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ADVANCED MACHINE LEARNING AND EDGE COMPUTING

CODE 106801
ACADEMIC YEAR 2022/2023
CREDITS
  • 10 cfu during the 2nd year of 8732 INGEGNERIA ELETTRONICA (LM-29) - GENOVA
  • TEACHING LOCATION
  • GENOVA
  • MODULES This unit is composed by:
    TEACHING MATERIALS AULAWEB

    OVERVIEW

    ('Edge Computing' module)

    The Internet of Things (IoT) produces large amounts of data to be transmitted and processed before they can be exploited, Edge Computing addresses the processing and interpretation of data in proximity to their origin. This approach, through machine learning techniques, increases the autonomy and 'decision-making capacity' of the electronic system at the edge. Consequently, the exploitation of the transmission band, the overall resources required, the response times and performance in general are optimized too. The reference hardware platform is typically represented by network interconnected microcontrollers, sensors and transducers. The course introduces then architectures of these systems, programming of microcontrollers and interfaces, software development tools and the most spread platforms, to apply machine learning techniques.

    AIMS AND CONTENT

    LEARNING OUTCOMES

    (Edge computing module) The course aims providing the fundamental elements of edge computing, focusing on programming advanced microcontrollers. Addressed topics concern also analog-to-digital conversion, communication protocols, sensors cards (eg MEMS) and embedded operating systems. Each topic is discussed through several examples and experimental exercises.

    TEACHERS AND EXAM BOARD