End User
Veolia
Description
The Anomaly Detection and Fault Diagnosis service detects abnormal patterns in the Torrelago district heating network using AI-based techniques applied to real-time and historical data. By establishing expected behavioural baselines from historical patterns and continuously comparing real-time data against these baselines, the service provides early warnings of inefficiencies, faults, and unexpected operational conditions.
Core Capabilities
Monitoring & Anomaly Detection
Business Need
DHN operators need continuous visibility into system behaviour to detect inefficiencies, faults, and abnormal conditions as early as possible. Building on initial anomaly identification in Service 1, this dedicated service provides a more advanced framework with severity indicators and diagnostic insights to support proactive intervention before issues escalate into costly operational problems.
Key Performance Indicators
Detection rate: proportion of true anomalies correctly identified
False alarm rate: proportion of alerts not corresponding to genuine anomalies
Response time: lead time from anomaly onset to alert generation
Diagnostic usefulness: clarity of origin attribution per detected anomaly
Data Provided
Time-stamped anomaly alerts with severity indicators
Diagnostic insights indicating the likely source of the deviation
Visual dashboards showing deviations from expected behaviour and historical trends
TEF
TEF DHN