DATA RELIABILITY
Without reliable data, no energy performance is possible
Your sub-meters are collecting data… but is it reliable? Data gaps, inconsistencies between sub-meters and main meters, invisible drift. You may be making decisions based on faulty data. Without reliable data, no energy strategy holds.
The problem
Frequent anomalies that distort your steering
- communication losses with some meters
- inconsistencies between supervision and databases
- gaps between sub-meters and main meters
- data gaps or irregular time steps
Result:
- biased energy analyses
- reporting errors
- invisible overconsumption
Ultimately: decisions made on uncertain foundations.
Our approach
Bring your consumption data under control, for the long term
Level 1 — Data integrity
- detection of data gaps and duplicates
- time step and timestamp verification
- identification of outliers
Level 2 — Meter consistency
- logical index progression
- detection of frozen or disconnected meters
- meter vs. sub-meter sum comparison
Level 3 — Energy analysis
- spike identification
- consistency with occupancy and season
- detection of drift and atypical behavior
Automated checks executed once a week.
Anomaly detection
Quickly identify what's drifting
The system automatically detects:
- consumption drift (AHU filters, water leaks…)
- abnormal spikes, inconsistencies
- atypical energy behaviors
Anomalies are displayed clearly:
- gap visualization
- color-coded severity indicators
- action prioritization
The operator knows where to act, without wasting time.
The result
Reliable data, precise energy management
With Foobot:
- quickly detect anomalies
- improve visibility into energy performance
- make operations teams' work easier
- keep your data usable over time
Move from data you endure to energy management you control.