Health Monitoring of Civil Engineering Structures with Workshop

Name (Acronym)

Health Monitoring of Civil Engineering Structures with Workshop – ICT Laboratory (MSCL)
ECTS

4
Contact E-mail

alessandro.polo.1@unitn.it
Teacher

POLO Alessandro
Syllabus

ESSE3 Page
Institution

DICAM, University of Trento
Study Program

M.S. Ingegneria Civile [LM CIV]
Degree

Master
Language

Italian
Tracks

Structural Health Monitoring, Wireless Technology and Network Planning

ABSTRACT

The course workshop will cover the fundamental components of monitoring systems used for health assessment and decision support in civil structures. The course will explore the process of collecting data from distributed sensing technologies (e.g., accelerometers, load cells) and how these measurements are acquired, converted, and delivered to end-users through digital platforms. Participants will also learn techniques for data validation and cleaning, including noise detection and removal, to ensure the accuracy of data. This process will lead to the creation of Key Performance Indicators (KPIs) for alerting systems, as well as the visualization of real-time data streams and processed information on user devices. The course will include real-world demonstrations of monitoring systems, highlighting their core methodologies and applications. To complement the theoretical lessons, students will engage in hands-on hardware and software exercises, utilizing IoT devices and software tools to reinforce key concepts.

COURSE CONTENT

Part 1: INTRODUCTION AND FUNDAMENTALS

Distributed Monitoring Systems for Civil Structures: Architecture and Building Blocks;
Bridge Monitoring and Early Alerting System (MITIGO App) [Try Yourself];
Sensing, Internet of Things (IoT), and Communication Technologies.

Part 2: DATA ACQUISITION BLOCK: FEATURES AND HANDS-ON EXAMPLES

From Sensors to Data: Sampling and Quantization;
Digital Data Representation and Storage;
Introduction to ARDUINO Internet of Things (IoT) Platform;
Load Cell Measurements with ARDUINO [Hardware Exercitation].

Part 3: DATA PROCESSING BLOCK: ALGORITHMS AND HANDS-ON EXAMPLES

Noise and Anomalies in Acquired Data;
Strategies for Analyzing and Cleaning Data;
Analyze and Process Data with MATLAB [Software Exercitation].

Part 4: DATA VISUALIZATION BLOCK: TECHNIQUES AND HANDS-ON EXAMPLES

Deploying Information to Target Audience;
Early-Alerting Indicator for Structural Health Monitoring (MITIGO Project);
Plotting with MATLAB/GNUPlot [Software Exercitation].

Part 5: DECISION SUPPORT BLOCK: METHODS AND HANDS-ON EXAMPLES

Environmental Measurements: Spatialization and Inference (E-MUSEUM System);
Multi-Resolution Sensing: Improving Accuracy with Machine Learning (TELL-ME System);
Dynamic Resources: From Monitoring to Optimization (INSPECTOR System);
Geo-Referenced Information: Spatial Maps (SHARON System).

TEACHING ACTIVITIES

Theoretical Lessons;
Bridge Monitoring App Hands-On;
Internet of Things (ARDUINO) Hands-On;
MATLAB Hands-On;
Monitoring and Decision Support Systems in Action (Working Examples).