Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
For the year 2019/2020 No calendar yet available
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
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Academic staff
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.
Training offer to be defined
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Networked embedded & IoT systems (2020/2021)
Teaching code
4S009004
Teacher
Coordinatore
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
II semestre dal Mar 1, 2021 al Jun 11, 2021.
Learning outcomes
The course aims to provide the knowledge necessary for the specification, modeling, development and verification of embedded network systems for industrial applications, in particular networked control systems, cyber-physical components, network infrastructures and Internet-of-Things (IoT) applications. At the end of the course the student will have to show the acquisition of the ability to analyze and understand the functioning of the networked embedded and IoT systems and the problems related to their design, implementation, verification, certification and use, with reference to their most important properties: performance, reliability, security and privacy. This knowledge will allow the student to acquire the ability to specify, model, design and verify networked embedded systems in the industrial and IoT fields, identifying the most appropriate components to integrate with each other, with the production machinery and the company information system. At the end of the course the student will be able to apply and deepen these topics independently.
Program
Theory:
- wireless embedded systems and protocols.
- networked control systems.
- protocols for smart manufacturing.
- advanced networking.
Laboratory:
- MQTT and Kafka.
- Multimedia communications and Quality of Service.
- Optimization of an actual industrial infrastructure.
- Programming of networked embedded systems
Examination Methods
Oral exam with 3 questions on theory and laboratory
Optional project:
- max 2 people
- effort: 40 hours
- possible synergy with other courses, stage, thesis
- some topics will be proposed at the end of the program but they can be proposed by students too
- max score: 3
Final score: oral exam score + project score.
Type D and Type F activities
Training offer to be defined
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.
Graduation
List of theses and work experience proposals
theses proposals | Research area |
---|---|
Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games |
Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) |
Domain Adaptation | Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION |
Domain Adaptation | Computing methodologies - Machine learning |
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.Please refer to the Crisis Unit's latest updates for the mode of teaching.