MK EN
ФИНКИ

Subject

Internet of Things for Ecosystems

1. Course Title Internet of Things for Ecosystems
Internet of Things for eco-systems
2. Code m23_s_237
3. Study Programme —
4. Organizer of the study programme (unit, institute, department or division) Faculty of Computer Science and Engineering
5. Degree level (first, second, third cycle) Second cycle
6. Academic year / semester 10 / Summer
7. Number of ECTS credits 6
8. Teacher Andrea Naumoski, Kosta Mitreski
9. Prerequisites for enrolling in the course —
10. Objectives of the course programme (competences) Upon completion of the course, students will acquire knowledge of applying IoT systems for monitoring, analysis of spatial and temporal environmental data, and decision-making based on such analyses. Additionally, they will learn how to apply these solutions to enhance and protect ecosystems.
11. Course content Introduction and examples of IoT systems in ecology, Application of IoT for monitoring and analysis of data from aquatic ecosystems, IoT in monitoring and analysis of ambient air data, Monitoring and analysis of measurement data from IoT soil systems, IoT and GIS in spatial information analysis, IoT in biodiversity studies, IoT in urban noise protection, IoT and electromagnetic radiation protection, IoT in the control and prevention of solid and liquid waste pollution, IoT and hydrophone systems, IoT in forest surface protection
12. Learning methods Lectures supported by slide presentations, interactive lectures, practical exercises (using equipment and software packages), teamwork, case studies, invited guest lecturers, independent preparation and defence of a project assignment and seminar paper, and learning in an electronic environment (forums and consultations).
13. Total available time 6 ECTS x 30 hours = 180 hours
14. Distribution of available time 60 + 0 + 0 + 0 + 0 = 180 hours
15. Forms of teaching activities
15.1. Lectures - theoretical instruction 60 hours
15.2. Exercises (laboratory, auditory), seminars, teamwork 0 hours
16. Other forms of activities
16.1. Project assignments 0 hours
16.2. Independent assignments 0 hours
16.3. Home study 0 hours
17. Assessment method
17.1. Tests 45 points
17.2. Seminar paper / project (presentation: written and oral) 0 points
17.3. Activities and learning 10 points
17.4. Final exam 100 points
18. Grading criteria (points / grade)
up to 50 points5 (five) (F)
from 51 to 60 points6 (six) (E)
from 61 to 70 points7 (seven) (D)
from 71 to 80 points8 (eight) (C)
from 81 to 90 points9 (nine) (B)
from 91 to 100 points10 (ten) (A)
19. Requirement for obtaining a signature and taking the final exam completed activities 15.1 and 15.2
20. Language of instruction Macedonian and English
21. Method for monitoring the quality of teaching internal evaluation and survey mechanism
22. Literature
22.1. Required literature
1. Raffaele Giaffreda, Radu-Laurentiu Vieriu, Edna Pasher, Gabriel Bendersky, Antonio J. Jara, Joel J.P.C. Rodrigues, Eliezer Dekel, Benny Mandler | Internet of Things. User-Centric IoT | Springer | 2016
2. Hwaiyu Geng | Internet of Things and Data Analytics Handbook | John Wiley & Sons, | 2017
3. Rajkumar Buyya, Amir Vahid Dastjerdi | Internet of Things: Principles and Paradigms | Elsevier | 2016
4. Friedrich Recknagel, William K. Michener | Ecological Informatics: Data Management and Knowledge Discovery | Springer | 2017
22.2. Additional literature
No. Author Title Publisher Year
Деканат Dean’s Office Студии Studies Акти Acts Проекти Projects