AI-Powered Hydrogen Leakage Detection for Refuelling Stations
Safety & Security
What it collects
- Real operational data from HTEC hydrogen refuelling stations, including streaming readings of hydrogen produced and hydrogen filled, used to calculate losses and detect anomalies.
- 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
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
- Real operational data from HTEC hydrogen refuelling stations, including streaming readings of hydrogen produced and hydrogen filled, used to calculate losses and detect anomalies.
- Station-level operational status data covering different combinations of station operations, used to evaluate hydrogen losses across operational modes and identify abnormal behaviour.
Processing
- 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
- 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.
- Continuously ingests streaming sensor data from hydrogen production and filling operations to feed the analytical pipeline in real time.
Outputs
- Daily, weekly, and monthly hydrogen loss statistics; overall station operational status assessments; and hydrogen loss figures for different combinations of station operations.
- Identification of the source component responsible for detected hydrogen loss, presented to station operators as actionable diagnostic information via the monitoring portal.
Run by
- The National Research Council Canada (NRC) developed and deploys this hydrogen leakage monitoring system as part of research into hydrogen refuelling station safety.
Built by
Not stated by the Helpful Places.
Kept for
Not stated by the Helpful Places.
Shared with
- 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.
- AI registerGovernment of Canada AI Register — Hydrogen Leakage Monitor (2526-NRC-CNRC-019)
- AI registerGovernment of Canada AI Register — Hydrogen Leakage Monitor
- Register entryPublished by the Helpful Places. Reference 5d8e9751. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
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.