|SCIENTIFIC DISCIPLINARY SECTOR||ING-INF/01|
|LANGUAGE||Italian (English on demand)|
The course aims to provide a broad overview of the various types of state-of-the-art cyberphysical sytems: synchronous, asynchronous, continuous-time dynamic, timed, and hybrid systems. The treatment of systems covers modeling, simulation, and verification (model checking) topics. Each topic is also addressed through the use of appropriate development tools, such as nuXmv, Spin, Uppaal, Matlab-Simulink-Stateflow. Part of the course introduces the python language, with emphasis on application to data science and machine learning
This course is intended to provide an introduction to the analysis and design of cyberphysical systems. This includes synchronous and asynchronous processes, safety and liveness requirements, and dynamic and timed systems. The course is also intended to provide an introduction to the Python language, with emphasis on application to data science and machine learning.
By taking the course, the student should come to possess a broad knowledge about the various types of cyberphysical sytems in the state of the art, such as: synchronous, asynchronous, continuous-time dynamic, timed, and hybrid systems. For each type of system, modeling, simulation, and verification (model checking) topics are covered. The student will have the opportunity to learn the theoretical foundations, and to study some application examples. Exercises are proposed, and usually solved in class, for each topic in order to test the acquisition of knowledge. The student will also learn to use a development tool for each type of cyberphysical system covered (nuXmv, Spin, Uppaal, Matlab-Simulink/Stateflow).
Part of the course will introduce the python language, which is useful for processing data acquired from the above systems, with emphasis on data science and machine learning.
The project that will be agreed upon for the exam is aimed at stimulating and verifying the student's design and implementation skills, as well as the operational field verification of part of the acquired knowledge.
The learning outcomes concern the realization of the above training objectives, including through the implementation of a project. At the end of the course the student will be able to analyze and design engineering solutions based on various types of cyber-physical systems, in various types of applications.
Digital Systems Electronics
Computer architecture basics
Lectures, with use of slides, and examples/exercises carried out both on blackboard and PC (or tele-learning, if made necessary), using the development/simulation tools indicated in class. Student reception. Proposal, implementation and discussion of a project.
Modeling, simulation and verification of cyberphysical systems
- Synchronous models
- Safety requirements
- Asynchronous models
- Liveness requirements
- Dynamic systems
- Timed systems
- Hybrid systems
Introduction to the python language
- Data types
- File systems
- numpy library
- Pandas library
- (pyplot library)
R. Alur, Principles of Cyberphysical Systems:
J. VanderPlas, Python Data Science Handbook, O'Reilly
Lecture notes and other material suggested by the lecturer during the course
Office hours: On appointment: mail (email@example.com) or on Teams or after lecture
FRANCESCO BELLOTTI (President)
ALESSANDRO DE GLORIA
All class schedules are posted on the EasyAcademy portal.
Oral exam on the first part (cyber-physical systems), including both theoretical questions and exercises, on the topics covered in class.
Project work (on modeling/simulation of a cyber-physical system or on an IoT/machine learning/data science application).
Assessment will be through questions/exercises in the oral examination. As for the project, assessment will take place in the preparatory interviews and during the design/implementation of the solution and in the final discussion of a paper descriptive of the work done.
The evaluation will also take into account the student's participation during the course.
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