EE305 Instrumentation and Measurements


EE305 Instrumentation and Measurements

Syllabus   |  International University of Sarajevo  -  Last Update on Feb 02, 2026

Referencing Curricula

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Electrical and Electronics Engineering

Academic Year
2025 - 2026
Semester
Spring
Course Code
EE305
Weekly Hours
3 Teaching + 2 Practice
ECTS
6
Prerequisites
Teaching Mode Delivery
Face-to-face
Prerequisite For
Teaching Mode Delivery Notes
-
Cycle
I Cycle
Prof. Jane Doe

Tarik Namas

Course Lecturer

Position
Associate Professor Dr.
Phone
033 957 -
Assistant(s)
Mr. Alminko Kasibovic "Scholarship Assistnat"
Assistant E-mail

Course Objectives

The objectives of this course are to introduce the students to the principles of instrument measurement, calibration and signal conditioning, and provide hands-on laboratory experiences with a variety of transducers and instruments. Basic priciples of PLC organisation and programming will be presented . Wiring of sensors from field to PLC and using of measurement data in process control will be presented during lectures and Labs.

Learning Outcomes

After successful completion of the course, the student will be able to:

1
Explain different standards and units of measurement and the conversion between them
2
Perform various measurement of physical variables for control and monitoring of industrial processes, and explain various stages of measurement, and different measurements techniques
3
Explain the different characteristics of measurement instruments and their effect on the measurements
4
Perform the process of calibration, and explain its importance
5
Design a temperature (or other type) sensor and explain the need for a transmitter in the measurement process,

Course Materials

Required Textbook

T: Principles of Measurements and Instrumentation, 3rd edition, Alan. S. Morris, 2001

Additional Literature
R1. Lessons In Industrial Instrumentation, by Tony R. Kuphaldt, 2019 (Open access book) R2. Process Control Instrumentation Technology,8th edition, Curtis D.Johnson, Pearson, 2014 R3. Measurement and Instrumentation Theory and Application, Alan S. Morris, Reza Langari, 2012 R4. Measurement, Instrumentation, and Sensors Handbook CRC-IEEE 1999 R5. Measurement and Control Basics, 3rd Edition BY Thomas A. Hughes, ISA PRESS, 2002

Teaching Methods

Class discussions with examples
Active tutorial sessions for engaged learning and continuous feedback on progress
Team assignments
Team projects in form of lab experiments that involve real data, summary, interpretation and reporting in the lab

Weekly Topics

This weekly planning is subject to change with advance notice.
Week Topic Readings / References
1 Course syllabus & Mechanics, Measurements, importance & applications R1,R2,R3,R4,R5
2 Introduction about the importance of measurements and its applications,error Analysis. Interference. R1,R2,R3,R4,R5
3 Principle of calibration. Analog signal processing, Op-amps, Bridge circuits. Part 1 R1,R2,R3,R4,R5
4 Principle of calibration. Analog signal processing, Op-amps, Bridge circuits. Part 2 R1,R2,R3,R4,R5
5 Temperature and strain measurements. R1,R2,R3,R4,R5
6 Pressure measurements R1,R2,R3,R4,R5
7 Level measurements R1,R2,R3,R4,R5
8 MIDTERM EXAM
9 Flow measurements R1,R2,R3,R4,R5
10 Strain gauge, gas analyzers, encoders, position measurements. R1,R2,R3,R4,R5
11 Data acquisition, PLC basic and DCS R1,R2,R3,R4,R5
12 PLC- continuation Part 2, Project- giving tasks for project R1,R2,R3,R4,R5
13 PLC- continuation Part 3 R1,R2,R3,R4,R5
14 Project- presentation R1,R2,R3,R4,R5
15 FINAL EXAM

Course Schedule (All Sections)

SectionTypeDay 1Venue 1Day 2Venue 2
EE305.1 Course Friday 15:00 - 17:50 A F1.17 - -
EE305.1 Tutorial Wednesday 17:00 - 18:50 RC1.5 - Electronic Laboratory - -

Office Hours & Room

Course Office hours will be available here soon.

Assessment Methods and Criteria

Assessment Components

30%x1
Final Exam
AI: Not Allowed

Alignment with Learning Outcomes :  1  2  3  4

10%x2
Quizes (Tests)
AI: Not Allowed

Alignment with Learning Outcomes :  1  2  3

25%x1
Midterm Exam
AI: Not Allowed

Alignment with Learning Outcomes :  1  2  3  4

10%x1
Laboratory
AI: Not Allowed

Alignment with Learning Outcomes :  1  2  3  4  5

20%x1
Term Project
AI: Not Allowed

Alignment with Learning Outcomes :  4  5

5%x1
Homework
AI: Not Allowed

Alignment with Learning Outcomes :  1  2  3

IUS Grading System

Grading Scale IUS Grading System IUS Coeff. Letter (B&H) Numerical (B&H)
0 - 44 F 0 F 5
45 - 54 E 1
55 - 64 C 2 E 6
65 - 69 C+ 2.3 D 7
70 -74 B- 2.7
75 - 79 B 3 C 8
80 - 84 B+ 3.3
85 - 94 A- 3.7 B 9
95 - 100 A 4 A 10

Late Work Policy

Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.

ECTS Credit Calculation

📚 Student Workload

This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:

Lecture Hours

42 hours ⏳ (14 week × 3 h)

Laboratory

10 hours ⏳ (5 week × 2 h)

Active Tutorials

10 hours ⏳ (10 week × 1 h)

Home Study

42 hours ⏳ (14 week × 3 h)

Mid-term Exam Study

10 hours ⏳ (1 week × 10 h)

Final Exam

20 hours ⏳ (2 week × 10 h)

Term Project

16 hours ⏳ (4 week × 4 h)

150 Total Workload Hours

6 ECTS Credits


Course Policies

Academic Integrity

All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.

Attendance Policy

Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.

Technology & AI Policy

Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.

Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.

Communication Policy

All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [EE305] in the subject line.

Academic Quality Assurance Policy

Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.

More info

Learning Tips

Engage Actively

Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.

Read and Review Purposefully

Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.

Think Critically in Assignments

Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.

Ask Questions Early

Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.

Syllabus Last Updated on Feb 02, 2026 | International University of Sarajevo

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