The Artificial Intelligence (AI) for Logistics program was established as part of the National Research Council of Canada's (NRC) commitment to support the goals of Scale AI – Canada's AI Global Innovation Cluster.
The program provides R&D expertise focused on next-generation technology issues. It aims to boost industry performance by leveraging AI technologies to improve value chains, with a specific focus on building resilient and sustainable supply chains.
Areas of focus
Theme 1: Transportation and warehousing
Projects:
- AI for road freight in the Canadian Prairies and North
- Augmented-reality system with AI modules for efficient remote guidance of drones
- Optimization of regional logistics networks for parcel delivery services
- Smart route recommendation system for transporting goods in extreme weather
- Multi-sensor odometry with deep-learning based map building and mode adaptation for vertical take-off and landing (VTOL) vehicles
- Crowdsourcing framework for last-mile delivery by leveraging AI and blockchain
- Continuous action, time and space (CATS) reinforcement learning
- Biologically inspired online novelty detection
- Adaptable AI tools for safe and reliable remote operation of aerial manipulators interacting with their environment
- Medium-range sea-ice presence forecasting using AI approach
- Development of AI-based digital twin for railway operation
- AI-enabled navigation of vertical takeoff and landing (VTOL) drones beyond visual line-of-sight
- AI-enabled navigation of uncrewed aircraft systems (UAS) in remote northern areas
- Development of an AI driver intentionality and action predictor tool to improve safety in urban last-mile delivery operation
- Winter road logistics: Constitution of a multimodal northern transportation database
- Formal verification and optimization of adaptive training systems for ice management and life boat simulators
- Optimization of regional truck hours for delivery services
- XRT4TEAM: Extended reality for first responder hazardous materials response training
Theme 2: Condition of infrastructure and goods
Projects:
- A data-driven approach to enhance transportation infrastructure resiliency through bridge monitoring
- Towards smart and sustainable pavement structures in Canada
- Enhancing freight transportation using self-monitoring smart roads
- AI for rail infrastructure thermal stress condition assessment
- Health monitoring system for condition-based maintenance applied to rail/transit infrastructure and bogie
- AI-enabled tools to reduce risks to first responders in responding to freight-transportation fire incidents
- Development of self-learning algorithms for monitoring and assessing integrity of goods in Internet of Things-based urban logistics
- Beyond visual line-of-sight (BVLOS) inspection of critical logistics infra- and superstructures using coordinated multiple uncrewed aircraft systems (UAS)
Theme 3: Cybersecurity for logistics
Projects:
- Secure and resilient fog computing framework for intelligent transportation systems
- Security of data provenance and machine learning for the Internet of Things
- Internet of Things device profiling in smart transportation pathways
- GPS jammer risk management
Theme 4: Canadian logistics AI‑powered modelling
The AI for Logistics program, through its R&D themes above, its convenor activities, and its Logistics Data Vault, has expanded technology and linkages, enhancing possibilities for AI to enable larger scale improvements to Canadian logistics through multi-modal, multi-jurisdictional modeling.
Since its approval in the fall of 2019, the AI for Logistics program has provided advances to make the Canadian freight transportation system better, safer and smarter. This includes enabling more efficient, secure and resilient vehicles, infrastructure and systems.
The program has:
- Developed technologies capable of increasing regional ground freight efficiency by at least 10% (if efficiently deployed, these technologies could save Canadian industry several million dollars each year)
- Enabled the training of over 119 students and post-doctoral fellows
- Developed models to support improved freight access to and for remote and northern communities
- Developed technologies to improve monitoring and reduce derailment risk in view of climate change
- Improved tools for the visualization of transportation networks
The program has also delivered a successful Forum and Speaker's Series on data ethics and responsible data, as well as a number of stakeholder engagement and ecosystem development events.
Contact us
Margaret McKay
Program Leader, Artificial Intelligence for Logistics program
Email: NRC.AIforLogistics.Program-Programme.IALogistique.CNRC@nrc-cnrc.gc.ca
Industry sectors
Logistics, transportation, warehousing, shipping, rail, trucking, aerospace, manufacturing, retail, civil infrastructure, information technology.