Mobile Sensor Systems and Ambient Intelligence

Објавено: June 28, 2022
1. Course Title Mobile Sensor Systems and Ambient Intelligence
2. Code 4ФЕИТ07Л008
3. Study program КТИ
4. Organizer of the study program (unit, institute, department) Faculty of Electrical Engineering and Information Technologies
5. Degree (first, second, third cycle) First cycle
6. Academic year/semester IV/8 7. Number of ECTS credits 6
8. Lecturer D-r Hristijan Gjoreski
9. Course Prerequisites Passed: Data Structures and Programming, Programming and Algorithms
10. Course Goals (acquired competencies): Introduction to the concept of mobile sensor systems and their use in everyday life, wearable sensors, smart devices, ambient intelligence. With this course, the student will gain knowledge about the practical use of tools and techniques for working with mobile sensory data. That is, collecting data, processing them, and building appropriate models.
11. Course Syllabus: Introduction to mobile sensor systems, smart devices, smart systems, wearable sensors. Smartphone and Smartwatch sensors. Introduction to the concept of Ambient Intelligence and its applications, such as human activity recognition, automatic fall detection, calorie estimation. Sensors, sensors data, data fusion, data analysis, statistical modeling. Practical development of a smartphone sensor application, including data collection, data analysis, model development.
12. Learning methods: Lectures, auditory and laboratory exercises, independent learning, independent work on project tasks and preparation of seminar papers
13. Total number of course hours 2 + 2 + 1 + 0
14. Distribution of course hours 180
15. Forms of teaching 15.1. Lectures-theoretical teaching 30
15.2. Exercises (laboratory, practice classes), seminars, teamwork 45
16. Other course activities 16.1. Projects, seminar papers 45
16.2. Individual tasks 20
16.3. Homework and self-learning 40
17. Grading 17.1. Exams 0
17.2. Seminar work/project (presentation: written and oral) 40
17.3. Activity and participation 20
17.4. Final exam 40
Grading criteria (points) up to 50 points 5 (five) (F)
from 51to 60 points 6 (six) (E)
from 61to 70 points 7 (seven) (D)
from 71to 80 points 8 (eight) (C)
from 81to 90 points 9 (nine) (B)
from 91to 100 points 10 (ten) (A)
19. Conditions for acquiring teacher’s signature and for taking final exam Practical (laboratory) exercises and finished project
20. Forms of assessment Partial exam during the semester lasting 120 minutes or one final written exam in the appropriate exam session lasting 120 minutes. Evaluation of laboratory exercises. Project assignment that will be evaluated.
21. Language Macedonian and English
22. Method of monitoring of teaching quality Internal evaluation and surveys
23. Literature
23.2. Additional Literature
No. Author Title Publisher Year
1 Werner Weber, Jan Rabaey, Emile H.L. Aarts Ambient Intelligence Springer 2005
2 Manish J. Gajjar Mobile Sensors and Context-Aware Computing Morgan Kaufmann 2015
3 Mark Weiser . The Computer for the 21th Century Scientific American 1991