Summary of proposals for public release:

The Canadian railway system is currently beset by a train track "fog of war" due to a lack of available information on the location of other companies’ railcars. Without such intel, it is difficult for companies to determine which sidetracks (called sidings) are vacant and available to use for parking, and it also hinders the process of renting or purchasing railcars from each other. To solve this problem, DICE and MGH Railcar Services Limited collaborates on the research and development of a system that will use sensors, Computer Vision technology, and a Convolutional Neural Network to autonomously gather railcar data.

The team will design machine learning algorithms using a CNN to extract and process information from digital images or video in order to determine the identity of a railcar. The system will include hardware health monitoring data analysis and user interface. Finally, this project looks to investigate the creation of a Distributed Ledger Technology framework specifically for railcar data use. The railway industry will benefit since locating railcars and available storage areas will become more coordinated and efficient.

Partner organization

MGH Railcar Services Limited (Engage)

Funding sources

NSERC logo

MGH Railcar Services Limited (Engage)
DICE and Krate Distributed Information Systems are developing the Krate Cloud, a decentralized storage and computer network powered by user devices that strives to solve the current epidemic of data breaches (DBs). Currently, data is protected but unusable while encrypted, so it must be temporarily decrypted to use. The Krate Cloud will solve this vulnerability with a system able to compute encrypted data by combining blockchain and cloud technology with lattice-based encryption—the first cloud with cryptographic privacy. This project will benefit Krate by manifesting its theoretical work and establishing the base network necessary for later project phases, while DICE will benefit from knowledge exchange with Krate. Also, it will transform data management and cybersecurity by returning to users full control of their data, and by developing Fully Homomorphic Encryption (FHE), a technique believed to be quantum-proof. 

Partner organization

Krate Distributed Information Systems (Engage)

Funding sources

NSERC logo

Krate Distributed Information Systems (Engage)
In partnership with Xesto, DICE is developing a system for the online clothing retail industry that will interface through a mobile app/micro-app, using 3D scans obtained from software originally developed for facial recognition. The system infrastructure will collect scan data and other data to support the user online purchase of clothing and apparel from different brands that fits properly, thus reducing the need for returning purchases. In addition, support for custom interfacing with brand websites for analysis of fitting data requirements, in partnership with member brands, will produce a more accurate system for size determination based on the product chosen for purchase. This sets the foundation for a reduction in return of missized purchases which are often disposed of, as well as potential custom product creation and purchase from brands that support customization. The application will benefit anyone who has special needs for such items as shoes, clothing or jewellery as well as those limited to online purchasing due to personal circumstances.

Partner organization

Xesto (Engage)

Funding sources

NSERC logo

Xesto (Engage)