Digital health and geospatial analytics

A program in support of Canada's Digital Technology cluster

Canada's Digital Technology Supercluster is a member-driven organization which co-invests in ambitious, collaborative projects that develop products and platforms enabling the digital transformation of key industries including health care and natural resources. The joint investment of the cluster and its members helps Canadian businesses grow and prosper, creating jobs and setting the foundations for scalable economic growth for Canada.

The National Research Council of Canada (NRC) is undertaking a collaborative research program focussed on digital health and geospatial analytics with the aim of supporting the research agenda of this cluster.

Focus areas

1. Artificial intelligence and digital enablement for health

This focus area uses artificial intelligence and digital technologies to improve health care delivery and connect it to real-world, evidence-based clinical research.

Projects:

• A new framework for safeguarding the security and privacy of precision health care data using big data analysis and homomorphic encryption
• A virtual reality intervention to improve workplace functioning in British Columbians with depression: the BWELL-D Cognitive Care Platform
• Secure in-home patient health care framework for body-area network based scheme
• Simulating interaction with IoT-enabled devices through virtual and augmented reality
• Process modelling for digital twins of robot-assisted orthopedic surgery
• Development of transfer learning methods for diagnostic application of lipido/metabolomics

2. Geospatial analytics

This focus area uses digital geospatial technologies to solve compelling challenges in areas such as agriculture, forestry, environmental monitoring, transportation and clean energy.

Projects:

• Smart agri-food supply chain digital twinning
• Exploitation of the earth data store for data-driven mission planning for airborne camera systems
• Learning from big historical geospatial data on environmental impact to shellfish industry for predictive models and monitoring toolkits

In both focus areas, the key to creating meaningful applications is collecting and processing data and transforming it into knowledge through machine learning and advanced analytics. Both areas represent highly distributed data ecosystems in which data discovery, ontology mapping, data use contracting, digital trust, traceability and value-chain management can be performed at scale.