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.
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 enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
Compulsory activities for Smart Systems & Data AnalyticsCompulsory activities for Embedded & Iot Systems2° Year activated in the A.Y. 2024/2025
| Modules | Credits | TAF | SSD |
|---|
Compulsory activities for Embedded & Iot SystemsCompulsory activities for Robotics SystemsCompulsory activities for Smart Systems & Data Analytics| Modules | Credits | TAF | SSD |
|---|
Compulsory activities for Smart Systems & Data AnalyticsCompulsory activities for Embedded & Iot Systems| Modules | Credits | TAF | SSD |
|---|
Compulsory activities for Embedded & Iot SystemsCompulsory activities for Robotics SystemsCompulsory activities for Smart Systems & Data Analytics| Modules | Credits | TAF | SSD |
|---|
3 modules among the following (Computer vision and Human computer interaction 1st year only; Advanced computer architectures 2nd year only; the other courses both 1st and 2nd year. A.A. 2024/2025: Data visualization, Systems design laboratory and Electronic devices and sensors are not activated) 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 (2024/2025)
Teaching code
4S009004
Credits
6
Coordinator
Not yet assigned
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Courses Single
Authorized
The teaching is organized as follows:
IoT Systems
Credits
3
Period
Semester 2
Academic staff
Davide Quaglia
Networked embedded systems
Credits
3
Period
Semester 2
Academic staff
Davide Quaglia
Learning objectives
The course focuses on complex IoT systems that present the interaction of embedded components with cloud components through a communication network. The course aims to describe the techniques for the automatic design of such systems, also present in the industrial field, starting from their specification to go through verification, automatic synthesis and testing. The main languages for dealing with this type of project and the most advanced automatic tools for their manipulation are also presented. At the end of the course the students will have to demonstrate that they have the following ability to apply the acquired knowledge: to identify, starting from the specifications, the best architecture for a complex IoT system; model, design and verify complex analog / digital components; develop embedded software and interact with IoT and cloud architectures; partition a functionality between HW and SW with attention to network architecture and operating systems; build a project report highlighting the critical aspects resolved; to be able to use additional languages for the design of IoT systems starting from those studied in the course.
Program
Networked Embedded Systems
-----------------------------
- Wireless embedded systems and related transmission protocols
- Energy management
- Networked control systems
- Applications to home automation, industry, and agriculture
IoT systems
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- Network analysis tools
- The synchronization problem and Network Time Protocol (NTP)
- Containerization and orchestration: Docker and Kubernetes
- The pub/sub paradigm, MQTT and Kafka
- The concept of Compute Continuum
- Multimedia transmission over IP and the Quality of Service problem
Learning assessment procedures
The exam consists of:
1) oral test on the computer with questions on the theoretical and practical part;
2) an optional development of a project
- individual or team-based
- for those who have already passed the oral test, obtaining a score greater than or equal to 25
- effort: 40 hours of work
- to be closed by the end of September
- possible synergies, on request, with other courses, internships, theses
- max score: 3
