Innovative Projects Realized

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

29670 Completed Projects

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

Projects by Category

The potential role of vertical agriculture in sustainable and resilient community food systems

Vertical agriculture could play a strong role in sustainable food systems, as it can be used to produce year-round supplies of nutritious foods with low environmental footprints. Vertical farming could be a valuable strategy for developing urban agriculture and local food systems, thereby contributing to sustainable community development and resilience. This research explores this potential by (1) experimenting with growing conditions for a vertical farm (e.g., lighting, nutrient inputs) to determine how to increase yield and nutrition while reducing costs and carbon footprint, and (2) using a map-based online tool to map different vertical agriculture scenarios in a BC city (e.g., distributed small farms, centralized large farms) to examine the social, economic, and environmental outcomes of the scenarios (e.g., local food access, supply chains, GHG emissions, economic viability, etc.). The research involves a collaboration between the University of the Fraser Valley, QuantoTech Solutions (vertical farming specialists), and iOpen Technologies (GIS tools specialists).

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Faculty Supervisor:

Robert Newell;Lenore Newman;Lenore Newman;Robert Newell;Stefania Pizzirani

Student:

Partner:

QuantoTech;i-Open Technologies

Discipline:

Sociology

Sector:

Agriculture

University:

University of the Fraser Valley

Program:

Accelerate

Building a Mindfulness-Based Community of Inquiry to Educate for Regenerative and Sustainable Living in Times of Crisis

The COVID pandemic and looming climate crisis have pushed people to become aware of our vulnerability and rethink our lives/lifestyles. This proposed research sees mindfulness as important in supporting school educators to educate for sustainable living in environmental crises. Mindfulness has gained a mainstream status in school-based programs for its benefits on teachers and students’ wellbeing. Despite growing research on the positive role of mindfulness in education, few studies exist to examine K-12 educators’ personal and practical experiences of engaging mindfulness in educating for environmental sustainability during times of emergency.
This research will develop a knowledge base for understanding how teachers engage mindfulness in their life and work to cultivate their capacity to educate for sustainable living. Findings from this study will contribute to True Peace Sangha’s effort to develop a mindful and sustainable living centre for the common good in Ontario.

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Faculty Supervisor:

Shijing Xu

Student:

Partner:

True Peace Sangha of Toronto;Kawartha World Issues Centre

Discipline:

Sociology

Sector:

Education

University:

University of Windsor

Program:

Accelerate

QT and BIPOC volunteer rider experiences with The Bike Brigade

The Bike Brigade serves vulnerable communities by signing up volunteer cyclists to deliver food and other resources to individuals in need. In collaboration with The Bike Brigade, this project is meant to highlight the experiences of QT and BIPOC volunteer bicyclists, in order to increase The Bike Brigade’s capacity and inform their anti-oppression and equity framework. Research participants will engage in arts-based methods in addition to interviews to discuss the ways in which they use the bicycle to contribute to anti-racism, gender-based violence prevention, and environmental justice, particularly within the context of COVID-19. This project provides space for volunteers to share their stories, and contribute to increasing equity and access to The Bike Brigade’s program, as well as bicycling more broadly.

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Faculty Supervisor:

Lyndsay Hayhurst

Student:

Partner:

The Bike Brigade

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

York University

Program:

Accelerate

The Characterization of Novel and Traditional Plant Proteins

There has been recent scientific and public interest in the development of plant- based proteins as alternate sources to animal protein. With the popularity of vegetarianism and veganism, the demand for plant-based products has significantly increased. Meat being rich in proteins not only makes it nutritionally rich, but also significantly contributes to its texture and palatability. This property, however, has not be achieved in plant- based meat analogues yet. Therefore, this study aims to texturize and test various plant-based protein powders and analyse them at the molecular level. This would help food processors optimize their production parameters and render nutrition-rich plant protein products.

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Faculty Supervisor:

Ashutosh Singh

Student:

Partner:

Griffith Foods Ltd.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Guelph

Program:

Accelerate

Designing global event sets of floods and tropical cyclones under future climates for underwriting, capital management and regulatory purposes

With mounting pressure coming from regulators and other bodies worldwide, the financial services industry (banks, insurers, and reinsurers) will soon need to disclose and stress test their solvency and profitability to various climate scenarios. The work from the Task Force on Climate-related Financial Disclosures (TCFD) thus provides guidance as to how it should be accomplished. Physical risk assessment of the impacts of climate change remains however an important challenge for the global reinsurance industry requiring catastrophe models to be connected to climate models. The general objective of the research project is to build global event sets of floods and tropical cyclones that are consistent with future climate and socioeconomic scenarios to support financial risk management for insurers and reinsurers, climate-related financial disclosures and stress tests, as well as strategic long-term decision-making.

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Faculty Supervisor:

Mathieu Boudreault

Student:

Partner:

AXA XL;AXA XL (UK)

Discipline:

Mathematics

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Université du Québec à Montréal

Program:

Accelerate

FOREX Geocoding System for Foreign Currency Market Monitoring

An existing Forex currency trading system has demonstrated a proof of concept on a static data set. The current project proposes to implement the trading system for real-time applications taking advantage of available geospatial information which can influence currency markets. The novel methodology will be based on building a high-dimensional weighted autocorrelation model between real-time news and their spatio-temporal geographic locations. This would require development of sophisticated methods in the areas of data mining, geocoding and spatio-temporal pattern matching. The developed technology will be incorporated into CTS Forex trading software which will improve its monitoring and predictive capabilities by allowing to change the system trading behavior, i.e. exiting the trade, moving the stop loss and take profit in real-time.

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Faculty Supervisor:

Marina Gavrilova

Student:

Partner:

Winsor Global Financial Inc

Discipline:

Computer science

Sector:

Finance and Insurance

University:

University of Calgary

Program:

Accelerate

Recherche sur l’adaptation des jeunes en lien avec la pandémie de la Covid- 19 : évaluation de l’utilisation et de la satisfaction d’un guide d’intervention pour la reprise du développement psychosocial

La Covid-19 a été déclarée pandémie par l’Organisation mondiale de la santé le 11 mars 2020, résultant d’abord en un
confinement général de la province du Québec de mars à mai 2020, et depuis à des mesures sanitaires restrictives dans le but
de diminuer la propagation du virus. Ce projet de recherche porte sur l’adaptation des jeunes et des familles dans le contexte
de la pandémie de la Covid-19. Il s’agit de poursuivre une recherche qui a débutée à l’été 2020 auprès de parents d’enfants
âgés entre 6 et 17 ans et auprès d’adolescents âgés de 14 à 17. Les résultats issus de ce projet de recherche permettront de
mieux comprendre les facteurs personnels et familiaux liés à l’adaptation des jeunes et des familles lorsque confrontés à une
situation susceptible d’amener une grande charge de stress sur la famille et les individus. Ces résultats pourront mener au
développement d’outils afin de favoriser une meilleure adaptation des jeunes et des familles.

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Faculty Supervisor:

Catherine Laurier;Katherine Pascuzzo

Student:

Partner:

Fondation Jasmin Roy Sophie Desmarais

Discipline:

Sociology

Sector:

Education; Other services (except public administration)

University:

Université de Sherbrooke

Program:

Accelerate

Ultrasound Nerve-block Guidance using Machine Learning

One of the most critical components of ultrasound-guided nerve blocks is the accurate detection of a nerve within an ultrasound image. Trying to classify the various types of tissue in a noisy, greyscale ultrasound feed is a very daunting task. Therefore, a software solution would help doctors to perform the procedure in a precise and effective manner. To date, there have not been many improvements in terms of nerve detection, often resulting in the application of more anesthetic than required. This is problematic because doctors aim to use the minimum amount of anesthetic which poses less of a risk for the patient’s health. This study will present a software-based solution for the detection of nerves in ultrasound images. The software will take advantage of machine learning and image processing techniques to detect the location of the various nerves in the body within an ultrasound feed.

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Faculty Supervisor:

Thomas Hemmerling

Student:

Partner:

Divocco Medical

Discipline:

Life Sciences

Sector:

Retail trade

University:

Research Institute of the McGill University Health Centre

Program:

Accelerate

Application of Machine Learning in Radiation Oncology Scheduling

Cancer incidence rates in Canada are increasing steadily every year which puts a strain on the treatment system. In Quebec, the waiting time to start treatment of cancer patients is enforced by law, however, it is difficult to meet with limited resources and personnel. Efficient planning is hence vital in
reducing the long waiting time of cancer patients as well as improving resources’ utilization and wellness
of medical staff.
Gray is a company founded with the ambition of applying Operations Research and Machine
Learning solutions to improve healthcare quality. Their product GrayOS, which provides multiple
functionalities such as modelling patient flows, automatically scheduling cancer treatments, real-time
optimization, has been deployed and is in the testing phase at the cancer center of CHUM. In this project,
the intern is expected to work with Gray to develop a novel approach for scheduling radiotherapy
treatments.
Scheduling in healthcare is challenging due to the stochastic nature of the field. Future arrivals of
patients are not known in advance, yet have a huge impact on the current scheduling decision. Many
techniques have been developed to take into account future arrivals such as stochastic programming or
Markov Decision Process. However, those techniques usually are algorithmically heavy and might be
difficult to implement and maintain in real-world applications.

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Faculty Supervisor:

Antoine Legrain

Student:

Partner:

Gray Oncology Solutions Inc.

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Optimal building community operation using data-driven mixed-integer convex model predictive control

We propose a new approach to coordinate the energy consumption of the rooftop unit (RTU) heating, cooling, ventilation, and air conditioning (HVAC) system of commercial buildings within an aggregation, e.g., building or units of a shopping center. Our approach uses a new specialized solver for neural network-constrained integer programs to optimize the energy consumption while ensuring that (i) temperature preferences are respected in each building and (ii) electric network constraints like voltage magnitude or maximum line current are satisfied in the vicinity of the aggregation. The latter is important when taking part to demand response programs as can induce a sudden drop in power consumption or if the aggregation includes electric vehicle charging stations or solar panels that can significantly alter its power consumption. The expected benefit to BrainBox AI is a readily implementable approach that can (i) optimally, efficiently, and safely be used on one of their main client types, commercial buildings, and (ii) be built on to integrate new, refined building specificities by the partner.

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Faculty Supervisor:

Antoine Lesage-Landry

Student:

Partner:

BrainBox AI

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Minimization of Switching Power Converter Ripples in RF Power Amplifier Circuits

As the power processing density in new technologies such as 5G and 6G increases, reduction of ripples caused by switching power converter operation becomes a gradually more difficult design problem to solve. Analysis of these ripples and exploring various methods for the ripple reduction in the RF power amplifier circuits are the main topics for this project. Except of developing and evaluation of various HW solutions for the ripple reduction, additional benefits for the partner organization include improving the design process by reusing algorithms developed for i) analysis of ripple voltage in circuits with switching power converters, ii) analysis of currents through electrolytic capacitors, and iii) design of the switching power converters. On the intern’s side, working on the project will create opportunity to gain industrial experience, specifically learning new skills and acquiring knowledge in the power supply area, and also learning the design process from the industry leader.

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Faculty Supervisor:

Michel Nakhla;Ram Achar;Xiaoyu Wang

Student:

Partner:

Ericsson Canada Inc (Kanata, ON)

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing

University:

Carleton University

Program:

Accelerate

Réduction du bruit dans la ventilation minière souterraine

Le bruit des ventilateurs est une problématique de santé et sécurité au travail importante. Ainsi, des mesures effectuées sur des ventilateurs installés dans des mines du Québec ont montré des niveaux de bruit supérieurs à 100 dB(A), ce qui peut entrainer des lésions auditives majeures. D’autre part, dans les mines, le bruit des ventilateurs peut masquer le bruit des alarmes de recul de certains engins [Trudel 2011]. Le bruit des ventilateurs peut donc conduire à des situations dangereuses pour la santé et la sécurité des travailleurs. Le contrôle du bruit des ventilateurs est un donc un enjeu majeur dans l’industrie minière, qui est demandeuse d’équipements de ventilation plus silencieux. Dans ce contexte général, des études plus spécifiques concernant la mesure de la puissance acoustique des ventilateurs chez Équipements KN et l’étude de différents dispositifs de réduction du bruit, comme les silencieux seront menées.

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Faculty Supervisor:

Patrice Masson

Student:

Partner:

Equipements KN

Discipline:

Engineering

Sector:

Mining

University:

Université de Sherbrooke

Program:

Accelerate

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