Registre des initiatives en IA

198 initiative(s) courante(s)

• 224

  Remote Observation of Watercraft on Roads

  The Aquatic Invasive Species Program is proposing to launch a pilot initiative aimed at addressing a critical knowledge gap in our understanding the spread of aquatic invasive species. Invasive species can attach to boats, trailers, and related equipment—a process commonly referred to as the "stowaway pathway"—which enables their unintentional spread across ecosystems when watercraft are transported between water bodies. The AIS Program is seeking to understand watercraft movement into Canada via international land border crossings. Currently, the extent of this "stowaway" pathway remains largely unquantified. To address this, the pilot will deploy remote camera systems at select border entry points to capture imagery of incoming vehicles. Leveraging machine learning, the system will automatically identify and flag images containing watercraft. This data-driven approach will provide actionable insights to inform strategic decisions on the timing and placement of watercraft inspection and decontamination resources. This initiative may represent a significant step toward enhancing our ability to proactively manage aquatic invasive species risks at key entry points.

  Pilote Perception et compréhension

• 225

  Innovation en matière de données – Initiative relative à la stratégie sur le saumon du Pacifique

  Discover innovative data and artificial intelligence (A.I) projects addressing complex salmon data challenges made possible through strategic investments from the Pacific Salmon Strategy Initiative (PSSI). PSSI initiatives harness the power of advanced data and A.I. technologies like machine learning, computer vision, and natural language processing to revolutionize how to support salmon conservation and rebuilding efforts in the modern data and digital era. By integrating advanced data and A.I. technologies with program activities such as habitat restoration, ecosystem planning, sustainable fishery management practices, and collaborative efforts in Science, the PSSI leverages modern tools to enhance planning and data-driven decision-making. Together, these data and A.I. efforts create high quality and more accessible data and enable better insights and actions to protect and restore Pacific salmon and its ecosystems.

  Idéation Infrastructure et habilitation

• 226

  DFO AI - Pipeline

  DFO Pipeline Analyzer is a private Azure DevOps extension designed to assist development teams in diagnosing and resolving pipeline failures using AI. When a pipeline run fails, this task automatically triggers, extracts the provided error details, and queries a secure AI API to generate a human-readable explanation of the failure along with actionable troubleshooting steps. It will assist developers to make appropriate steps in right direction as they are getting suggestion with-in pipeline logs. Suggestion also provide corrected version of pipeline Key features: Runs only on pipeline failure (condition: failed()) Fully agent-agnostic: Works on self-hosted and Azure-hosted agents, across Windows, Linux, and macOS Provides clear error analysis and resolution guidance directly in pipeline logs Keeps your data secure by using your own OpenAI or other AI API key Fully private and scoped to your Azure DevOps organization We have working prototype of DFO-AI pipeline Analyzer by communicating with OpenAI securely. In next steps we are also exploring to integrate with our self-hosted AI Models (open-source via Ollama), currently in discussion

  Pilote Dirigeant principal du numérique Infrastructure et habilitation

• 227

  Github Copilot

  GitHub Copilot is being piloted at DFO aimed at enhancing developer productivity and exploring the operational value of AI-assisted coding. Stats: (90-day period) - 27,584 lines of code were accepted - 17,801 prompts were accepted - Potential savings of $144K ($50/hour developer) based on 40 developers

  Pilote Dirigeant principal du numérique Infrastructure et habilitation

• 228

  SILScanner

  Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Inspection Logs (SILs). The PoC was originally developed on SSC's cloud infrastructure. It is now being deployed in DFO PB cloud infrastructure. BLADES initiative and IT security teams are involved.

  Pilote Dirigeant principal du numérique Perception et compréhension

• 229

  DFO PB LLM Service

  Provide an approved DFO internal LLM as a service in a PBMM environment. After our team performed a year-long pilot project providing an unclassified internal GenAI models for 14 teams to develop their custom chatbots, we have collected feedback and identified gaps in the availability of GenAI at DFO. One of the biggest gaps was the need for a secure model to be used with private or classified data. Our cloud platform is certified up to PBMM, so we are working to identify, deploy and approve an internal large language model (LLM), as well as make it available to DFO users through API. IT security team is involved in helping us secure and certify the model for use at DFO.

  Pilote Dirigeant principal du numérique IA cognitive et générative

• 230

  Mise en œuvre de la plateforme Copilot Studio

  With the growing interest from CDOS and the rest of the department on custom AI Chat Bots and Citizen Development, there is an opportunity to increase IT enablement through the use of low code solutions. Since the department has already invested indirectly in the Power Platform, it makes sense to extend that investment into the proper implementation of Microsoft Copilot Studio which is another tool from the Power Platform rapid development platform.

  Idéation Dirigeant principal du numérique Infrastructure et habilitation

• 231

  Smart Assyst

  Assyst is point of entry to all CDOS service requests and it covers many of the ITIL and ITSM practices which is the foundation of any IT organisation - and it has the potential to support most if not all of the ITIL and ITSM practices. The most recent versions of Assyst now have deeply integrated AI functionalities that are embedded in all parts and stages of the IT support process. It includes: A natively integrated Chat Bot for technicians and clients, AI ticket assignment, integration to MS Teams, recommended solutions, automated FAQ generation, natural language system search, risk prediction, conversational coding for Assyst developers, smart ticket assignment and escalation, summarization of knowledge articles, and more Activating and configuring those AI functionalities would require an investment in the Assyst system in order to make it AI ready. There is currently a lot of waste in the various CDOS ITIL practices due to a lack of investment in our ITSM tools. Modernizing Assyst to make it AI ready and turning on many of the newer AI features would joinlty contribute to reduce much of the waste incurred during the delivery of our CDOS services to the organization. It would also be a strong showcase both for CDOS and our clients of the power of AI integrated to a complete service process instead of the common and simple use case of AI conversational agents that may only produce limited and siloed value.

  Idéation Dirigeant principal du numérique Interaction et engagement

• 240

  The Current

  Don't let your harvested data get stuck in still water. Navigate new data streams with AI automation, augmentation and information enablement. The Current is a cloud-hosted platform that enables users anywhere in the department to ingest large volumes of structured and unstructured documents, extract data using optical character recognition and large language models, validate and review results through human-in-the-loop workflows, and relate extracted information using shared concepts and standards. The architecture emphasizes asynchronous processing, modular extraction services, strong traceability, and governance-ready design. The platform supports configurable extraction tasks, versioned models and definitions, auditable review processes, and future discovery of related research outputs and datasets across heterogeneous sources. As the initial use-case, the Text Intelligence and Data Extraction (TIDE) Service has been developed for the Salmon Habitat Restoration (SHARE) System. TIDE is a baseline iteration of The Current that fulfills the minimum viable product requirements of SHARE. TIDE focuses on digitizing, extracting, and modeling data from large unstructured text documents. TIDE establishes the baseline architecture and demonstrates a scalable workflow in Production.

  Développement Gestion des pêches Perception et compréhension

• 245

  Solution de reconnaissance d’objets, de classification, d’étiquetage, d’organisation et de compréhension des modèles (OCTOPUS)

  This initiative leverages AI technologies to build an Object, Classification, Tagging, Organization, and Pattern Understanding Solution (OCTOPUS) to enhance the analysis of video, image, and audio data, improve monitoring capabilities and support decision-making processes at DFO. The MVP will initially focus on video processing capabilities, with planned expansion to image and audio analysis in FY 2026–27. In addition, the initiative will deliver integrated data annotation and model training tools to support continuous improvement and reuse of AI models.

  Développement Dirigeant principal du numérique Perception et compréhension

• 246

  GeoAI

  Overview: Potential GeoAI‑Impacted Programs and Processes GeoAI (the integration of geospatial data, AI, and machine learning) is being explored to enhance decision‑making, efficiency, and service delivery by automating spatial analysis, identifying patterns at scale, and enabling predictive insights. 1. Program and Service Delivery GeoAI can support more targeted, timely, and evidence‑based services by: Identifying spatial patterns in environmental, socio‑economic, or ecological data Prioritizing areas for intervention, monitoring, or investment Improving accessibility and equity of services through location‑based insights Examples Risk‑based prioritization of inspections, monitoring sites, or enforcement activities Predictive habitat or species distribution mapping to support conservation or fisheries management Enhanced situational awareness for emergency response or environmental incidents 2. Operational Efficiency GeoAI enables automation and scalability in routine or data‑intensive operations, reducing manual effort and turnaround times. Examples Automated feature extraction from satellite imagery, aerial photos, or LiDAR (e.g., shoreline change, infrastructure, habitat types) Near‑real‑time monitoring of environmental conditions or operational assets Change detection to flag anomalies or emerging risks Operational Benefits Reduced reliance on manual digitization and visual interpretation Faster updates to spatial products and dashboards More consistent and repeatable analytical outputs 3. Business Processes and Decision Support GeoAI can modernize internal business processes by embedding spatial intelligence into planning, reporting, and governance workflows. Examples Predictive analytics to support long‑term planning and scenario analysis Decision‑support tools that integrate geospatial, operational, and administrative data AI‑assisted data quality assessment and metadata generation Process Impacts Improved transparency and defensibility of decisions Better integration of spatial data across programs and systems Enhanced performance measurement and outcome tracking 4. Cross‑Cutting Opportunities Across all domains, GeoAI supports: Data integration: Linking spatial, temporal, and non‑spatial datasets Scalability: Applying consistent analysis across large geographic areas Innovation: Enabling new analytical questions that were previously impractical

  Idéation Dirigeant principal du numérique Automatisation et aide à la décision

• 247

  NECTR – Solution Power Apps – Intégration d’IA Copilot

  We would like to integrate copilot into power apps to be able to help users find and identify data in the database. This will save time for users looking to identify and extract data from the system. We currently have almost 500 users, so enabling AI for this would save a lot of time for these employees.

  Développement Politiques stratégiques Interaction et engagement

• 248

  Analyse des tracés AIS en mer

  Analyse 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 

  Pilote Conservation et protection Automatisation et aide à la décision

• 249

  Plateforme d'IA

  Build a secure, scalable AI platform that extends the Enterprise Data Hub (EDH) and enables DFO teams to develop, deploy and govern AI solutions that will accelerate insights, support scientific discovery and uphold the highest standards of data quality, security, and ethical use.

  Développement Dirigeant principal du numérique Infrastructure et habilitation

• 250

  Agent Conversationnel du centre de données du MPO

  • Faster access to Data Centre information and processes • Reduced dependency on SMEs and email-based support • Improved staff onboarding and operational efficiency • Supports GoC digital-first and AI-enablement direction

  Développement Politiques stratégiques Interaction et engagement

• 252

  Centre d'IA du MPO

  The DFO AI Hub is a centralized digital platform that demonstrates the application of artificial intelligence technologies to fisheries and oceans research, management, and operations. The platform serves as an educational tool that demonstrates how AI can help addresses business needs for faster, more accurate data analysis, improved decision support, and increased operational efficiency across research, monitoring, and management functions. It enables exploratory use of machine learning, computer vision, and natural language processing to process diverse data sources (e.g., imagery, sensor data, scientific reports), automate routine analytical tasks, and generate actionable insights for policy, compliance, and conservation programs.

  Développement Politiques stratégiques Interaction et engagement

• 253

  Tri des plaintes

  triage of email notifications to auto-distribute to an appropriate email inbox, based on the location of the information received

  Idéation Conservation et protection

• 254

  Amélioration de la qualité des données sur les prises et l'effort de pêche

  The creation of a tool or system to use administrative data records to produce a clean and complete database of trip level catch and effort data.

  Idéation Politiques stratégiques

• 255

  L'IA au service du design

  We’re exploring the use of a SaaS design tool with built-in AI, such as Claude Design, to support UX and design work using unclassified information. The goal is to help with things like early ideation, drafting content, prototyping, and general design workflows to improve speed and consistency. We’re also trying to understand the leanest and most efficient way to go through AI governance for this type of tool, while still meeting privacy, security, and policy requirements.

  Idéation Dirigeant principal du numérique

• 256

  Conception d’expérience utilisateur et flux de travail de création de contenu optimisés par l’IA

  AI-enabled capabilities to help UX and content designers deliver digital work faster and more consistently. This includes supporting early ideas, rapid iteration, drafting and revising content, creating and comparing design options (task flows, wireframes, mockups, interactions, prototypes), and producing documentation needed for handoffs and approvals while still meeting GC standards. We also want employees to build modern, transferable skills.

  Développement Dirigeant principal du numérique

• 257

  IA Figma

  The initiative explores the use of Figma's AI capabilities to support user experience (UX) design activities across DFO. Figma AI features may assist in generating interface designs, creating wireframes, producing placeholder content, organizing design assets, accelerating prototyping activities, and improving collaboration among design teams. The objective is to improve productivity and reduce manual effort while maintaining human oversight of all design decisions and outputs.

  Idéation Dirigeant principal du numérique

• 258

  Mise en place d’un processus national normalisé de traitement des données de biotélémétrie

  Development of a national biotelemetry platform that standardizes the processing of acoustic animal tracking data. Automated workflows that apply Random Forest and neural network methods to identify movement patterns, mortality events, and other biologically significant behaviours will standardize quality control, improve data interoperability, and provide self-service analytical tools for scientists and managers across multiple departments, supporting faster evidence-based decision making.

  Développement Sciences des écosystèmes et des océans

• 259

  Système de gestion PPB

  Gestion budgétaire, factures, opérations, bathymétries.

  Idéation Ports pour petits bateaux