Intelligent sensor networks

1.

Subject title

Intelligent sensor networks

Интелигентни сензорски мрежи

2.

Code

m23_s_047

3.

Study program

Cloud Computing, Data science in computer science and engineering, IT management, Security, Cryptography and Coding, Еducation with ICT, 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, Bioinformatics, Inteligent Systems, Eco-informatics, Internet Technologies and cyber security,

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 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Ласко Баснарков ворн. проф. д-р Мирослав Мирчев

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

After completing the course, the student is expected to have knowledge of modern intelligent sensor networks and their diverse applications. Well versed in communication, routing, synchronization, coordination and localization methods in mobile sensor networks. To know how to design sensor networks that will be intelligent in terms of space, data, grouping and context, as well as to be able to develop appropriate software.

11.

Subject content:

Introduction to sensor networks and their applications. Architecture, Operating Systems and Programming of Sensor Nodes. Communication, routing, synchronization, localization, coordination, power management and security. Programming and control of sensor networks. Processing, aggregation and storage of data from large sensor networks. Distributed detection and estimation. Data analysis and knowledge discovery from sensor data. Networks and swarms of sensor-robotic agents. Algorithms for space search and coordinated movement by mobile agents.

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

45 + 15 + 30 + 50 + 40 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

45 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

15 hours

16.

Other forms of activities

16.1.

Project tasks

50 hours

16.2.

Independent tasks

30 hours

16.3.

Homework

40 hours

17.

Grading method

17.1.

Tests

45 points

17.2.

Seminar work / project (presentation: written and oral)

50 points

17.3.

Activities and learning

10 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

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature