Innovative Projects Realized

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

29670 Completed Projects

2811
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4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

A Wide Bandgap Based Step-up Power Converter With Enhanced Self-Reconfigurability for Medium Voltage Renewable Power Network

Wind and solar photovoltaic energy are the fastest growing sources of electricity in Canada, targeting to reach 10% of Canada’s total generation by 2040. Aligned with Canada’s energy transition, this research aims at developing a novel, highly efficient, compact, and reliable power electronics interfaces for high power renewable energy resources. The use of power electronics converters is an attractive solution to significantly reduce the weight and size of the step-up voltage conversion unit in today’s high power renewable energy systems. However, the existing converters fail to maintain a stable grid voltage efficiently against a wide range of solar irradiation level or wind speed. To address this issue, a high frequency converter with four modes of operations is proposed that employs newly available high voltage wide bandgap (WBG) transistors. The structure of the proposed converter can be changed according to the atmospheric conditions by using a single switch. Hence, high efficiency for a wide range of solar irradiation level or wind speed can be obtained.

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Faculty Supervisor:

John Lam

Student:

Partner:

I-INC Foundation for Business Development;iBoost Zone

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Optical device for accurate and real-time assessment of liver fat content in human subjects

A novel technology that will allow transplant surgeons to obtain accurate measurements of liver fat content during donor surgeries has been developed. These results will be immediate and will guide the transplant surgeon in deciding whether the liver is acceptable for transplantation. This will lead to fewer discarded livers, reduced waitlists for liver transplantation and improved quality of life for many individuals with end-stage liver disease. Our alpha prototype has been proved to detect fat at concentrations greater than 5%. Further research aims at reliable detection of the more clinically relevant low concentrations of fat (<5%). Our intention is to license to a local NS company, led by intern Hao Guo.

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Faculty Supervisor:

Kevin Hewitt

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Spinning Multi-Beam LiDAR (VLP-16) new mapping scheme and the effect on the generated 3D point cloud : Point density and Thin features extraction in a Mobile mode of operation

Maps are vital in our life. Three-dimensional (3D) maps are essential in traditional and new applications, such as smart cities, autonomous vehicles and augmented reality. The number of end-users who require 3D maps has expanded exponentially in recent years and is anticipated to expand even more in the future. LiDAR scanners are the main sensors in 3D mapping systems. The commercially available 3D LiDAR-based mapping systems tend to be bulky, expensive and thus out of the reach of many end-users. Recently a relatively low-cost LiDAR scanner has been introduced for autonomous vehicles. This LiDAR scanner has been integrated to develop a unique LiDAR-based 3D mapping system. The developed 3D mapping system has a substantial cost reduction compared to the commercially available. This project proposes and validate a novel setup for the system in the data collection process maximising the benefits of its usage despite using relatively low-cost sensors.

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Faculty Supervisor:

Ahmed Shaker Abdelrahman

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Accelerate

Mobile Health Application Validity and Efficacy Study

The first MITACS internship for this project focused on design of the “Be Kalm” Anxiety App. The second internship will focus on the programming, implementation, and evaluation of the resulting design. The App will combine several interactive methods of diffusing anxiety with the use of images, music and heart rate monitoring. The HeartBeats music player will contain a selection of predetermined music that will speed up or slow down in tempo along with the user’s heart rate. The breathing feature will display an animation of a balloon, filling up and deflating rhythmically, which will help set the timing of the users breathing. Images representing different types of negative thoughts will act as buttons. When clicked, these images will log the thought, helping the user keep track when and how often these thoughts occur. Methods of analyzing, filtering and illustrating feedback from the various features of the application will be tested…………….

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Faculty Supervisor:

Bruce Gooch

Student:

Partner:

Westcoast Child Development Group Inc

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

University of Victoria

Program:

Accelerate

Multiplexed confocal FLIM microscope for Drug Discovery

Fluorescence lifetime imaging (FLIM) is an emerging technique that is used drug discovery by universities and pharmaceutical companies. The research team developed a multiplexing technique that can improve the imaging speed by 1000 times. However, matching 1000 focal points to 1000 detectors individually is very difficult. In this project, the team plans to develop a self-adaptive online alignment technology that can optimize the alignment between the 1000 point foci array and the detector array. Successful of the proposed development will significantly strengthen the technology and pave the path towards a startup or joint venture for the next phase commercialization activities with the industry partner.

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Faculty Supervisor:

Qiyin Fang

Student:

Partner:

Lumen Instruments

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

Automobile Purchasing Behaviorial Data Collection, Management, and Analysis

This project investigates automobile purchasing behavior of female millennials. In order to achieve the goal of understanding and making use of purchasing behavior, data are to be collected, managed, and analyzed. In addition to using existing data and third-party data, two major tasks of data collection are the use of questionnaire and web crawling to gather region, product types, and consumer market segment specific information relevant to the partner organization. Customizable tools for data collection and analysis are to be designed, implemented and deployed in collaboration with the partner organization. If meaningful analysis results are obtained, a recommendation system can be designed to match a client’s behavior to potential products of their desire, and targeted marketing and promotion schemes can be devised.

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Faculty Supervisor:

Kin Fun Li

Student:

Partner:

VINN Auto

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Spatio-Temporal Human Activity Recognition on Manufacturing Floors

In industry, inspection of manufacturing floors is handled by humans. The drawback of using humans for this repetitive task is that collected data can be highly prone to bias due to small sample size and industrial engineers can miss relevant details during the cycle time analysis. Calculations often misinterpret the real factory situation. This research aims at finding an automatic computer-vision-based system for manual inspection. Some industries are trying to use wearable sensors, so that they can monitor worker activities. However, such an approach is not readily scalable and can be burdensome to the worker. On the contrary, computer-vision-based activity recognition systems can function without interrupting workflow. This research attempts to find a scalable vision-based AI solution that can perform activity recognition on gateway devices. The goal is to develop a neural network architecture with low computational complexity, taking advantage of state-of-the-art computer vision and deep learning tools.

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Faculty Supervisor:

Jonathan Wu

Student:

Partner:

IFIVEO

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

La réalité virtuelle comme outil de lutte contre la victimisation des personnes aînées

La réalité virtuelle est un outil de plus en plus utilisé par et pour les personnes aînées. Par contre, il y a peu de connaissances scientifiques entourant l’utilisation de cette technologie dans le cadre d’expériences de nature sociale. Ce projet vise donc à mieux comprendre comment les personnes aînées réagissent à des activités de sensibilisations à la maltraitance, l’intimidation et l’âgisme par le biais de la réalité virtuelle, en se joignant à l’activité Les Ateliers 360 de la Fondation Jasmin Roy Sophie Desmarais. De plus, ce projet cherchera à explorer les éléments de cette activité et de la technologie utilisée qui sont perçus comme positifs, à proposer des pistes d’améliorations pour ce genre d’activité et à contribuer à une réflexion sur la place de la réalité virtuelle dans la pratique du travail social.

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Faculty Supervisor:

Marie Beaulieu

Student:

Partner:

Fondation Jasmin Roy Sophie Desmarais

Discipline:

Sociology

Sector:

Education; Other services (except public administration)

University:

Université de Sherbrooke

Program:

Accelerate

Transformation numérique dans une organisation à but non lucratif (OBNL)

Pour assurer le maintien et l’accroissement de la vitalité et visibilité, une organisation à but non lucratif (OBNL) se donne les moyens et la capacité d’adaptation pour évoluer vers une transformation numérique réussie, ainsi que pour créer de la valeur pour leurs clients, projets et services. L’objectif général consiste à analyser l’organisation avant sa transformation numérique, pour ensuite définir les zones d’intervention prioritaires. Nous allons considérer trois éléments pour évaluer leur maturité et identifier leurs besoins en regard de la technologie, de la transformation et de la gestion du changement et de la gestion de projets. L’évaluation de leur maturité et de leurs besoins permettront d’identifier les forces et faiblesses de l’organisation, les compétences à redresser et les cibles d’amélioration, pour ensuite élaborer un plan stratégique numérique.

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Faculty Supervisor:

Véronique Nabelsi

Student:

Partner:

Centre de recherche en technologies langagières

Discipline:

Business

Sector:

Administrative and support, waste management and remediation services; Professional, scientific and technical services

University:

Université du Québec en Outaouais

Program:

Accelerate

Detailing the Life-History, Biology, and Population Ecology of Phorodon cannabis

Cannabis sativa is a plant grown used as industrial hemp, for CBD oil, and both medicinal and recreational cannabis (marijuana). Since production has historically been prohibited in Canada and the USA, little is known about insect pests of cannabis, including a species of aphid, the cannabis aphid (Phorodon cannabis). In order to develop effective management techniques, one first needs to generate an understanding of the insect’s basic biology. The proposed research will document the life-history and ecology of cannabis aphids in commercial fields and greenhouses. This project will be performed with the industry partner, Canopy Growth, which has the field and greenhouse infrastructure to examine these insects in commercial contexts. This project will generate information essential to developing management methods for cannabis aphids that can be directly employed by the partner organization and will be serve as a baseline for future research into the aphid and cannabis pests.

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Faculty Supervisor:

Sean Michael Prager

Student:

Partner:

Canopy Growth

Discipline:

Life Sciences

Sector:

Manufacturing

University:

University of Saskatchewan

Program:

Accelerate

Algorithme décisionnel intelligent pour systèmes énergétiques multi-agents

La consommation énergétique des bâtiments représente à elle seule près de 40% de la consommation énergétique mondiale, et plus de 30% des émissions annuelles de gaz à effet de serre. Dans cet ordre d’idée, l’optimisation du contrôle des chauffages, de la ventilation et de la climatisation (CVC) représente un enjeu majeur pour le secteur énergétique actuel.
Le présent projet met en place un système de contrôle automatisé à base d’intelligence artificielle, spécialement entraîné par renforcement positif sur des données en temps réel et par rapport à l’impact de ses décisions. Ceci permet d’une part d’optimiser le comportement de tout équipement de CVC, peu importe sa nature, sa technologie ou de ses spécificités; d’autre part de présenter une adaptation continue au changement dans son environnement à la suite de son instauration. En plus de mettre à profit toutes ces caractéristiques, les agents considérés sont instaurés sous forme de communauté, afin de tirer profit en plus du développement d’une intelligence collective.
Ce projet à la fine point de la recherche est bénéfique pour l’environnement et le développement durable, et présente un intérêt autant pour les distributeurs électriques, que pour les institutions publiques, les clients privés et les industriels.

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Faculty Supervisor:

Fabian Bastin;François Bouffard

Student:

Partner:

BrainBox AI

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

OPTIMISATION DE PERFORMANCE D’UN RÉSEAU DE DÉTAILEXPLOITANT DES INFORMATIONS VIVES DE DEMANDE, D’OFFRE ET D’OPÉRATION

La présente proposition s’appuie sur un partenariat d’une durée de quatre ans, débutant en avril.2010 et

se terminant en mars.2014, avec le Groupe Aldo, chef de file du domaine de détail des chaussures. Ce

projet d’envergure fait suite à un projet industriel réalisé en 2009-2010, lequel repose sur la recherche

d’efficience opérationnelle basée sur l’exploitation des demandes d’essai capturées en magasins. Fort

de ce partenariat et des avancées significatives déjà réalisées au niveau de l’analyse de la demande,

nous avons identifié, en collaboration avec le Groupe ALDO, de nombreuses pistes et problématiques

de recherche qui font l’objet de cette proposition.

De manière générale, nos buts pour les prochaines années sont d’exploiter des techniques

mathématiques et les technologies de l’information afin de récupérer les informations live du réseau,

dont les demandes d’essai, les ventes (boutique et site web), et les mouvements de stock dans le réseau

logistique, avec comme objectif d’augmenter significativement la qualité et la vitesse décisionnelles..

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Faculty Supervisor:

Benoit Montreuil

Student:

Partner:

Groupe Aldo

Discipline:

Mathematics

Sector:

Retail trade

University:

Université Laval

Program:

Accelerate