Grants and Contributions

To leverage AI technology to advance ArmorFoam development in CO2 Enhanced Oil Recovery (EOR) and CO2 storage applications. The objective is to establish a comprehensive, classified database of key parameters influencing ArmorFoam’s stability and performance.

This project will enhance the OneVest trading platform with improved portfolio optimizer, enhanced multi-currency management and separately managed accounts for high-net-worth individuals and institutional clients.

Development and execution of Sales, Marketing, and Business Activities to implement and deliver a wildfire prediction and mitigation solution to at risk communities.

Emission of methane, a greenhouse gas, is a major contributor to climate change. Natural gas and oil pipeline leaks account for about 30% of methane emission. Early detection and mitigation of leaks will reduce emission, benefit the environment, and reduce energy costs. Sensor carrying aircraft are utilized for pipeline monitoring, since they can quickly cover the vast and remote areas over which pipelines are spread. The Project team plan to combine upconversion detection of mid-infrared light with threshold quantum photon number resolving detection. Mid-infrared sensing light is converted into near-infrared light, which can be detected with a thresholded quantum photon number resolving detector. Such detection has been shown to provide a quantum advantage in signal-to-noise ratio when detecting fewphoton laser light in the presence of thermal background (such as solar radiation), due to the difference in the quantum properties of laser and thermal light

The goal of this project is to investigate and define specifications for an AI-driven module that leverages Generative AI to analyze historical bird strike data and generate predictive insights. These insights would help proactively identify conditions that increase the risk of bird strikes occurring potential allowing for earlier intervention and enhanced safety. This phase of the project will focus on initial research, feasibility assessment, and technical specifications to guide the development of a predictive analytics solution aligned with our customers' needs.

The project will assess data quality and data sources to support the development of an AI-driven diagnostic tool for customer support in EV charging. It will also document and characterize key data attributes to enhance AI training and data governance practices.

OKAKI is currently working with several clinical research laboratories to achieve Health Canada and FDA regulatory approval for Gaitly, a computer vision and NLP driven software-as-a-medical-device application. The project requires a graduate with skills related to computer vision, natural language processing, digital signals processing, and machine learning to assist the project manager and research laboratories to develop new and refine existing algorithms for measuring Gait, Balance, and Cognitive assessments. The expected outcomes for this project includes the development and publication of novel computer vision and NLP algorithms used for achieving regulatory approval and technical reports for use in patents and publications.

The Project will support the development of AI-powered pricing software for vacation rental properties, pilot testing data-driven pricing strategies, determining the target architecture, and establishing quantitative technical objectives to maximize revenue and occupancy through advanced data integration and machine learning models.

Membership to IUPsyS allows Canada to participate in international endeavours and promotes the exchange and dissemination of knowledge in the most advanced areas of scientific and industrial research.

Atomic defects in diamonds offer the potential to serve as room-temperature quantum sensors, enabling precise monitoring of temperature, pressure, and electromagnetic fields with unprecedented precision. Diamond-based quantum magnetosensors offer extremely promising applications in orbital magnetosphere mapping, low-altitude mapping for mineral prospecting, and ground-level boarded sensors for defense and environmental applications. Being in their technological infancy, these diamond devices struggle to rival their non-quantum counterparts but do present tremendous potential for improvement. By combining the expertise of SBQuantum, the Université de Sherbrooke, the University of Calgary, and two National Research Council centers, the Project brings these quantum magnetosensors to their full deployment potential and lead the Canadian quantum technology industrial ecosystem to new horizons. The Project is transformative research that has the potential to revolutionize production processes and the Canadian quantum sensing technology landscape by significantly improving the sensitivity, cost, size, power consumption and industrial applications of magnetic quantum sensors. This will be accomplished by producing and commercializing nano integrated quantum magnetometers for high sensitivity, accuracy, and cost efficiency. To realise this, the Project Team will develop a scalable diamond-based quantum sensor fabrication process and demonstrate a robust industrial packaging methods to establish a Canadian assembly line for quantum photonic products. The initiative also targets the advancement of applications for the Canadian mining industry with quantum sensing technology for ore processing and the deployment of drones for advanced exploration surveys. Finally, the industrial partner will distribute those quantum sensing solutions to domestic and international clients