PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)

Context and Challenge

In Italy, monitoring and maintaining infrastructure have become crucial to ensure safety and prevent disasters in a territory prone to seismic and hydrogeological risks. With over 70% of the territory at seismic risk and more than 80% of the landslides registered in Europe, many Italian infrastructures are outdated, exposed to degradation phenomena, and subject to natural stresses that severely challenge their resilience.

Most monitoring activities are still based on manual inspections, which are inefficient and costly. In this context, the proposed project aims to innovate structural monitoring of public and private buildings by introducing an advanced integrated system based on Operational Modal Analysis (OMA) and artificial intelligence (AI) algorithms. This system will provide real-time information on the health status of structures, focusing on critical buildings such as schools and hospitals.

State of the Art and Proposed Innovation

Currently, infrastructure monitoring predominantly relies on periodic on-site inspections, with data management being unstructured and poorly integrated. Technological innovations such as IoT, AI, big data, and cloud computing are only partially utilized in this sector, particularly for applications related to infrastructures like bridges and viaducts. Today, there are several software solutions that implement specific functionalities in the SHM area. However, none of these software implements realtime acquisition, OMA and AI algorithms for structural damage prediction, within a single solution. The project’s main goal is to transfer these innovations to buildings, a less dynamic but equally vulnerable context in terms of seismic events and structural degradation phenomena.

The proposed innovation consists of implementing an integrated system that combines:

• Operational Modal Analysis with algorithms for detecting vibrations, forces, and deformations on multiple floors of buildings.
• Artificial Intelligence for predictive analysis and automatic maintenance based on the collected data.
• IoT and Edge Computing for real-time data collection and processing, enabling continuous and data-centric monitoring.

Project Objectives and Activities

The I.N.S.I.E.M.E. (Infrastrutture Sicure e Intelligenti per un’Efficienza Monitorata ed Evolutiva) project aims to develop a complete prototype system, testing it on an existing school building, the “G. P. Delfino” Primary School in Colleferro. The municipality of Colleferro has expressed interest in testing and validating the project.
The main objectives and activities are as follows:

1. Design and Development of the Integrated System: Design a system consisting of advanced sensors (accelerometers, strain gauges, inclinometer), connected to a hardwaresoftware system capable of acquiring real-time structural and environmental data. Accelerometers will be installed on various floors of the building, particularly on higher floors where the modal response is more significant.

2. Implementation of Operational Modal Analysis (OMA): Configure algorithms to perform automated Operational Modal Analysis, both in the frequency domain (FDD) and time domain (SSI), to assess the dynamic properties of the building (natural frequencies, mode shapes) under natural operating conditions.

3. Integration of AI Algorithms for Predictive Maintenance: Develop algorithms capable of identifying anomalies and predicting critical points of structural deterioration, enabling timely interventions and optimizing resources dedicated to maintenance.

4. Validation and Testing in Real Conditions: Install and experiment with the prototype
system on the selected building, conducting tests of varying durations to verify the accuracy of monitoring, the reliability of the algorithms, and the system’s efficiency in detecting structural anomalies.