interfaces and user experience 2
  10. Students' choice topic
  11. User's needs analysis
  12. Design thinking
  13. Service learning
  14. Seminar
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Elective Courses (1. semester)
Communication and Space Technologies (profile)
Elective Courses (2. semester)
Computational Modelling in Engineering (profile)
Elective Courses (2. semester)
Computer Engineering (profile)
Elective Courses (2. semester)
Computer Science (profile)
Elective Courses (2. semester)
Control Systems and Robotics (profile)
Elective Courses (2. semester)
Data Science (profile)
Elective Courses (2. semester)
Electrical Power Engineering (profile)
Elective Courses (2. semester)
Electric Machines, Drives and Automation (profile)
Elective Courses (2. semester)
Electronic and Computer Engineering (profile)
Elective Courses (2. semester) Elective Courses of the Profile (2. semester) Specialization Course (3. semester)
Electronics (profile)
Elective Courses (2. semester)
Information and Communication Engineering (profile)
Elective Courses (2. semester)
Network Science (profile)
Elective Courses (2. semester)
Software Engineering and Information Systems (profile)
Elective Course of the profile (2. semester) Elective Courses (2. semester)


Andree Woodcock, Louise Moody, Deana McDonagh, Ajita Jain, Lakhmi C. Jain (2019.), Design of Assistive Technology for Ageing Populations, Springer Nature
Zaigham Mahmood (2019.), Guide to Ambient Intelligence in the IoT Environment, Springer
Albert M. Cook, Pedro Encarnação, Janice Miller Polgar (2019.), Assistive Technologies, Mosby
Hideyuki Nakashima, Hamid Aghajan, Juan Carlos Augusto (2009.), Handbook of Ambient Intelligence and Smart Environments, Springer Science & Business Media

Associate Lecturers

For students


ID 222442
  Summer semester
L3 English Level
L2 e-Learning
30 Lectures
15 Laboratory exercises

Grading System

90 Excellent
80 Very Good
70 Good
60 Acceptable