Table of contents

The course is connected to the following study programs

Teaching language

English

Prerequisites

Basic knowledge of signal processing, wireless communication, or loT

Recommended previous knowledge

Master level of sensors andwireless communicationsknowledge is advantageous but not required.

Learning outcomes

Upon completion of the course, students will be able to:

1. Understand the latest research advancements in the field of smart sensors andwireless communication protocols with a particular focus on the areas of expertise andongoing research conducted by professors at UiA.

2. Develop expertise in multi-modal data fusion andAl-based signal processing.

3. Apply knowledge to industrial automation, smart cities, healthcare, and autonomoussystems.

4. Analyze and incorporate the aforementioned research advancements into the PhDcandidates' own research within their respective fields.

5. Conduct independent research and publish findings in peer-reviewed journals.

Contents

1. Introduction to Sensors for Automotive, Industrial and Medical applications

2. Time-FrequencyAnalysis Techniques for Sensor Data

3. Al and Machine Learning for Sensor Data Processing

4. Deep Reinforcement Learning

5. Industry/Guest Lecture - Wireless Communication for Smart Sensors

6. Industry/Guest Lecture - Multi-Agent and Distributed Sensing

7. Applications and Future Trends

8. 1-2 Professors from Industry- Latest/Advanced Topics

Teaching and learning methods

The course combines lectures with interactive workshops, allowing for a dynamic andengaging learning experience. Each professor has the flexibility to structure their sessionsaccording to their teaching approach. The total expected workload for the course isapproximately 130 hours, corresponding to 5 ECTS

Examinations

To successfully complete the course, students must actively engage in course components,deliver an oral presentation with a Q&A session, and submit a comprehensive project report.

  • Oral Presentation: Evaluated based on the clarity of communication, understanding oftheoretical concepts, and ability to engage in discussion during the Q&A session.
  • • Project Report: Assessed for coherence, analytical approach, and relevance,demonstrating the candidate's ability to apply key course concepts.

Student evaluation

The course will be evaluated in accordance with the quality system for education, chapter 4.1.

Offered as a free-standing course

Yes
Last updated from FS (Felles studentsystem) Oct. 15, 2026 2:27:54 PM