LEARNING OUTCOMES

The course aims to provide students with essential knowledge on telecommunications networks and signal processing / analysis in industrial contexts and, in particular, in the context of Industry 4.0. At the end of the course, the student will know the basic principles of telecommunications networks, the main technologies / standards related to wired and wireless networks applicable in industrial environments, the architecture and Internet protocols and the basic aspects related to the theme of cyber security. He will also have learned the essential concepts related to the representation of analogical and digital information and to the analysis of data through machine learning

AIMS AND LEARNING OUTCOMES

After the course, the student will have learnt the basic principles of telecommunication networks, the main technologies and standards related to wired and wireless networks for industrial environments, the architectures and the protocols of Internet, and the basic aspects of cyber security. The student will also have learnt the basic concepts associated with information representation through analog and digital signals and with signal analysis through machine learning, with special focus on supervised classification techniques.

TEACHING METHODS

Class lectures

SYLLABUS/CONTENT

• Basic principles of telecommunication networks
• Main technologies and standards for wired and wireless networks in industrial environments
• Internet architecture and protocols
• Basic aspects of cyber security
• Basic principles of information representation through analog and digital signals
• Basic aspects of signal analysis through machine learning
• Case studies of machine learning applications in industrial contexts and Industry 4.0
• Introductory concepts of deep learning

RECOMMENDED READING/BIBLIOGRAPHY

• Slides used in class and made available on AulaWeb
• Bishop C., Pattern recognition and machine learning, Springer, 2006
• Carlson A. B., Crilly P., Communication systems, McGraw-Hill, 2009
• Hastie T., Tibshirani R., and Friedman J., The elements of statistical learning, Springer, 2008
• Goodfellow I., Bengio Y., and Courville A., Deep learning, MIT Press, 2016
• Kurose J. F. and Ross K. W., Computer networking: a top-down approach, 7th Edition, McGraw-Hill, 2017
• Stallings W., Data and computer communications, 10th Edition, Prentice Hall, 2013
• Stallings W., Wireless communication networks and systems, Global Edition, Prentice Hall, 2016
• Tanenbaum A. S. and Wetherall D. J., Computer networks, 5th Edition, Prentice Hall, 2010