| 1. | Course Title | Ambient Intelligence and Smart Devices | |||||||||||
| 2. | Code | 4ФЕИТ07001 | |||||||||||
| 3. | Study program | 7-NKS, 8-KM-INN, 20-IMSA, 21-PNMI, 22-BE | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Daniel Denkovski, Dr Hristijan Gjoreski | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 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 |
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| 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. |
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| 12. | Learning methods:
Lectures, exercises, independent learning, independent work on project tasks and preparation of seminar papers |
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| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 45 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 30 hours | |||||||||
| 16.2 | Individual tasks | 30 hours | |||||||||||
| 16.3 | Homework and self-learning | 30 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | 0 points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | 50 points | |||||||||||
| 17.3. | Activity and participation | 0 points | |||||||||||
| 17.4. | Final exam | 50 points | |||||||||||
| 18. | Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||||||
| from 51 to 60 points | 6 (six) (E) | ||||||||||||
| from 61 to 70 points | 7 (seven) (D) | ||||||||||||
| from 71 to 80 points | 8 (eight) (C) | ||||||||||||
| from 81 to 90 points | 9 (nine) (B) | ||||||||||||
| from 91 to 100 points | 10 (ten) (A) | ||||||||||||
| 19. | Conditions for acquiring teacher’s signature and for taking final exam | Regular attendance on lectures | |||||||||||
| 20. | Forms of assessment | Project assignment and final exam. | |||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | Self-evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required 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 | |||||||||
