Grants and Contributions

The primary objective of the proposed project is to research and develop a process to upgrade barite (BaSO4) from API to industrial grades (97%+) and, more importantly, to significantly reduce the lead content
found in the final product. This will be achieved by developing a test procedure to upgrade barite via flotation and then remove lead via leaching. Testing will also provide the opportunity to obtain critical design criteria to ultimately engineer the required commercial scale processing facility. The technology and ability to produce an industrial-grade barite product will provide a significantly more robust market for the final product.

Traffic signals are the major components of cities' traffic systems that require continuous maintenance and adjustment for optimal operation using signal performance measures (SPF). Currently, SPF, such as delay and number of stops, can be obtained from expensive and difficult-to-maintain traffic sensors, including cameras, loop detectors, and radars. This project will develop a cost-effective SPF system using connected cars GPS data, aka probe vehicles, using no physical sensors. Connected cars generate massive car data attributes that share the location, speed, engine status, etc. of vehicles to the car manufacturers and other companies, creating many opportunities for developing services for smart cities such as traffic management.

The purpose of this CanExport SMEs agreement is to support small- and medium-sized enterprises (SMEs) for activities related to export market development that are part of an export business case for a specific target market, particularly where activities are targeting departmental priority markets and sectors.

A unique inland shrimp hatchery using artificial seawater and leading edge RAS technology.

The Universal Digital Vessel (UDV) project will combine the technologies and expertise of Genoa, Virtual Marine, Gastops and Modest Tree to create a relevant digital workspace that can be used by marine personnel in vessel design, construction, operation, maintenance and training innovation, without fear of violating IP rights. Modest Tree’s part of the collaborative project will be processing data through its asset pipeline to create data-driven lesson creation using sequence of instructions. Modest tree will provide expertise in the scenario development and connectivity of Gastops values/simulation and Genoa 3D model into a cohesive scenario demonstrating an operational immersive trainer of onboarding fuel on a ship.

This project will deliver the industry’s first, unified filtering mechanism, applicable across disparate Business Intelligence (BI) and Analytics platforms (BI&A). The benefactors of this project will be end users that are required to work with multiple BI&A solutions in order to effectively analyze corporate date. Users will be able to simultaneously analyze data across disparate systems replacing the current way that this type of analysis is performed, which consists of repetitive, error prone, manual interactions.

We shall develop advanced algorithms capable of providing end-to-end, touchless, in-transit, real-time, package-level monitoring of goods as they make their way through the supply chain. The algorithms will allows highly granular monitoring of the goods during transport, storage and transshipping, thereby mitigating todays huge losses and inefficiencies.
The algorithms will run on a multi-tier architecture: embedded in the the field devices that travel with the goods, in the cloud and in the front-end use application.

The proposed project concerns the further development of an innovative Digital Health platform and inventory-management system specifically designed for low-resource environments, with the aim of finalizing a pre-production model to meet increasing client demand.

The project is dedicated to providing high-quality, adaptive, and self-sustained automatic translation services for the legal, financial, and government sectors in Canada with AI technologies.

Development of advanced composite material cutting and automation technology to eliminate part variability and reduce scrap rate in composite material manufacturing