Skip to content
This is NOT an official site of the Government of Canada. Click here for the official AI registry.

Helpful Places

Government of Canada – DTPR AI Register

Back to your search

AI-Powered Hydrogen Leakage Detection for Refuelling Stations

Safety & Security

What it collects

About a measurement
Anonymized data
  • Real operational data from HTEC hydrogen refuelling stations, including streaming readings of hydrogen produced and hydrogen filled, used to calculate losses and detect anomalies.
Operational data
Anonymized data
  • Station-level operational status data covering different combinations of station operations, used to evaluate hydrogen losses across operational modes and identify abnormal behaviour.
Run by
National Research Council Canada (NRC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Not stated by the Helpful Places.
Your copy
You cannot see the data it holds about you. What you can do

What it is for

Safety & Security

This system monitors hydrogen refuelling stations in real time, calculating hydrogen losses from streaming operational data and detecting abnormal station behaviour. It generates daily, weekly, and monthly statistics and identifies which station component is responsible for any detected loss. The system does not process personal information. AI use is disclosed to users of the monitoring portal.

What it collects and what happens to it

Data taken in

About a measurement
Anonymized data
  • Real operational data from HTEC hydrogen refuelling stations, including streaming readings of hydrogen produced and hydrogen filled, used to calculate losses and detect anomalies.
Operational data
Anonymized data
  • Station-level operational status data covering different combinations of station operations, used to evaluate hydrogen losses across operational modes and identify abnormal behaviour.

Processing

Anomaly Detection
  • Detects abnormal operation of hydrogen refuelling stations and identifies the specific source component responsible for hydrogen loss, using learned baselines from streaming operational data.

What it does

Deciding (Analytical AI)
Human decides
  • Calculates hydrogen loss statistics, classifies station operational status, detects anomalies, and identifies source components of hydrogen loss. Results are presented via a monitoring portal for human review.
Sensing (Perceptive AI)
Autonomous
  • Continuously ingests streaming sensor data from hydrogen production and filling operations to feed the analytical pipeline in real time.

Outputs

About a measurement
Anonymized data
  • Daily, weekly, and monthly hydrogen loss statistics; overall station operational status assessments; and hydrogen loss figures for different combinations of station operations.
A recommendation or prediction
Anonymized data
  • Identification of the source component responsible for detected hydrogen loss, presented to station operators as actionable diagnostic information via the monitoring portal.

Run by

National Research Council Canada (NRC)
  • The National Research Council Canada (NRC) developed and deploys this hydrogen leakage monitoring system as part of research into hydrogen refuelling station safety.

Government of Canada AI Register — Hydrogen Leakage Monitor

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me
  • This system does not involve personal information. There is no personal data about members of the public held in this system for individuals to access.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Algorithmic TransparencyAI use in this system is disclosed to users of the monitoring portal. For further information on how the system works, contact the National Research Council Canada.

Risks and safeguards

  • Physical harmUndetected hydrogen leakage at refuelling stations poses serious explosion and fire hazards.Safeguard: The system provides real-time monitoring and anomaly detection with a portal for human review, enabling station operators to intervene promptly. The system is advisory — final safety decisions remain with human operators.