AI-Powered Drone Detection for Security and Safety

Safety & Security · Research & Development

What it collects

About a measurement

Anonymized data

Passive signals generated by the rotating propellers of drones — acoustic, RF, or related electromagnetic emissions — captured by sensors deployed in the environment. No personal information is collected.

Government of Canada AI Register — Drone Detection

Run by: National Research Council Canada (NRC)
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

Research & Development

This system uses AI to passively detect, track, and characterize unmanned aerial systems (drones) by analysing the acoustic or radar signals produced by their rotating propellers — not by matching images. It is a research and development tool operated by the National Research Council Canada, currently used by Government of Canada employees. The system is not yet disclosed to the public when in operation.

What it collects and what happens to it

Data taken in

About a measurement

Anonymized data

Passive signals generated by the rotating propellers of drones — acoustic, RF, or related electromagnetic emissions — captured by sensors deployed in the environment. No personal information is collected.

Government of Canada AI Register — Drone Detection

Processing

Anomaly Detection

Flags unusual aerial signals corresponding to drone presence, distinguishing them from background clutter in complex environments. Designed to generate very few false alarms.

Government of Canada AI Register — Drone Detection

Classification & Prediction

Classifies and characterises detected drones based on propeller-signal features. Tracks identified targets over time and predicts drone trajectories in cluttered low-altitude settings.

Government of Canada AI Register — Drone Detection

What it does

Sensing (Perceptive AI)

Autonomous

The system passively senses signals generated by drone propellers and converts raw signal data into structured detections — identifying, tracking, and characterising drones without requiring human initiation of each detection event.

Government of Canada AI Register — Drone Detection

Deciding (Analytical AI)

Human decides

The AI classifies and tracks drone targets by analysing propeller-signal characteristics, producing detection scores and classifications that operators use to decide on appropriate responses.

Government of Canada AI Register — Drone Detection

Outputs

About a measurement

Anonymized data

Detection alerts, drone tracking data, and characterisation outputs (e.g. drone type, trajectory, position) derived from propeller-signal analysis. Outputs relate to the drone object, not to personally identifiable individuals.

Government of Canada AI Register — Drone Detection

Run by

National Research Council Canada (NRC)

NRC's Digital Technologies Research Centre, in collaboration with Defence Research and Development Canada (DRDC), developed and deploys this drone-detection system. Primary users are Government of Canada employees.

Government of Canada AI Register — Drone Detection

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me

Detection outputs are available only to authorised Government of Canada employees. Members of the public, including drone operators whose craft may be detected, cannot access data produced by this system.

Government of Canada AI Register — Drone Detection

Available to the accountable organization

Detection data and characterisation outputs are available to NRC and DRDC personnel operating and evaluating the system.

Government of Canada AI Register — Drone Detection

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 TransparencyThe register indicates that AI use is not currently disclosed to users or the public. As the system moves toward operational deployment, affected parties would have a right to be informed of AI use in their environment. Contact the National Research Council Canada for inquiries about the system's operation.

Risks and safeguards

Civil liberties harmAlthough the register states no personal information is collected, passive signal-based detection could, if expanded, implicate surveillance of individuals operating drones in lawful contexts.Safeguard: The system targets drone propeller signals rather than images or identity data, reducing personal-information exposure. Deployment is currently limited to GC employees in R&D contexts. AI use is not yet disclosed to affected parties, which poses a transparency risk; mitigation would require public notification prior to operational deployment.