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Line 25: − + − − + − [[File:IUU Non compliance example.png|center|frameless|757x757px]]The functionality of the POC is further complemented by developing another predictive model to find spatial hot spots of fishing activities. For example, a heat map of highly active fishing areas across all Quebec region fisheries is shown below.+ +
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Supported by the 2020 – 2021 Results Fund, a Proof of Concept (POC) was developed for the automated detection of vessel fishing activity using an AI model. The resulting predictive model takes vessel movement tracks as input and outputs the vessel tracks annotated with its activity i.e. fishing or not-fishing, as illustrated below. The model uses features such as vessel speed standard deviation, course standard deviation, and fishing gear type to detect vessel activity.
Supported by the 2020 – 2021 Results Fund, a Proof of Concept (POC) was developed for the automated detection of vessel fishing activity using an AI model. The resulting predictive model takes vessel movement tracks as input and outputs the vessel tracks annotated with its activity i.e. fishing or not-fishing, as illustrated below. The model uses features such as vessel speed standard deviation, course standard deviation, and fishing gear type to detect vessel activity.
[[File:FishingDetectionModel2.png|alt=|center|thumb|767x767px|'''<small>The results of applying the predictive model for detecting fishing behaviour. The left image shows the vessel trip before applying the model. The right image shows the vessel trip annotated with fishing activity. Green points indicate fishing points.</small>''']]
[[File:FishingDetectionModel.png|center|frameless|767x767px|'''Predictive model for detecting fishing behaviour: input and output'''|alt=]]
The insight gained from the predictive model is then combined with other data sources, such as fisheries management areas and license conditions to detect non-compliance with fisheries regulations. An example of such functionality is shown below.
The insight gained from the predictive model is then combined with other data sources, such as fisheries management areas and license conditions to detect non-compliance with fisheries regulations. An example of such functionality is shown below.
[[File:Ex-non2.png|alt=|center|thumb|800x800px|<small>'''The left image: an example of compliance: a fishing trip adhering to the fishing zone restriction.'''</small>
'''<small>The right image: an example of non-compliance: a fishing trip fishing outside its allowable zones.</small>''']]
The functionality of the POC is further complemented by developing another predictive model to find spatial hot spots of fishing activities. For example, a heat map of highly active fishing areas across all Quebec region fisheries is shown below.
[[File:Hotspot.png|center|frameless|536x536px]]
[[File:Hotspot.png|center|frameless|536x536px]]
