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Case study – FS Engineering
Ingegneria

AI-Based Ground Anomaly Detection

For FS Engineering, an engineering company of the Ferrovie dello Stato Italiane Group, we developed an AI framework capable of identifying anomalies in the ground through the integration of data from various instruments. The platform accelerates analysis and interpretation activities, reducing operational times and supporting more timely technical decisions.

Case study – FS Engineering
Ingegneria

AI-Based Ground Anomaly Detection

For FS Engineering, an engineering company of the Ferrovie dello Stato Italiane Group, we developed an AI framework capable of identifying anomalies in the ground through the integration of data from various instruments. The platform accelerates analysis and interpretation activities, reducing operational times and supporting more timely technical decisions.


FS Engineering
Ingegneria

AI-Based Ground Anomaly Detection

For FS Engineering, an engineering company of the Ferrovie dello Stato Italiane Group, we developed an AI framework capable of identifying anomalies in the ground through the integration of data from various instruments. The platform accelerates analysis and interpretation activities, reducing operational times and supporting more timely technical decisions.

Problem

01.
  • Heterogeneous technical data
  • Slow and complex ground analysis

In the context of infrastructure engineering, the identification of anomalies in the ground requires the analysis of large amounts of data from various instruments. The variety of sources, the complexity of the information collected and the need for accurate technical interpretations can slow down the decision-making process. The challenge was to make the integration and reading of data more efficient, supporting technical teams in the timely identification of potential critical issues.

Solution

02.
  • AI framework for multi-source analysis
  • Automatic integration of instrumental data

For FS Engineering, an engineering company of the Ferrovie dello Stato Italiane Group, we developed an AI framework capable of integrating data from various instruments and identifying anomalies in the ground. The platform analyses the information collected, correlates it and supports technical interpretation activities, providing teams with an advanced tool to accelerate the assessment of soil conditions.

Result

03.
  • Anomalies identified more quickly
  • More timely technical decisions

The platform has accelerated data analysis and interpretation activities, reducing operational times and improving the ability to identify potential ground anomalies. The framework supports faster and more informed technical decisions, helping to make the assessment process more structured, efficient and consistent.

What changed

Before and after introducing
Generative AI

Before

Before

Data scattered across different instruments

Slower technical interpretation

Greater complexity in identifying critical issues

After

After

Data integrated into a single framework

Faster and more structured analysis

AI support for timely technical decisions

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VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
GRID+ Copyright © 2026. All Rights Reserved.
VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
P. IVA 17387741006 · The capital has been paid up in full €10,000 | RM – 1715269
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