Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

31620 Completed Projects

2978
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5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
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98
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619
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1192
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Projects by Category

Hybrid recommender system with multi-source data and social knowledge graph integration

Accurately recommending items of interests is essential for users to improve their experience. To acquire better performance, a recommender system can utilize multiple sources of data and the social knowledge graph. This can lead to efficient use of information to improve the recommender system. By exploring the data and extract crucial features to feed to designed models, the recommending engine can increase its performance dramatically. Furthermore, a social knowledge graph contains the description and relation of users, which can act as a knowledge base for inference. By fusion of those techniques, the resulting recommender system can be optimized.

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Faculty Supervisor:

Peter Marbach

Student:

Partner:

AppDirect Canada Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Mineral carbonation for global warming mitigation and concurrent nickel and cobalt extraction from laterites

Both global warming and increasing supply of nickel and cobalt are urgently world-wide issues to be addressed. Mineral carbonation is a promising method to permanently store greenhouse gas CO2 into stable mineral carbonates but energy-intensive requirements and low-value products limit the successful application. Meanwhile, with the increasing demand on global nickel and cobalt supply for electrical vehicles and gradual decrease of nickel sulphides deposit, it becomes more important to extract nickel and cobalt from dominant laterites of nickel resources. However, poor selectivity and hazardous wastes detrimentally affect surrounding environments and communities. In fact, these two global issues can be potentially addressed in an integrated process by utilizing mineral carbonation to concurrently and selectively extract nickel and cobalt from laterites. This project is to develop an innovative and environmentally-friendly process which can selectively extract nickel and cobalt extraction from laterites for industries and also simultaneously sequester CO2 for global warming mitigation.

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Faculty Supervisor:

David Dreisinger

Student:

Partner:

LeadFX

Discipline:

Engineering

Sector:

Mining

University:

The University of British Columbia

Program:

Accelerate

Pathways to a More Inclusive Labor Market in Calgary

An inclusive economy aims to provide all members of society with the opportunity to contribute to and benefit from a community’s economic activities and systems. Calgary Economic Development acknowledges that helping all Calgarians achieve their personal potentials is imperative to leveraging Calgary’s rich diversity to bring innovation and creativity into our industries and businesses. However, we are still facing challenges regarding diversity, equity and inclusion in Calgary labour market. Through this project, we intend to further Calgary Economic Development’s understanding of: a) how inclusive is Calgary’s economy? b) what are some identified causes of varying labor force outcomes in Calgary, and c) what are some tangible next steps to address varying labor force outcomes?

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Faculty Supervisor:

Atsuko Tanaka

Student:

Partner:

Calgary Economic Development Ltd.

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

University of Calgary

Program:

Accelerate

Quantifying the value of community science data for conservation

Community science, the public participation and collaboration in monitoring and research, is rapidly emerging as an effective means to collect vast quantities of data in a cost-efficient manner. This may prove invaluable to conservation efforts, as using crowd-sourced data to inform decisions can allow managers to redirect limited funds towards action rather than monitoring. My research investigates how integrating community science data with professional monitoring can improve our understanding of how birds make use of agricultural land during migration. Money saved by using the freely available community science data can then be redirected to compensate farmers for taking part in conservation initiatives to benefit these species. My work will explore how we can augment our knowledge of dynamic ecosystems while reducing the cost to do so, benefiting both farmers and biodiversity.

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Faculty Supervisor:

Joseph Bennett

Student:

Partner:

University of Queensland

Discipline:

Life Sciences

Sector:

Sustainability & the Environment; Environmental Science and Technology; Agriculture and Food

University:

Carleton University

Program:

Globalink Research Award

Development of a standardized assay for after cooking darkening by which to support cultivar selection for breeding program and timing from storage for optimum processing (continued).

Two types of color changes occur in potato, raw potato darkening and after cooking darkening. We are investigating the factors behind each type of darkening in three potato cultivars (Chieftain, Goldrush, and Yukon Gold). Effect of digging method (hand/mechanical) and storage time (after 3, 5, and 7 mo) were studied to find if the digging method and/or storage has any effect on darkening. In addition we are developing a digital photography system and color intensity measuring software to use in industry as an inexpensive, quick, and more accurate determination of potato discoloration. Digital photography and color measuring software will eventually replace visual scoring of potato discoloration which is currently used in industry.

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Faculty Supervisor:

Danielle Donnelly

Student:

Partner:

Patates Dolbec Inc;Centre de Research Les Buissons;Fonds de Promotion; Association des Emballeurs de Pommesde Terre du Quebec;Federation des Producteurs de Pommes de Terre du Quebec

Discipline:

Earth science

Sector:

Agriculture

University:

McGill University

Program:

Accelerate

AI-Powered Wireless Human Activity Recognition for Safety and Health Improvement

Human’s gait, and activity monitoring play important roles in many applications that can have a positive impact on improving the ability of individuals to be as independent, secure, and healthy as possible. Most existing technologies rely on cameras and wearables, while people are not always compliant and need to be wearing them with a battery charge for them to work. Camera-based sensors, on the other hand, systems are sensitive to high-contrast light and poor visibility conditions and suffer from obstructed line-of sight conditions and privacy concerns. The purpose of this research project is to develop zero e?ort and wireless sensors for independent and autonomous gait monitoring and activity recognition.

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Faculty Supervisor:

Plinio Pelegrini Morita;George Shaker

Student:

Partner:

TandemLaunch Inc

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Advanced Manufacturing; Information and Communications Technology

University:

University of Waterloo

Program:

Accelerate

Automatic Creation of Fertility Maps in Precision Agriculture

One of the important problems in farming is to decide on variable fertilizer rates based on the inputs about varying soil types and some other factors. This is a key component for optimizing productivity and sustainability in precision agriculture. The main objective of this project is to use datasets captured by satellite imaging to develop computer algorithms for:
1. automatic creation of fertility maps to guide soil test points selection,
2. visual analytic tools to help agronomists to make decisions about variable fertilizer rates and yield goals of crops across multiple fields.

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Faculty Supervisor:

Faramarz Samavati

Student:

Partner:

Decisive Farming Corp.

Discipline:

Computer science

Sector:

Agriculture and Food; Information and Communications Technology; Sustainability & the Environment

University:

University of Calgary

Program:

Accelerate

AI-empowered Robust Ad-hoc Underwater Tactical Wireless Networks: Sensing & Threat Classification

This project is part of a longstanding continuous collaboration between Ultra and École de technologie supérieure that seeks to leverage the advancements of artificial intelligence (AI) to design a comprehensive framework for a robust ad-hoc underwater tactical wireless networks (AUTWNs). The network will be featured with privacy preserving mechanism to assist threat classification and self-organizing capabilities. AUTWNs play a significant role in the success of maritime and warfare missions, naval and underwater disaster relief operations, and many more. Ultra is a global leader in AUTWNs; their customers include the Five-Eyes nations and others. As part of its strategic research and development plan, Ultra is planning to upgrade its underwater wireless communication (UWC) systems. The current state-of-the-art AUTWNs require constant human intervention, for network configuration and reconfiguration in case of failure, threat management and classification, etc. The current advancements in AI make such a reliance on humans a huge vulnerability, which motivates this project. Furthermore, the key-concepts and core-technologies developed under this project are not only imperative for tactical and emergency applications, but they are also of significant value for scientific and environmental applications to monitoring underwater environments.

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Faculty Supervisor:

Georges Kaddoum

Student:

Partner:

Ultra Intelligence & Communications

Discipline:

Engineering

Sector:

Information and Communications Technology; Artificial Intelligence; Ocean Tech

University:

École de technologie supérieure

Program:

Accelerate

Oblivious IDS using Homomorphic Encryption

Intrusion Detection System (IDS) is used to protect internal networks of companies and organizations against malicious activities and policy violations. These systems are typically under the full control of the local system administrator. In this project, we propose to use Homomorphic Encryption techniques to design and implement an Intrusion Detection System that can run as a service on the cloud. In this model, the cloud system administrator who runs and operates the IDS does so while being completely oblivious to the underlying policies and matching rules.

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Faculty Supervisor:

Mostafa Taha

Student:

Partner:

Solana Networks

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

Optimizing Pretrained Clinical Embeddings for Automatic COVID-related ICD Coding (Phase II)

We are building a machine-learning algorithm to be able to understand the unstructured clinical notes better and to identify the most appropriate ICD codes for each visit. This algorithm will help healthcare systems standardize and extract insights from these notes to make them more useful for determining how sick patients are, what procedures are performed and how patients are improving over time.

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Faculty Supervisor:

Helen Chen

Student:

Partner:

Semantic Health Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Ubisoft: Détection d’anomalies de performances

L’industrie du jeu vidéo est une source inépuisable de données et notamment de données de performances [8]. L’origine provient de la nécessité pour une expérience de jeu ultime, d’avoir des performances similaires quelle que soit la plateforme utilisée. Cependant, la fragmentation du marché des plateformes de jeu est multiple. Entre les différentes consoles et l’ensemble des configurations possibles pour les ordinateurs personnels, un développeur de jeu doit faire face à une myriade de problèmes de performances. L’idée de ce projet est de faciliter cet aspect du monde des jeux vidéo.
Ubisoft développe des jeux multi-plateformes, et pour chaque plateforme, tente d’optimiser les performances d’affichage (en nombre d’images par seconde). Lors de cette phase de test, une quantité impressionnante de journaux sont générés en vue d’analyser l’impact de chacune des composantes du jeu (comportement, animation, rendu, etc). Dans chacune de ces composantes, c’est parfois plusieurs milliers d’éléments qui sont impliqués et nombre d’entre eux sont réutilisés entre différents jeux ou dans différents contextes d’un même jeu. Par exemple, le comportement d’un lapin pourra être réutilisé en plaine en été ou en montagne en hiver.

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Faculty Supervisor:

Christian Gagné;Audrey Durand

Student:

Partner:

Ubisoft Divertissement

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing

University:

Université Laval

Program:

Accelerate

Customizing CareChanger to remotely detect and effectively predict void events.

The CareChanger product is an incontinence care system to be used for detecting and predicting voiding events of a care-receiver in an assisted care facility while providing care to one or more patients with incontinence issues. The fundamental aim of this project is to assist caregivers in providing more personalized, efficient, and cost-effective care specifically around void events and prevent health issues in patients.

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Faculty Supervisor:

Aaron Gulliver

Student:

Partner:

4M Biotech

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.