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AI-Assisted Water Level and Flood Risk Monitoring for Rail Lines

Safety & Security

What it collects

About a measurement
Anonymized data
  • Lidar point-cloud data from hi-rail vehicles measuring terrain elevation, water surface elevation, and proximity to rail infrastructure.
About a place
Anonymized data
  • Drone and satellite imagery capturing the geographic area surrounding rail lines, including water bodies, drainage features, and terrain.
Run by
Transport Canada (TC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

Safety & Security

This system uses algorithms to assess water levels and flooding risk near railway infrastructure using data from drones, satellites, and lidar sensors mounted on hi-rail vehicles. It is primarily used by Government of Canada employees at Transport Canada to support rail safety decisions. Members of the public are not directly affected by individual decisions, but the system contributes to the safety of railway infrastructure that serves Canadians.

What it collects and what happens to it

Data taken in

About a measurement
Anonymized data
  • Lidar point-cloud data from hi-rail vehicles measuring terrain elevation, water surface elevation, and proximity to rail infrastructure.
About a place
Anonymized data
  • Drone and satellite imagery capturing the geographic area surrounding rail lines, including water bodies, drainage features, and terrain.

Processing

Classification & Prediction
  • Algorithms classify water level conditions and estimate flood risk scores from fused drone, satellite, and lidar sensor inputs.
Computer Vision
  • Interprets drone and satellite imagery to detect water bodies, flooding extent, and changes in surface water near rail corridors.

What it does

Deciding (Analytical AI)
Human decides
  • Algorithms predict and classify water level and flood risk conditions from sensor data; GC employees review and act on the outputs.
Sensing (Perceptive AI)
Human decides
  • Processes raw drone imagery, satellite imagery, and lidar point-cloud data into structured measurements and detections usable by downstream analysis algorithms.

Outputs

About a measurement
Anonymized data
  • Water level assessments and flood risk scores derived from sensor fusion, produced for locations along rail corridors and made available to Transport Canada employees.
A recommendation or prediction
Anonymized data
  • Risk assessments advising GC employees on flooding conditions near rail lines, supporting decisions about rail safety interventions.

Run by

Transport Canada (TC)
  • Transport Canada is the federal department accountable for developing and deploying this water-level and flood-risk monitoring algorithm for rail infrastructure safety.

Government of Canada AI Register — 2526-TC-013

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs are available to Government of Canada employees at Transport Canada who use them to inform rail safety decisions.
Not available to me
  • The algorithmic outputs are internal to Transport Canada and are not directly accessible by members of the public.

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 TransparencyThis system is listed on the Government of Canada's Algorithmic Impact Assessment registry (AI Register ID 2526-TC-013), where general information about its function is publicly available. Members of the public may consult the registry at open.canada.ca.

Risks and safeguards

  • Physical harmInaccurate flood-risk assessments could lead to missed warnings or unnecessary rail service disruptions, potentially affecting passenger and worker safety.Safeguard: Outputs are reviewed by GC employees before action is taken; the system supports rather than replaces human safety decisions.