Grants and Contributions

Intellectual Property - Strategy

This project aims to enhance the firm’s ability to leverage AI/ML algorithms to deliver personalized, data-driven training plans.

This project explores a number of technology tools and architectural approaches that use AI to autonomously combine images and text for the purposes of personalizing the online buying experience of custom printed products. The objective of the project is to find the most successful technology approach for this use case, thereby de-risking the adoption of AI in the business and laying the foundations for a more substantive project.

This project will investigate and define customer requirements for an enabling electro-optics system in the application area of quantum technology.

The project will support pilot testing of AI strategies, determine target architecture, and establish quantitative technical objectives for implementing an AI solution. To achieve this goal, FPrimeC will expand its current platform to include additional non-destructive testing (NDT) concrete testing variables analyzed by a deep learning AI model. This expansion will improve the condition assessment of existing structures and align with FPrimeC’s mission to preserve existing structures in support of sustainability.

The Modernizing Payments for Rural Canadian Entrepreneurs project aims to significantly enhance the Direct Yield Market (DYM) platform, which connects rural entrepreneurs and brokers with agricultural manufacturers. DYM provides direct access to crop protection products at competitive prices, bypassing traditional, costly intermediaries. In addition, developing an innovative business model, "brokers-as-merchants", allowing rural farmers to resell to their local community within regulations. In addition,

However, a critical gap in the current system is the lack of efficient, affordable payment processing for infrequent but high-value transactions, which are common in this sector. Through this project, we will integrate a scalable and automated payment system that enables seamless ACH transactions for all users, including brokers, vendors, and local retailers.

Design a novel 3D camera system with co-located illumination and sensors using structured light for accurate long-distance measurement, enhanced versatility, and effectiveness.

The Project will support pilot testing of AI strategies, determine target architecture and quantitative technical objectives for implementation of an AI solution.

The NRC in collaboration with the Recipient, a Vancouver-based company specializing in
process automation, will develop an automated sampling technology for monitoring
hydrometallurgical processes in real time by building on the Recipient’s DirectInject system
(developed for pharmaceutical applications) to monitor hydrometallurgical processes and
enable online process analysis for the synthesis and recycling of battery raw materials. After
prototype development, duplicate systems will be deployed at NRC sites in Mississauga and
Ottawa for testing, demonstration and to analyze key processes in metal extraction and
recycling including crystallization, leaching, and ion exchange. Successful completion will
deliver a first-of-its-kind automated sampling system for real-time process monitoring,
accelerating R&D efforts and reducing operational costs.

Automated Ground Truth Generation uses AI tools and machine learning algorithms to produce ground truth data for training machine learning models. This process uses machine-based heuristics and algorithmic computations to significantly reduce the need for human expertise and manual effort. The aim of this project is to create 3D annotations, such as bounding boxes, occupancy grids, and projected segmentation from a video or image sequences. While many existing tools offer AI-assisted annotation, they have limited support for generating ground truth data for more complex areas like 3D as it requires advanced technical skills and the fusion of data from multiple sources.