Category | Theoretical-methodological |
Scientific or art field | Telecommunications and Signal Processing |
ECTS | 9 |
The course objective is to combine theoretical knowledge gained from various fields of information and communication technologies (ICT) and processing of signals and information, as well as their practical application at the Chair of Telecommunications and Signal Processing (KTIOS) laboratories. Through realization of project assignments, students master the skills of teamwork in completion of tasks. In this course, students, through consultations with teachers and in cooperation with industry partners, learn the reasons and importance of applying ICT and advanced methods for processing signals and information in business operations, as well as the importance of data collection with a wide variety of sensors in order to analyze multimodal representations of phenomena in society, bioinformatics, robotics, medicine, and art.
Students are trained in teamwork and collaboration with partners from industry to solve complex problems defined by their project tasks. The acquired knowledge and skills are used to perform the task analysis and recognize the possibility for active use of advanced ICT and modern methods of signal and information processing to improve the company's business, operation of devices, and systems in different areas of social and economic life.
Applications of Information and Communication Technologies (ICT), data and information processing in: •Industry 4.0 (cyber physical system, digital and virtual factory); •Business operations (information technology and systems, business software applications); •Smart traffic (intelligent transport systems, development of traffic cloud, and smart parking); •Education (video conferences, blogs, shared workspaces, adaptive education trajectories); •Agriculture (management of agricultural goods and machinery, ICT in livestock production); •Energy (energy distribution through smart grids); •Medicine (virtual clinics, sensory networks, and continuous monitoring of vital functions). Application of machine learning techniques and processing of multidimensional and multimodal signals for: •Remote observation with hyper spectral sensors with the purpose of scene analysis and classification; •Creating a smart environment, augmented and virtual reality; •Digital record interpretation obtained by multimodal scanning (digital photography, infrared, multi-spectral sensors, radiography, and X-ray fluorescence) for the restoration and conservation of works of art; •Natural Language Processing (NLP) in a variety of dialogue systems (voice portals, personal assistants, smart homes, etc); •Extraction of quantitative disease markers and knowledge by integration of physiological signals at multiple levels and recording modalities; •Cross-searching of multimedia archives for media services; •Forensic identification of speakers using modern audio signal processing techniques; •ICT and signal processing applications to aid people with disabilities.
Lectures, exercises, and consultations with independent research. ICT applications and signal processing were presented through the analysis of various trends and indicators, as well as projects of collaboration between laboratories and business partners. After forming teams of 3-5 students with related topics of master thesis and defining their project assignments, students will work to define technical solutions and their implementation through laboratory work. In addition to independent research work and consultations with subject teachers, the student will actively collaborate with business partners. At the end of the course, a group presentation of the developed technical solutions is planned in which students will exchange experiences, evaluate their own work, the work of their team, and others.
Authors | Title | Year | Publisher | Language |
---|---|---|---|---|
2015 | English | |||
2015 | English |
Course activity | Pre-examination | Obligations | Number of points |
---|---|---|---|
Project task | Yes | Yes | 50.00 |
Oral part of the exam | No | Yes | 30.00 |
Presentation | Yes | Yes | 20.00 |
Full Professor
Assistant Professor
Assistant Professor
Assistant with PhD
Assistant Professor
Assistant - Master
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© 2024. Faculty of Technical Sciences.