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Corso di laurea magistrale

Piano di Studi

Primo anno

  • Computer Architecture and Digital Systems (12 cfu)

    • The course aims to understand the high-performance and energy-efficient computer architecture, as a basis for informed software performance engineering and as a foundation for advanced work in computer architecture, compiler design, operating systems and parallel processing. Further objectives are to enable students to master digital integrated circuit design trade-offs. Experience state-of-the-art electronic design automation tools and high-level design methodologies for FPGA and semi-custom technologies. Understand sensor based electronic systems including sensor conditioning and sensor data fusion.
  • Dependable and Secure Systems (9 cfu)

    • The objective of this course is to teach the theoretical background and the basic methodologies for developing dependable and secure networked embedded systems. The course enables the students to design and analyze secure and dependable networked embedded systems in several application domains such as (wireless) sensor networks, robotics, avionics, automotive, multimedia, and biomedical systems. The security part of the course introduces the security requirements and a threat model for embedded systems. The dependability part introduces fundamentals of reliability in digital control systems: faults, errors and failures of hardware/software components; reliable system design techniques and approaches to reliability modeling and evaluation. The formal methods part presents the fundamental techniques for the formal specification of a system and the formal verification of its properties, with particular emphasis on embedded systems with real time constraints.
  • Real Time and Distributed Systems (12 cfu)

    • The objective of this course is to teach the theoretical background and the basic methodologies for developing time sensitive applications with high degree of concurrency and a set of performance requirements. The course enables the students to design and analyze real-time software in several application domains, as sensory monitoring, robotics, avionics, automotive, multimedia, and biomedical systems. The first module of the course introduces the computational model of real-time activities with time, precedence, and resource constraints. The second module of the course focuses on programming concurrent and distributed applications that play a primary role in systems where many events occur simultaneously.
  • Optimization Methods (6 cfu)

    • The goal of this course is to provide analysis of mathematical methods of optimization. Applications are mainly devoted to networks and equilibrium problems. Algorithms and optimization software are analyzed.
      Topics are: Linear and integer optimization; Nonlinear optimization; Multiobjective optimization; Non-cooperative game theory ; Optimization software.
  • Design of Embedded Systems (9 cfu)

    • The objective of the course is to teach how to deal with all stages in the development process, including requirements, specifications, design models, coding, testing, simulation, verification, as well as autocode generation techniques. The course covers the main stages in the development of embedded systems, with emphasis on model-based development and formal methods for the analysis of system properties.
  • Digital Control Systems and Mechatronics (12 cfu)

    • The objective of this course is the understanding of the basic control theories for digital systems. The course presents physical modeling problems and reviews typical architectures for the control of electro-mechanical systems. The course will enable students to understand electronic circuits and design the related control software for the control of mechanical systems. Module1 presents mathematical theories of modeling and control, Module2 the mechatronics problem.
  • Secondo anno

  • Internet of Things (6 cfu)

    • The objective of this course is to teach the principles of internetworking of embedded devices and the state-of-art architectures, technologies and protocols aimed at enabling the formation of highly distributed and ubiquitous networks of seamlessly connected heterogeneous devices which can be fully integrated into the current Internet, fully in line with the Internet of Things paradigm. The course enables the student to design and analyze such networks in order to support the development of intelligent services with given performance requirements in a variety of application domains.
  • Robotics and Human-Machine Interfaces (6 cfu)

    • The objective of the course is to provide students
      • the capability of solving problems using tools developed for the analysis of robots;
      • the practical ability in designing and integrating a robotic-mechatronic system;
      • the theoretical and practical knowledge of algorithms and architectures that integrates Human-Robot interaction. This course is organized in two sections. The first part aims at providing the students with the basic concepts needed for the modeling and control of robots. The second part of the course introduces the student to a specific field of Human-Robot Interaction.
  • Prova finale (15 cfu)

  • Virtual and Augmented Reality (6 cfu)

    • The objective of the course is to provide an overview of the opportunities and the main issues related to designing and developing VR/AR systems architectures, both in local and in distributed (even web-based) contexts, and to the development of VR/AR applications with a multimodal perspective and approach. The course will provide a general introduction of Virtual and Augmented Environments followed by an analysis of features, requirement and issues in real-life applications. The course will include practical exercises aiming to design and develop a simple 3D real-time interactive applications exemplificative of real-life application contexts.
  • Computational Intelligence (6 cfu)

    • The objective of this course is to teach the theoretical background and the basic methodologies for developing intelligent systems, i.e., systems that show the remarkable ability to reason and learn in uncertain and imprecise environments. The course enables the students to design and develop intelligent systems in several application domains. The course covers the theory and application of a number of computational intelligence methodologies, including artificial neural networks, fuzzy inference systems and genetic algorithms.
  • Industrial Applications (12 cfu)

    • The course aims to explain the architecture, the technologies and the design methodologies that characterize industrial applications from the informatics point of view. Students will be able to design and realize industrial applications, by considering algorithms, interface with sensors and actuators, hardware infrastructures, programming interfaces, software architectures and RTOS. A significant part of the course is devoted to the development of an industrial application, starting from the ideation up to the implementation on real hardware of sample prototypes.
  • Free activity (9 cfu)

    • Si suggerisce allo studente di utilizzare un corso del proprio piano di studi

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