Description

Theory
2

Laboratory
2

Instructors

Paula Viana

Contents

This course addresses new paradigms, technologies and applications of Computing Systems (CS), encompassing the following domains:
- distributed, embedded, ubiquitous & cyber-physical CS; Internet-of-Things (IoT)
- mobile CS & mobility support
- CS for multimedia & entertainment
- high-performance, parallel and distributed CS
- real-time & safety-critical CS
- cloud, fog & edge CS
- location/context-aware & human-centric computing
- human-computer interaction (HCI), virtual & augmented reality
- artificial intelligence & computer vision
- communication networks & protocols
- operating systems, programming languages & simulation/software development environments.

The student should be able to identify, select and test technologies not covered in previous courses, according to real problem requirements. He/she should be able to define the functional and non-functional properties of computing systems/applications, which enable to design and implement the specified system.
 

Learning Outcomes

The main objective of this course is for the student to gain theoretical and practical competences in "advanced" Computing Systems, namely being able to identify, understand, integrate and use novel paradigms and technologies in emerging domains that may include:
- industrial automation systems, e.g. in the Industry 4.0 and M2M contexts;
- smart home/building, e.g. security, comfort, entertainment, energy efficiency, system/functionality integration;
- smart mobility and autonomous systems, e.g. autonomous vehicles (land, air, water), domestic robots, health support robots;
- "infotainment", telecommunications and multimedia systems, e.g. TV box, gaming, virtual/augmented reality, human-computer interaction;
- large-scale (area, density) monitoring/control systems, e.g. homeland security, environmental monitoring, precision agriculture, structural health monitoring (bridges, tunnels, stadiums, monuments) and critical infrastructures (gas, water, electricity, sewage, telecommunication networks);
- urban, social and participatory sensing, e.g. people/data-centric applications, location/context-aware computing, crowd-sourcing;
- smart environments and assisted health/living (remote healthcare, wearable computing, assisted living);
- detection, identification, localization, classification, mapping and tracking of objects/targets, namely through multiple sensor fusion;
- artificial intelligence techniques and tools, building on both "classic" and "generative" and natural language processing paradigms.