First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
INP6075638, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
IN0527, Degree course structure A.Y. 2008/09, A.Y. 2018/19
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination MEASUREMENT SYSTEMS IN AUTOMATION
Department of reference Department of Information Engineering
E-Learning website
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge GIADA GIORGI ING-INF/07

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines ING-INF/07 Electric and Electronic Measurement Systems 9.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 9.0 72 153.0 No turn

Start of activities 01/10/2018
End of activities 18/01/2019

Examination board
Board From To Members of the board
1 A.A. 2018/2019 01/10/2018 15/03/2020 GIORGI GIADA (Presidente)
NARDUZZI CLAUDIO (Membro Effettivo)

Prerequisites: Basic knowledge of mathematical analysis, probability and statistics, signal elaboration and programming.
Target skills and knowledge: The course of Measurement Systems in Automation aims at providing to the students the essential tools for understanding and properly characterizing the main parts which compose a measurement/acquisition system. For this reason, the course has been structured in three parts concerning theoretical lessons, laboratory tutorials about the use of instrumentation, and practical lessons during which the students have possibility of developing small projects. Theoretical lessons will be mainly focused on the characterization of hardware components, such as sensing devices, acquisition systems, transmission protocols and so on, and how to extract useful parameters for the successive construction of mathematical models for these components. A great attention will be reserved to the discussion of actual standards regarding smart sensors for Internet of Thing (IoT) system and regarding the uncertainty characterization.
Examination methods: Oral discussion
Assessment criteria: Students should demonstrate of having acquired a sufficient capacity in solving problems concerning the design and characterization of a measurement systems.
Course unit contents: Analysis of the main components of a measurement system: sensing devices, acquisition unit, transmission protocols. Tools for the analysis of measurement results: application of the discrete Fourier transform to actual situations, uncertainty analysis. Tutorial on the use of laboratory instrumentation. Distributed measurement systems and related issues such as data management and distribution of a common time reference. The synchronization protocol IEEE 1588. Standard for smart sensors in the IoT scenario: IEEE 1451. Standard for calculating and representing measurement uncertainty. Introduction to transmission protocols, i.e. Lora, for distributed measurement systems.
Planned learning activities and teaching methods: Frontal lessons and laboratory activities.
Additional notes about suggested reading: Documents available from the moodle page of the course.
Textbooks (and optional supplementary readings)
  • Robert Gallager, Gabriele D’Antona, Digital Signal Processing for Measurement Systems. Springer US 2006: ISBN 0-387-24966-4,0-387-28666-7, --. e-book (SpringerLink Books Collection LCL) Cerca nel catalogo