Grants and Contributions

Development of a point-of-care medical device for disease detection.

Falkbuilt intends to implement a lean manufacturing project to reduce manufacturing lead times and improve productivity and efficiencies while incorporating COVID 19 social distancing measures.

Gaia Protein is an insect protein production company that is doing research and development towards producing high quality protein at a price that is competitive with conventional sources. Insect protein has numerous health and environmental advantages. There are many opportunities for optimization in this emerging industry in North America. We will be utilizing rejected industrial heat and agricultural by-products in our production process to improve environmental outcomes and maximize profitability. Our team has successfully accessed rejected industrial energy in a previous bio-tech project. We will apply modern agricultural science and engineering to a traditional production practice that is widely used on a global scale.

The youth industrial designer will support improvement of the design process for large customised rope play structures

Entos has developed Covigenix VAX-001, a DNA Proteo-Lipid Vehicle (PLV) vaccine intended for the prevention of COVID-19 infection by SARS-CoV-2. In this project, Entos will advance the VAX-001 vaccine candidate through Phase 1 clinical trials to establish its safety and immunogenicity in healthy adults.

This project will involve the pursuit of research and development efforts to result in new and innovative solutions for detection of antibody biomarkers associated with disease states in hemostasis and cancer. The underlying technology necessary to adapt immunoassays to common coagulation assay platforms will be developed, resulting in a rapid, automated immunoassay technology, with a first application as a hemostasis biomarker IVD device. In parallel, a competitive ELISA format immunoassay will be developed for the detection of an emerging cancer biomarker, which can in the future be adapted to the rapid immunoassay technology and enable Precision Biologic’s entry into new market segments.

Logistics, which is the process of planning, implementing and controlling the flow and storage of goods and services from the point of origin to the point of consumption, is essential for successful and sustainable economic growth in Canada. However, due to pressure from saturated markets, new customer demands and adverse seasonal weather conditions, the logistics systems in Canada face many new complex challenges. Recently, the rapid technological convergence between
Internet of Things (IoT), Fog/Cloud Computing, and AI has made Logistics 4.0 possible, which has significant potential to improve the quality of logistics in Canada by providing benefits such as real-time big data analytics for optimized routing and reduced storage requirement without information disruption. Nevertheless, Logistics 4.0 still faces many security and privacy challenges, such as veracity of data, robustness of IoT and Fog devices, and privacy-preserving big data AI
processing. The proposed research project aims to address these challenges by contributing to the development of a secure and resilient fog computing framework for Intelligent Transportation Systems (ITS) to address the
threats to ITS, including those to field devices such as IoT devices, sensors, traffic signals, roadside equipment, and those to transportation management centers. Specifically, we will secure data in its whole cycle
within ITS, i.e., secure data collection, data transmission, data storage, and data processing within ITS. Novel techniques, including privacypreserving AI data processing, lightweight authentication for IoT and Fog devices, and efficient malware detection techniques for IoT and Fog devices will be exploited in the framework for ITS.

This project will develop new methods to ensure the security of IoT devices in large corporate networks. Data provenance and machine learning will be the main project tools. Provenance establishes the trustworthiness of the data generated by devices, which can in turn be used for training machine learning models that detect malicious behaviour. A major focus of the research will be to ensure that the new techniques do not introduce additional attack vectors. The project will investigate the vulnerability of ML-based systems to attacks that specifically target ML algorithm, and the project team will apply robust learning techniques where necessary to protect against such attacks. Distributed ledgers will be leveraged to provide tamper resistance to the data provenance information.

IoT device use is increasing, which creates security operational challenges in IoTbased
smart transportation systems, such as knowing what IoT devices are
connected and whether they are functioning normally. IoT devices are entry
points into critical infrastructure, and as such can be exploited to leak sensitive
information. To ensure resilient supply chains, network traffic analytics can
characterize IoT devices, including their typical behavior mode in order to identify
anomalous behavior and alert officials of potential cyber threats.
This project will enable a complete survey of the state of the art of IoT devices
used in the supply chain used in transportation pathways, namely, ports of entry.
This project involves the creation and dissemination of knowledge of vulnerable
devices in the logistics chain. This will include identifying anomalies as well as
developing a visualization tool which can be tailored to other critical
infrastructures.

This contribution supports the development of the Ten-Year Monitoring Report which will detail the current state of the natural, cultural and/or recreational values of the Upper Restigouche River as part of the Canadian Heritage Rivers System.