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== Introduction ==

== Introduction ==

The Department of Fisheries and Oceans (DFO) Canada manages over 200 fisheries on the three coasts. Successful fisheries management is dependent on effective fisheries monitoring. The goal of fisheries monitoring is to provide accurate, timely, and accessible fisheries data, which is needed to effectively implement management measures such as target and bycatch limits, quotas, and closed areas.

The Department of Fisheries and Oceans (DFO) Canada manages over 200 fisheries on the three coasts. Successful fisheries management is dependent on effective fisheries monitoring. The goal of fisheries monitoring is to provide accurate, timely, and accessible fisheries data, which is needed to effectively implement management measures such as target and bycatch limits, quotas, and closed areas.

=== Implementation Approach ===

=== Implementation Approach ===

In 2022-2023, DFO issued a competitive Request for Proposal in collaboration with Public Service and Procurement Canada to solicit bids from contractors qualified on the Government of Canada's AI suppliers list. As a result of this process, the company AI.Fish won the contract and is currently developing the solution. The initial scope of the project is to develop an AI-assisted solution for fishing catch estimation and apportionment in Pacific trawl fisheries. As of the fiscal year 2022-2023, the project has entered '''Stage C: the Proof of Value phase'''.

In 2022-2023, DFO issued a competitive Request for Proposal in collaboration with Public Service and Procurement Canada to solicit bids from contractors qualified on the Government of Canada's AI suppliers list. As a result of this process, the company AI.Fish LLC won the contract and is currently developing the solution. The initial scope of the project is to develop an AI-assisted solution for fishing catch estimation and apportionment in Pacific trawl fisheries. As of the fiscal year 2022-2023, the project has entered '''Stage C: the Proof of Value phase'''.

[[File:Picture3.png|center|thumb|618x618px|The Development Stages of the Project]]

[[File:Picture3.png|center|thumb|618x618px|The Development Stages of the Project]]

== Model Development and Performance Results ==

== Model Development and Performance Results ==

== Demo ==

== Demo ==

== The Proof of Value Phase ==

== The Proof of Value Phase ==

The project currently is at the proof of value phase. The process for reviewing involves reviewers following their usual routine, where clips relevant to the participating boats from different tows are extracted from the loaded footage into FishVue Interpret and then loaded into the Proof of Concept solution. The reviewer is tasked with selecting at least 3 to 5 images from each tow for catch apportionment analysis. Afterward, they will review these catch apportionment results, utilizing them to inform and make more accurate catch estimates. Moreover, a sample of tows will undergo a full manual review. This step is crucial as it allows for the assessment of the impact on the accuracy of the catch estimates.

The project currently is in the Proof of Value (POV) phase. The process for reviewing involves reviewers following their usual routine, where clips relevant to the participating boats from different tows are extracted from the loaded footage into FishVue Interpret and then loaded into the Proof of Concept solution. The reviewer is tasked with selecting at least 3 to 5 images from each tow for catch apportionment analysis. Afterward, they will review these catch apportionment results, utilizing them to inform and make more accurate catch estimates. Moreover, a sample of tows will undergo a full manual review. This step is crucial as it allows for the assessment of the impact on the accuracy of the catch estimates.

 

* Number of catch apportionment results rejected by reviewers (single images).

* Number of catch apportionment results rejected by reviewers (single images)

* Number of total catch apportionment results rejected by reviewers (tows).

* Number of total catch apportionment results rejected by reviewers (tows)

* Accuracy of catch apportionment (deviation compared with manual review).

* Accuracy of catch apportionment (deviation compared with manual review)

* Delta in results between first and second iterations.

* Delta in results between first and second iterations

* Change in administrative user feedback between iterations if any UI/UX adjustments are made.

* Change in administrative user feedback between iterations if any UI/UX adjustments are made

== Next Steps ==

== Next Steps ==

Following the success of both the proof of concept and the proof of value, DFO plans to promote the AI-assisted solution for Pacific trawl fisheries into production in the fiscal years 2023-2024. Furthermore, the department is planning another pilot project for the use of AI in Snow Crab fisheries in the Quebec region.

Following the successful completion of both the proof of concept and the proof of value, the Department of Fisheries and Oceans (DFO) has plans to promote the AI-assisted solution for Pacific trawl fisheries into production in the fiscal years 2023-2024. In addition, the department is also planning another pilot project for the application of AI to monitor Snow Crab fisheries in the Quebec region.