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 Insect Detection and Classification for Biodiversity Tracking

Ecology · Research & Development

What it collects

About a measurement
Anonymized data
  • Photographs of sticky traps containing captured arthropods, taken in agricultural field settings. These images contain no personal information.
Operational data
Anonymized data
  • Scientific research papers are used as a data source to inform the species classification models, providing taxonomic and biological reference information.
Run by
Agriculture and Agri-Food Canada (AAFC)
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

EcologyResearch & Development

This system uses computer vision models to automatically detect and identify insect species from photographs of sticky traps used in agricultural monitoring. Results are displayed on an online dashboard to help government scientists track arthropod biodiversity. The system does not process any personal information and is used exclusively by Government of Canada employees. Its use of AI is disclosed to users.

What it collects and what happens to it

Data taken in

About a measurement
Anonymized data
  • Photographs of sticky traps containing captured arthropods, taken in agricultural field settings. These images contain no personal information.
Operational data
Anonymized data
  • Scientific research papers are used as a data source to inform the species classification models, providing taxonomic and biological reference information.

Processing

Computer Vision
  • Computer vision and image recognition models are used to locate and identify arthropod species within sticky-trap photographs.
Classification & Prediction
  • Classification models assign detected arthropods to species categories. Calculation and workflow automation are also applied to support biodiversity tracking outputs.

What it does

Sensing (Perceptive AI)
Human decides
  • Computer vision models read sticky-trap photographs and produce structured detections of arthropod species present in each image, which are then surfaced to GC scientists via a dashboard.
Deciding (Analytical AI)
Human decides
  • The system classifies detected arthropods into species categories and applies workflow automation to support biodiversity tracking calculations and reporting.

Outputs

About a measurement
Anonymized data
  • Species identification results and biodiversity counts derived from sticky-trap images, displayed on an online dashboard for GC scientists. No personal data is included in the outputs.
A recommendation or prediction
Anonymized data
  • Dashboard visualizations provide GC scientists with advisory biodiversity insights derived from arthropod classifications, supporting but not replacing expert scientific judgment.

Run by

Agriculture and Agri-Food Canada (AAFC)
  • Agriculture and Agri-Food Canada is the federal department responsible for developing and deploying this arthropod detection system to support biodiversity tracking in agricultural contexts.

Government of Canada AI Register — record 2526-AAFC-AAC-007

Built by

Government of Canada
  • The system was developed internally by the Government of Canada, with no external vendor identified in the register entry.

Government of Canada AI Register — record 2526-AAFC-AAC-007

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me
  • The system outputs are accessible only to GC employees. The system processes no personal information, so individual access rights do not apply to members of the public.
Available to the accountable organization
  • Results and dashboard outputs are available to Agriculture and Agri-Food Canada employees for biodiversity tracking and scientific analysis.

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 Government of Canada discloses that AI is used in this system to GC employees who are the primary users. The system is listed in the public Government of Canada AI Register, making its existence and general purpose publicly accessible.
  • Right to Be Informed of AI UseAI use is disclosed to users of the system. GC employees interacting with the dashboard are informed that the classification results are produced by an AI model.

Risks and safeguards

No risks or safeguards have been published for this system yet.