AI initiative registry
Every initiative listed in the registry can be consulted here, without an account. Each record shows its progress, its milestones and the history of its decisions. Requests still under triage do not appear: they join the registry once reviewed.
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63 initiative(s)
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10
AI Agent for EGCSAI Agent for EGCS to evaluate Gs&Cs applications from external applicants (not until 2026-27)
Idea Chief Digital Officer Automation and Decision Support
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172
AI model for Condtions of Licences reviewPac has 130 COls. These have been individually edited over the past decades. An AI model to search and identify difference in wording for similar Conditions
Idea Programs Sector Automation and Decision Support
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175
AI model for duplcate or dubious licence accountsLicencing systems hold 10 times the amount accounts compared to licences issued. Many duplicate and dubious accounts across the millions of accounts. An AI model to discover duplicate/dubious accounts to highlight them for human review and action.
Idea Programs Sector Automation and Decision Support
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173
AI model for the traceability of harvested fishAn AI model that analysis incoming data requirements ( log books, fish slips, Other traceability documents required by existing and potentially new regulations connected to public reporting apps )
Idea Programs Sector Automation and Decision Support
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211
Analyse des sentimentsC’est un modèle pour traiter automatiquement des textes et documents audios pour classifier les sentiments qui en ressortent sur le sujet. Un premier test sera fait sur le sujet des nouveaux permis de pêche exploratoire du homard.
Pilot Strategic Policy Automation and Decision Support
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248
Analyse des tracés AIS en merAnalyse des tracés AIS en utilisant l'IA: un IA a été créé pour analyser les tracés de bateau et déterminer si des activités de pêche ont lieu. Un pipeline pour les données AIS est en cours de création pour acheminer les données à l'AI. Les coordonnées des ZPM et zones de coraux éponges ont été fournies et si des activités dans ces zones sont détectées, l'info sera fournie à l'équipe de surveillance aérienne et maritime pour suivi
Pilot Conservation and Protection Automation and Decision Support
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176
Analysis of rolesAnalysis of roles: Ad hoc analysis of roles within C&P, comparing 4 different roles and their responsibilities.
Idea Strategic Policy Automation and Decision Support
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127
Automated assessment of Crowd Source BathymetryThe Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of large volumes of crowd source data. AI routines will allow for automated QC, and drafting of Navigation Warnings.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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222
Automated assessment of Crowd Source BathymetryThe Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of large volumes of crowd source data. AI routines will allow for automated QC, and drafting of Navigation Warnings.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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194
Automated ELOG reportingAutomatically generate daily insights and reports on use of ELOGs Solution being developed to generate real-time reporting of ELOG use and implementation.
Pilot Indigenous Affairs, Aquaculture and Governance Automation and Decision Support
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24
Automated Identification of Vessel Fishing ActivityPiloting use of vessel AIS data with AI to predict probable fishing activity and provide near real time alerts to officers, aiming to boost compliance coverage and response. Action plan for this initiative: 1. Governance: Supervised under compliance analytics team, reporting to C & P management. 2. Guardrails: Apply strict controls (no personal data), validate accuracy in live pilots, monitoring for unintended use.
Pilot Programs Sector Automation and Decision Support
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221
Automated Paper Chart SolutionCHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sources. AI routines will improve speed and accuracy of solutions (machine learning) as software is refined to ensure product specifications are respected (as they are used for official navigation).
Pilot Ecosystems and Oceans Science Automation and Decision Support
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125
Automated Paper Chart SolutionCHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sources. AI routines will improve speed and accuracy of solutions (machine learning) as software is refined to ensure product specifications are respected (as they are used for official navigation).
Pilot Ecosystems and Oceans Science Automation and Decision Support
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193
Autonomous Task TrackerAutonomously complete tasks for fishery officer with multi-agent AI. Solution being developed in region to assist C&P autonomous completion of administrative tasks.
Pilot Indigenous Affairs, Aquaculture and Governance Automation and Decision Support
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116
BinderBot: A Smart Planning BinderEmploys AI-driven extraction to identify and compile the most relevant data from technical documents for the planning binder. Streamlines the planning binder process by automatically assembling targeted, information ready for executive review. Saves valuable administrative time and ensures that binder materials are both comprehensive and user-friendly.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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120
Characterizing areas of convergence in the Saint John HarbourThis project is using a technique called self-organizing maps, which is an unsupervised machine learning algorithm, to identify patterns in areas of convergence near the Saint John Harbour. The preliminary analysis suggests that these patterns are related to different environmental conditions such as river discharge and tidal phase. The work has been conducted in collaboration with scientists from the Maritimes Region and is currently on hold.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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128
CICADA (cumulative effects spatial data tool) Phase 2: determining stressor effects and interactions to inform decision-makingGeospatial and machine learning techniques will be applied to determine the overall effect, stress(or) interactions, and relative influences of different stresses(ors) on fish metrics such as species occupancy, population status or community status.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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140
Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental marginWe introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent environmental conditions (temperature, oxygen, acidity), and define the extremes based on the historical statistics of variability of each of these fields.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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59
Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental marginWe introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent environmental conditions (temperature, oxygen, acidity), and define the extremes based on the historical statistics of variability of each of these fields. unsupervised clustering with k-means
Pilot Ecosystems and Oceans Science Automation and Decision Support
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146
Comprehensive marine substrate classification applied to Canada’s Pacific shelfThis completed project built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives and oceanographic predictors using Random Forests.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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65
Comprehensive marine substrate classification applied to Canada’s Pacific shelfWe built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives and oceanographic predictors using Random Forests. Random Forests
Pilot Ecosystems and Oceans Science Automation and Decision Support
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61
CTD data QC using MLWorking with CDOS office to streamline our CTD QC using ML cnn and others
Pilot Ecosystems and Oceans Science Automation and Decision Support
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41
Cyber Security OperationCyber Security Operation Centre has deployed AI/ML in MS Defender (Endpoint Detection and Response (EDR) system), MS Sentinel (Security Incident and Event Management (SIEM) system), Data Lost Prevention (DLP), and Exchange Online Protection (EOP) for real-time threat detection.
Production Chief Digital Officer Automation and Decision Support
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83
Daily UseMapping, The AI Assist function in FME has been used to support code development for data processing while integrating and manipulating data in workbenches.
Pilot Programs Sector Automation and Decision Support
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152
Data Validation ToolUse large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose corrections and normalize data into a standardized format.
Pilot Ecosystems and Oceans Science Automation and Decision Support