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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198 current initiative(s)
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144
Factoid Finder ToolThis completed project used the Factoid Finder extracts text from machine-readable PDFs to create searchable content libraries. Small Language Models are used to implement semantic search techniques, allowing users to search the library for relevant passages within the PDFs.
Pilot Ecosystems and Oceans Science Cognitive and Generative AI
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137
Method Recommendation EngineA large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work
Pilot Ecosystems and Oceans Science Automation and Decision Support
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135
PII & Sensitivity ScoresDetermines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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134
LLM Document ChatbotLarge language model that can help users ask questions to document sets and get answers, summarize key information, and find data with citations and sourcing.
Development Ecosystems and Oceans Science Interaction and Engagement
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133
LLM Document Extraction - Prompt Engineering to Retrieve Relevant InformationUsing LLM to extract key information from documents with multiple templates using prompt engineering approaches. These results are reviewed by SMEs to ensure accuracy and relevancy.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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132
Salmon Scale AgingA model using computer vision to look at images of salmon scale and predict the age of salmon and also explain how it arrived at its prediction.
Pilot Ecosystems and Oceans Science Perception and Understanding
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130
Salmon Data DigitizationDigitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, and useable for analysis.
Pilot Ecosystems and Oceans Science Perception and Understanding
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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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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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126
Automated assessment of satellite imageryAI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards and ii) Change detection – i.e. shorelines or riverbank changes.
Pilot Ecosystems and Oceans Science Perception and Understanding
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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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124
Development of an underwater videography and AI system for studying fish passage effectivenessDesigned to train existing DFO tools with information on fish passage effectiveness and develop an SOP for training videography-based AI models in support of fish passage projects.
Pilot Ecosystems and Oceans Science Perception and Understanding
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123
Fish-Habitat AssociationsExtraction of relevant habitat association info and strengths based on vetted literature input to AI for synthesis. Goal to improve equivalency models used in regulatory decisions. Possible partnership with McMaster University.
Pilot Ecosystems and Oceans Science Cognitive and Generative AI
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122
Development and testing of artificial intelligence and machine learning to analyze underwater photo and video data to assess marine impacts and resourcesThis completed project (2020/21) aimed to utilize machine learning and imaging technology in fisheries science. The proponent planned to use Video and Image Analytics for Marine Environments (VIAME), an open-source system developed by NOAA, for two specific purposes: 1. Measure the movement of Atlantic cod across boundaries at the Gilbert Bay Marine Protected Area in Newfoundland and Labrador. 2. Assess the impact of seismic surveying on Atlantic cod as part of a project funded by the Environmental Studies Research Fund (ESRF). The automatic detection and count of fish near MPA boundaries was expected to reduce use of personnel time and effort.
Pilot Ecosystems and Oceans Science Perception and Understanding
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121
Develop a deep-learning model to age capelin otoliths: application for stock assessmentInvestigate the utility of applying a deep-learning model developed by the DFO Gulf Region for aging fish otoliths; specifically, to determine the age of capelin in the 2J3KL stock in Newfoundland for use in stock assessments. Otolith aging is currently done visually using a microscope, this proposed method would automate that process to save time and resources, while reducing human error and bias
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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119
Computer vision to automate fish data extraction from videoOur purpose has been to build a tool to broadly apply computer vision methods in marine research. Our work has generated several publications illustrating how we built, tested/validated, and applied computer vision methodology to collect / extract / and analyze data pertaining to marine fish in the Newfoundland and Labrador region, from video. For example, we have used it to examine the impact of seismic surveying on commercial fish in the Newfoundland and Labrador offshore. Our continuing purpose is now broadly sharing our system with commercial harvesters (fishermen), non-profit organization (AHOI), government researchers (aquaculture, MPAs, AIS), and academics (computing scientists), to collect and rapidly analyzing video data for a wide range of applications.
Pilot Ecosystems and Oceans Science Perception and Understanding
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118
Use of artificial intelligence models to facilitate seafloor video annotations in conservation areas.The purpose of this initiative is to utilize AI to facilitate seafloor video annotations collected as part of the MCT and Benthic Ecology programs in the NL Region. A large number of vidEcosystems and Oceans Science is collected annually, and manual video annotation (e.g., locating and counting observations) is extremely time-consuming. A published “object detection model” (FathomNet Megalodon Detector, YOLOv8x) trained using marine taxa by MBARI is currently being used to identify objects in our seafloor images. The model does not identify the objects (e.g., to species), but it largely accelerates the process given that locating objects is the most time-consuming part of the work.
Pilot Ecosystems and Oceans Science Perception and Understanding
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117
PolyDocs: Format and Translate for CSASA modular, bilingually-optimized (EN/FR) application that automates the formatting, quality assurance, and standardization of complex Word documents to meet Government of Canada publishing requirements. The tool orchestrates a highly configurable, low-code assembly line that handles deep document cleanup (resolving fragmented text, localizing punctuation/number conventions, and rebuilding tables of contents), applies localized terminology glossaries, and reduces file sizes for accessibility.
Production Ecosystems and Oceans Science 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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115
PublicLens: Science in Plain LanguageLeverages AI to transform highly technical scientific and documents into accessible, plain-language summaries for the Canadian public. Fosters transparency and builds public trust by making scientific and government information easily understandable. Promotes civic engagement by breaking down barriers between experts and everyday Canadians.
Pilot Ecosystems and Oceans Science Cognitive and Generative AI
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114
InsightBridge: Executive CSAS SummariesUses AI to convert complex, technical CSAS reports into concise, plain-language summaries tailored for executive decision-makers. Enhances leadership understanding and accelerates informed decision-making by providing easily digestible insights. Ensures executives can quickly grasp critical information without sifting through dense documentation.
Pilot Ecosystems and Oceans Science Cognitive and Generative AI
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113
Improving forecasting for high-priority portsResearch into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI modelling methods.
Pilot Ecosystems and Oceans Science Automation and Decision Support
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112
ECCC exchanges on use of AI for ocean modellingExchanges with ECCC on implementation of machine learning methods for operational ocean forecasting, including potential uses for DFO models.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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111
Digital Twins of the Ocean Task TeamNational exchanges on topics relating to ocean modelling for development of Digital Twins of the Ocean, including use of AI for modelling and products.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement