Ambient intelligence

Ambient intelligence

1.

Subject title

Ambient intelligence

Амбиентална интелигенција

2.

Code

m23_w_015

3.

Study program

Bioinformatics, Security, Cryptography and Coding, Cloud Computing, IT management, Еducation with ICT, Eco-informatics, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Software Engineering, Data science in computer science and engineering, Inteligent Systems,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

ворн. проф. д-р Ефтим Здравевски ворн. проф. д-р Петре Ламески

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


Within this course, students will be introduced to advanced approaches to processing data from ambient sensors and non -invasive sensors used to monitor the health status and activities of people in their habitats and work environments, as well as approaches to recognizing their activities. Implications for health systems and social aspects of people.

11.

Subject content:


Ambient and non -invasive sensors for detection of activities and sensors integrated into furniture Selection of the most suitable sensors and sensor readings Health Systems: Historical Review and Current Challenges Recognizing atomic activities at low Recognizing complex activities at high level Applying to monitoring the elderly Challenges in application Case studies and latest achievements Social aspects

12.

Learning methods:


Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

0 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

15 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

15 points

17.4.

Final exam

0 points

18.

Grading criteria (points / grade)

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.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

макед

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

6070

Nik Bessis, Ciprian Dobre

Big Data and Internet of Things: A Roadmap for Smart Environments

Springer

2014

6071

Seyed Shahrestani

Internet of Things and Smart Environments: Assistive Technologies for Disability, Dementia, and Aging

Springer

2017

6072

Nakashima, Hideyuki, Aghajan, Hamid, Augusto, Juan Carlos

Handbook of Ambient Intelligence and Smart Environments

Springer

2010

6073

Gaelle Calvary, Thierry Delot, Florence Sedes, Jean-Yves Tigli

Computer Science and Ambient Intelligence

Wiley

2013

22.2.

Additional literature

No.

Author

Title

Publisher

Year