The acquisition of information about physical quantities by means of sensors historically fostered the interpretation of measurement as a merely experimental activity. Conversely, measurement is a complex activity, far more complex than suitably connecting and reading an instrument. Indeed, measurement always requires descriptive activities to be performed prior of the execution of empirical activities to ensure both the correct implementation of the experiments and the interpretation of the obtained information.
In this tutorial, a conceptual framework highlighting the activities required to develop a measurement is presented and discussed. In such a framework, synthesized in Fig.1, measurement is envisioned as a three-level hierarchically structured process constituted of stages (planning, execution and interpretation), each one composed of activities performed through multiple tasks. A loose temporal sequence drives the execution of tasks (black arrows in the diagram), but the systematic presence of feedback (white arrows) emphasizes the complexity of the whole process.
The framework is very general. It supports a methodologically correct development of any measurement, regardless the kind of involved quantities (either physical or non-physical) or the field of application.
The framework is based on the following widely accepted assumptions:
- measurement is required to provide objective and inter-subjective information about properties of empirical objects, phenomena or events;
- measurement is not a self-motivating activity, but it is rather a goal-driven process: obtained information is usually employed as relevant input when deciding the best actions to be performed to achieve established goals, while satisfying given conditions;
- any empirical property can be, in principle, measured by performing logically equivalent steps;
- models are unavoidable in measurement, and they are co-determined by the measurement goals.
At the end of this tutorial the attendee will be able to answer such questions as: Which informative empirical processes can be considered measurements? How do I determine an adequate model for a given measurement? How do I estimate and express the quantity of information I achieve through measurement?
Fig.1. Conceptual framework showing different activities involved in measurement development.
The target audience of the tutorial are graduate students and researchers in every single field of experimental sciences or engineering, interested in approaching measurements with a solid theoretical background.
Dario Petri is a Full Professor of measurement and electronic instrumentation and the head of the Department of Industrial Engineering, University of Trento, Trento, Italy. He is also an IEEE fellow member, the VP for Finance of the IEEE Instrumentation and Measurement Society since 2013 and the chair of the IEEE Smart Cities Initiative in Trento since 2015.
He was the Head of the Department of Information Engineering and Computer Science of the University of Trento, from 2010 to 2012, the chair of the Italian Association of Electrical and Electronic Measurements (GMEE) from 2013 to 2016 and the chair of the IEEE Italy Section from 2012 to 2014. He was also a member of the Italian Group of Expert of Evaluation (GEV) for research in the area of Industrial and Information Engineering in 2016 and 2017.
Dario Petri received the M.Sc. degree (summa cum laude) and the Ph.D. degree in electronics engineering from the University of Padua, Padua, Italy, in 1986 and 1990, respectively.
During his research career, Dario Petri has been an author of about 300 papers published in international journals or in proceedings of peer reviewed international conferences. His research activities cover different fields and are focused on data acquisition systems, embedded systems, instrumentation for smart energy grids, fundamentals of measurement theory, and application of digital signal processing to measurement problems.