Computing Paradigms in the Internet of Things

Computing Paradigms in the Internet of Things

1.

Subject title

Computing Paradigms in the Internet of Things

Пресметковни парадигми во интернет на нештата

2.

Code

m23_s_043

3.

Study program

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

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Билјана Ристеска Стојкоска

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


The purpose of this course is to get acquainted with the program paradigms applied to each layer of modern IoT architectures (DEW, EDGE and FOG calculation). At the end of the course the student should know how to model and implement complex solutions for various IoT application domains, which should be optimized in the context of accounting speed, communication latency and energy efficiency.

11.

Subject content:


Basic concepts of inn. Architecture of Inn. Modeling and developing inn solutions on all layers. Collecting and Prosecutor`s Inn data. Time series analysis. Edge and Fog Analytics. Industry inn. Robots and drones. Innovation in IT.

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

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

6613

Eloi Bosse and Basel Solaiman

Information Fusion and Analytics for Big Data and IoT

Artech House

2016

6614

Ajit Jaokar and Jean-Jacques Bernard

Data Science for Internet of Things

Forthcoming edition Nov 2017, Futuretext

2017

6615

Xuemin (Sherman) Shen

IEEE Internet of Things Journal

IEEE

2017

6616

Robert Stackowiak

Big Data and The Internet of Things

Apress

2015

6617

0

22.2.

Additional literature

No.

Author

Title

Publisher

Year