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

Development of Supervised and Unsupervised Computer Vision Methods to Quantify Salmon and Forage Fish Biodiversity from Underwater Video

Underwater video cameras are a convenient method to monitor aquatic life such as fish. However, these cameras can collect a lot of footage, which can be challenging for humans to process. This project will use computer vision to automatically sort through video taken within and near to seaweed farms to specify the clips that have fish in them. The computers will then help identify and count rare and common fish to describe how marine organisms use seaweed farms as habitat. This information helps companies like Cascadia Seaweed farm seaweed in better ways to promote marine biodiversity by making their farms better habitats for marine life.

View Full Project Description
Faculty Supervisor:

Alexandra Branzan Albu;Francis Juanes

Student:

Partner:

Cascadia Seaweed

Discipline:

Computer science

Sector:

Sustainability & the Environment; Artificial Intelligence; Aquaculture and Fishing

University:

University of Victoria

Program:

Accelerate

Artificial Intelligence for Condition Assessment of Critical Infrastructure

Unexpected deterioration and failure of concrete infrastructure causes major disruptions and in the most severe
cases, results in lives lost. According to the 2019 Canadian Infrastructure Report Card, Canadian public
infrastructure is at risk therefore, detecting and addressing deterioration in such structures is crucial. The Damage
Rating Index (DRI), a reliable novel quantitative microscopic procedure, is currently used to assess deterioration
in concrete. Yet, its use is limited since it is time-consuming besides requiring experienced operators. Automating
the DRI using artificial intelligence (AI), reducing human error and increasing its accessibility leading towards more
complete diagnosis, has the potential to revolutionize the monitoring and management of critical concrete
infrastructure, enabling early detection, preventing minor disruptions and catastrophic failures and helping in the
selection of rehabilitation strategies to extend the lifespan of aging/deteriorating structures. Combined with the
collaboration of Englobe and their expertise in concrete materials, this project will achieve fruitful results.

View Full Project Description
Faculty Supervisor:

Leandro Sanchez

Student:

Partner:

Englobe

Discipline:

Engineering

Sector:

Construction; Artificial Intelligence

University:

University of Ottawa

Program:

Accelerate

An Aerodynamic-Acoustic Design of an Electrical and Shrouded Tail Rotor

Aerospace industry innovations targets reduction of fuel consumption and noise emission. Electrical power-bywire
enabled technology address these challenges yielding lighter designs, increased operation flexibility and cost
reduction. With electric motors having variable rotational speed, constraints in design and optimization strategies
for rotor and propellers can be released. ln addition to conventional aircraft and rotorcraft, new concepts arise in
the urban air mobility or autonomous air delivery markets. Noise annoyance during manoeuvre and local
community noise concerns around heliports have to be addressed early by manufacturers. This research project
is intended to take on the challenge with the development of aerodynamic-aeroacoustic coupled optimization
methods for the design of quieter rotor and propellers. The objective of the partnership Bell Textron Canada
Limited and Optis Engineering is to develop a coupled aerodynamic-aeroacoustic optimization framework for an
electrical distributed anti-torque (EDAT) system to equip future Bell helicopters produced in Canada.

View Full Project Description
Faculty Supervisor:

Marlène Sanjosé;Stéphane Moreau;Sivakumaran Nadarajah

Student:

Partner:

Bell Textron Canada;Optis Consultants Inc

Discipline:

Engineering

Sector:

Manufacturing; Transportation and warehousing

University:

École de technologie supérieure; McGill University; Université de Sherbrooke

Program:

Accelerate

Documentation et évaluation d’un projet de transition socio-écologique dans une perspective d’amélioration et de mise à l’échelle

La génération de déchets dans le secteur de la restauration a emporté est un fléau. Alors que la Ville de Montréal vient d’adopter un règlement interdisant l’utilisation de plastiques à usage unique, l’entreprise d’économie sociale Retournzy coop propose un modèle innovant d’économie circulaire et de partage de contenants réutilisables consignés sous forme d’un réseau. L’objectif de la recherche sera de documenter les résultats et indicateurs des opérations menées sur le terrain afin de formuler des recommandations quant à l’amélioration du processus dans une perspective de validation de l’intervention comme réponse à l’objectif de départ ainsi qu’une perspective de mise à l’échelle.

View Full Project Description
Faculty Supervisor:

Luciano Barin Cruz

Student:

Partner:

Retournzy Coop de Solidarité

Discipline:

Business

Sector:

Real estate and rental and leasing

University:

HEC Montréal

Program:

Accelerate

Early Biomarkers for Prediction of Chemotherapy-induced RNA Disruption in Tumour Cells

Chemotherapy agents can induce the degradation of a molecule in tumour cells called RNA. We call this phenomenon “RNA disruption”. High tumour RNA disruption after about 1 month of chemotherapy predicts for complete tumour destruction and improved cancer patient survival. We and Rna Diagnostics, Inc. are using this knowledge to predict patient outcome from chemotherapy. Patients with tumours not exhibiting high RNA disruption are likely to benefit from discontinuing chemotherapy and moving on to other treatments. We now have knowledge of earlier events within tumour cells that precede RNA disruption. The student will example some of these earlier events, with the goal of possibly identifying new tools to predict chemotherapy treatment outcome even earlier during treatment.

View Full Project Description
Faculty Supervisor:

Tom Kovala

Student:

Partner:

RNA Diagnostics Inc

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

Laurentian University

Program:

Accelerate

Le profil du client selon l’aire de diffusion: une application au domaine culturel

Un des gros défis des entreprises culturelles et artistiques est celui de la connaissance de leur public. Cette connaissance est le principal fondement pour la mise en place d’actions marketing pertinentes (Colbert & Dantas, 2019). Certes, les informations fournies par les systèmes de billetterie sont utiles pour la prise de décision. Cependant, ces informations ne sont pas suffisantes pour dresser un profil du public consommateur de spectacles. Ainsi, à l’aide de données de billetterie (Tuxedo) correspondant à plus de 15 000 spectacles, de codes postaux (Postes Canada) et des aires de diffusion (Statistiques Canada), nous allons établir le profil des clients ayant acheté des billets pour chacun des spectacles analysés.

View Full Project Description
Faculty Supervisor:

Danilo Dantas

Student:

Partner:

Groupe iCible Inc.

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

HEC Montréal

Program:

Accelerate

Cost-effective leachate treatment using aerobic granular sludge technology

Landfill leachate is a complex wastewater composed of organic carbon, nitrogen compounds, dissolved solids, and heavy metals. Leachate characteristics may differ depending on the waste landfilled, climate conditions, and landfill age. Because of the toxic and recalcitrant nature of its constituents, landfill leachate wastewater (LLW) must be treated before being released to the environment. There is an urgent need to develop robust and energy and cost efficient leachate treatment processes that can handle the high organic carbon and high ammonia loadings of leachate while be able to withstand the toxicity and inhibition that may arise due to the heavy metals of leachate.
In this two-year project, Dr. Liu’s research group at the University of Alberta will collaborate with the City of Edmonton, to develop and optimize aerobic granular sludge (AGS)-based nitritation/denitritation/anammox treatment processes for energy efficient high-strength LLW treatment. Pilot-scale bioreactors will be operated and optimized for enhanced ammonia reduction efficiency, improved energy efficiency and reduced environmental impacts for LLW treatment. The focus will be to determine the optimal conditions for LLW treatment and select the operation conditions and control strategies most favorable for developing a robust microbiome within bioreactors.

View Full Project Description
Faculty Supervisor:

Yang Liu

Student:

Partner:

City of Edmonton

Discipline:

Engineering

Sector:

Administrative and support, waste management and remediation services; Public administration

University:

University of Alberta

Program:

Accelerate

Using Technology for Curriculum-Based Measurement of Literacy

We do not have an effective Canadian Curriculum-Based Measurement Tool. Moreover, existing tools do not incorporate Artificial Intelligence. We aim to develop a tool that will enable the targeted and brief assessment of gaps in student literacy skills with the aim of allowing strategic instruction to be planned and delivered based on those gaps. Identifying and addressing these gaps is critical to improving student trajectories and ensuring their later success. Year 1 of our joint research project will implement established programs to provide online tutorial sessions. These sessions will enable data collection so that we can begin the development of a Curriculum-Based Measurement Tool in year 2. This tool will be developed using models that were created with the Year 1 data.

View Full Project Description
Faculty Supervisor:

Carrie Demmans Epp;Janet Werker

Student:

Partner:

uLearnify Ltd.

Discipline:

Computer science

Sector:

Education

University:

University of Alberta

Program:

Accelerate

Remotely Piloted Aircraft Systems for Precision Agriculture in Canadian Stone Fruit Orchards

On this project, the use of tethered remotely piloted aircraft systems to protect stone fruit orchards will be explored. The intern sill design and evaluate the performance of such aircraft systems and conduct both ground and in-flight testing of the system. BAAZ UAV will benefit from this technology and the potential deployment to support Canadian stone fruit producers in adapting to increasingly unpredictable and unfavourable growing conditions due to climate change.

View Full Project Description
Faculty Supervisor:

Jeremy Laliberté

Student:

Partner:

BAAZ UAV

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

Development of new RNA-guided dual-cleaving nucleases

Gene editing with RNA-guided nucleases based on the CRISPR bacterial defence system (clustered regularly interspaced palindromic repeats) has revolutionized both basic science and therapeutic applications. However, CRISPR associated (Cas) nucleases are not optimized for all types of gene-editing applications. In particular, the double-strand breaks made in DNA by the Cas proteins are imperfectly repaired by cellular DNA repair pathways that lead to a spectrum of gene-editing outcomes. The goal of this project is to develop new dual-cleaving RNA guided nucleases that generate defined gene-editing outcomes and that can target sequences not accessible by commonly used Cas9 nucleases. Given the wide-spread adoption of gene-editing technologies, the new dual-cleaving nucleases would provide alternative and improved gene-editing tools for basic scientific studies by academic and industry researchers. For Specific Biologics, this partnership supports future downstream therapeutic use of new dual-cleaving nucleases to target genetic mutations that cannot be targeted with current gene editors.

View Full Project Description
Faculty Supervisor:

David Edgell

Student:

Partner:

Specific Biologics Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of Western Ontario

Program:

Accelerate

In Pursuit of Local Histories: Regent Park Film Festival and the Immediacy of the Archive

To commemorate its 20th anniversary in 2022, the Regent Park Film Festival will commission four local IBPOC artists (prioritizing gender diversity and those from Regent Park or similar communities in Toronto) to produce digital media art works that engage with the history of Regent Park. The basis for their artistic engagements will include visual source material such as archival footage of Regent Park (documentaries, news coverage, home videos from residents etc.), as well as narrative forms set in Regent Park (short and feature films, web series episodes, music videos etc.). The Mitacs Post-Doctoral researcher will support the production of the films both through archival research, interviews with community stakeholders and the creation of an online digital interface that will support and extend the films.

View Full Project Description
Faculty Supervisor:

Janine Marchessault;Desiree de Jesus

Student:

Partner:

Regent Park Film Festival

Discipline:

Sociology

Sector:

Arts, entertainment and recreation

University:

York University

Program:

Accelerate

Generative Face Models for Video Chat and Broadcast

In today’s world, the video chat and conferencing has been a necessary part of overall routine life (both personal and work). Currently, the video chat and broadcast technologies require lots of bandwidth to transmit high quality data. In overall project, we aim to make video transmission data intelligent by using the state-of-the-art AI technology. This will not only reduce the size of video data but will also include the ‘instructions’ to give users creative control of their representations and serve as a segue to the metaverse – the intelligent part.
In this part of the project, we are planning to utilize the state-of-the-art face generating StyleGan2 neural network that convert the face video data into the compressed, intelligent, and ready-for-transmission data format. At the receiving end, the transmitted instructions will be used to regenerate the transmitted video data. The additional instructions to manipulate the video will provide the useful mechanism to generate the avatars with realistic faces – a must have feature for upcoming metaverse.

View Full Project Description
Faculty Supervisor:

Abdul Bais

Student:

Partner:

Cya Live

Discipline:

Engineering

Sector:

Artificial Intelligence; Information and Communications Technology; Entertainment and Media

University:

University of Regina

Program:

Accelerate