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
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825
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8841
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9197
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95
PE
568
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1088
NS

Projects by Category

A rapid detection test (RDT) to determine surface contamination by the SARS-CoV2 virus

The residual bacterial and viral contamination that remains on surfaces after cleaning in healthcare and palliative care settings is particularly lethal during a pandemic. Due to inevitable overcrowding and long shift hours, slipups occur. A technique to monitor surface cleanliness, and particularly to detect the presence of SARS-CoV2, is required to ascertain contamination and, if necessary, refine cleaning processes. We will develop a swab-based rapid detection test (RDT) kit to determine the presence of the SARS- CoV2 virus on surfaces. The RDT is based on a proven particle plasmon resonance sensing method using gold nanoparticles commercialized by our industry partner Genemis Labs. During our research, we will modify this sensing technique and make it specific to SARSCoV2 virus using antibodies specific to its viral surface proteins. Gold nanoparticles will be functionalized with antibodies and stabilized in a colloidal suspension that, along with a single-use sample processing apparatus and a portable colorimeter, will be used to detect colour changes that quantify relative surface viral load. The RDT will provide a quick method to monitor the presence of SARS- CoV2 and verify a surface cleaning procedure, thereby
diminishing infection spread and standardizing best practices across facilities.

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Faculty Supervisor:

Ishwar Puri;Rakesh P Sahu

Student:

Partner:

Genemis Laboratories

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

Development of an integrated online enzymatic micro-fluidic chip for glycoprotein analysisusing Chip-Cub QToF mass spectrometry

Glycoprotein analysis is very important in different field such as cancer and pharmaceutical research,
as ‘more than 70% of the proteins are glycosylated. However, the sample preparation of glycoprotein
for glycan profiling is very tedious as includes many enzymatic steps that could go for -36 hrs. This
project aims to develop a one chip reactor that can be used to prepare the glycoprotein(s) for mass
spectrometry analysis. This reactor includes online multi-enzymatic steps to eventually have the
glycans that are expressed on the glycoprotein, characterized and relatively quantified using mass
spectrometry. This chip can only be used on Agilent chip-cub that combined with Agilent QToF mass
spectrometry, which will lead to develop their Immunoglobulin commercial kit to be general for any Nglycoproteins.

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Faculty Supervisor:

James Dennis

Student:

Partner:

Agilent Technologies

Discipline:

Life Sciences

Sector:

University:

University of Toronto

Program:

Accelerate

Machine learning and the COVID Black Box: Safe monitoring of COVID-19 ICU beds, assessment centres, and surgeries

The project aims to optimize healthcare provider and patient safety and monitor PPE use, to optimize resource utilization during the COVID-19 pandemic. Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. With the data collected from operating room black box, the main aim is to analyze 1) hand hygiene, 2) adherence to personal protective equipment (PPE) protocols, 3) breaches in safety, and 4) system vulnerability in Ontario.

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Faculty Supervisor:

Animesh Garg

Student:

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Mitigating Snowy Owl Aircraft Collisions by Relocation

To aid in active management of Snowy Owls and other raptors at airports, it is essential to understand the spatial distribution and movement behaviour of birds both on and off the airfield. The impact of airfields on birds may be particularly pronounced because airfields provide open, undeveloped land similar to early successional habitats that are perceived as high quality by many species. Airport collisions are a significant threat to Snowy Owls and humans, and preventative measures cost over $500 million dollars each in North America alone. By using tracking technology and GIS software, our project will quantify movement data and environmental factors influencing relocations of Snowy Owls from airport facilities. This research will improve our understanding of Snowy Owl relocation behaviour and provide critical data to improve relocation efforts and to minimize collisions between airplanes and Snowy Owls.

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Faculty Supervisor:

Kyle Elliott

Student:

Partner:

Falcon Environmental Services

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

COVID-19 Monitor: a rolling public opinion study on the dynamics of the pandemic

This project will undertake a year-long rolling study of public opinion across eight countries—Canada, the United States, the United Kingdom, Australia, New Zealand, France, Germany and Brazil. It will measure the health, social, and economic impacts of COVID-19 throughout the duration of the pandemic and during its immediate aftermath. The study will be comprised of multiple survey waves in each country, mostly drawn from Vox Pop Labs’ proprietary online respondent panel, which is comprised of several million people worldwide. The proposed research team will be responsible for continuously adapting the survey design to reflect the changing dynamics around the pandemic, for analyzing the incoming data from the surveys, and for promptly and continuously engaging in knowledge mobilization via means such as government briefings, media contributions, and other public information resources.

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Faculty Supervisor:

Michelle Dion

Student:

Partner:

Vox Pop Labs Inc

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Generating a COVID-19 vaccine using ministring DNA and virus-like particles

The COVID-19 pandemic is a global health crisis on an unprecedented scale, with over 1 million confirmed cases, spread over 200 countries. With the world at a virtual standstill, and no existing treatments, there is an enormous need for novel therapeutics and vaccines to combat COVID-19. Our group is working on a DNA vaccine strategy that exploits our proprietary miniaturized DNA vector technology, called ministring DNA (msDNA), to encode and deliver specially engineered copies of COVID-19 viral proteins. Once delivered into human host cells, these proteins will be designed to self-assemble into viral-like particles (VLPs). VLPs are safe, generate a strong host immune response, and have a record of commercial success as vaccine products. We are confident that our strategy will lead to the development of an effective COVID-19 DNA vaccine.

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Faculty Supervisor:

Marc Aucoin;Shawn Wettig;Andrew Doxey;Roderick Slavcev;Mahla Poudineh

Student:

Partner:

Mediphage Bioceuticals Inc

Discipline:

Life Sciences

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Sous-réseau d’antenne pour Radar à Synthèse d’Ouverture destiné à la mesure de masse de neige

Le projet consistera à concevoir et analyser un sous-réseau d’antenne qui devra s’intégrer à une grande antenne réseau, formant le coeur d’un radar à synthèse d’ouverture (RSO). Ce RSO sera utilisé sur une satellite à basse orbite et sa mission sera d’obtenir des images de la couverture, et plus spécifiquement de la masse de neige dans les régions nordiques du Canada. Le suivi de l’évolution de la masse de neige devient nécessaire à cause du réchauffement global. L’étudiant stagiaire bénéficiera de l’expertise d’ingénieurs spécialisés en conception d’antennes de satellite de la compagnie MDA, chef de file mondial dans le domaine des charges utiles de satellites de communication et de télédétection.

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Faculty Supervisor:

Jean-Jacques Laurin

Student:

Partner:

MacDonald, Dettwiler, and Associates Ltd (Sainte-Anne-de-Bellevue, QC)

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Pattern Recognition and Event Forecasting to Increase the Performance of Industrial Bioprocesses, in an Effort to Accelerate the Sustainable Development of the Transformation Industry

The first objective is to use ML to reduce the modeling error in predicting the end-of-growth of a batch, reducing the emission of CO2 and water consumption of synthesized products. The second objective is to formulate the algorithms to facilitate its integration into our analytics solution. The third objective is to validate shared learning when applied for 1) forecasting other events and 2) forecasting the same events using similar but different datasets from different users. Finally, the fourth objective is to use this algorithm as a starting point to develop a learning platform to help our customers to learn from the best practice of the industry. The success of the project will 1) enable a significant increase in the efficiency of our customers’ processes with significant environment and social impacts, 2) trigger a series of sales, 3) improve our toolset to create a better offer to our customers, 4) to set a baseline for the development of advanced AI-based tools and expertise.

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Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

BioIntelligence Technologies inc

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Improvement of covid-19 treatment with machine learning

Currently, testing the population more at risk to be severely ill is a cumbersome process. There is a limit to the capacity and the resources of the healthcare system that show a need to be more efficient in discovering infected person. Being able to quickly detect infected person helps reduce the risk of infecting others and it is especially important in environments like nursing homes where there is a high density of person at risk. Using an earpiece that work as a connected object, it is possible to monitor some signals such as cardiac rhythm, level of CO2, and cough. Using machine learning, those data could be used to detect automatically if a person has symptoms that should be checked by a health professional. It would improve the efficiency of detecting infected persons and, therefore, help healthcare providers manage the workload caused by covid-19.

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Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

JACOBB

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Development of Optical Clearing Materials Towards Oral Lesion Pathology Screening with Optical Coherence Tomography

The early identification of oral cancers will help to reduce serious complications and death associated with these diseases. Currently, identification of cancerous tissues relies significantly on visual identification during oral exams before more accurate further testing is performed. The use of optical coherence tomography (OCT) has allowed for more accurate initial identification of cancerous tissues, but suffers from limitations in resolution and how far into tissues can be analyzed. We propose to develop methods and techniques to allow deeper and clearer imaging into oral tissues to allow for more accurate identification of early-stage cancerous tissues. This will involve the development of materials that can be applied to the gum tissues to allow for better imaging into the tissues, as well as modifications of the OCT system and image processing techniques to improve depth and clarity of images.

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Faculty Supervisor:

Ozzy Mermut

Student:

Partner:

LiveVue Technologies

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Online economic tool to quantify the health benefits of municipal investments in urban greenspaces

7.2. Public Project Overview:
The project will develop an online tool to quantify the economic return on investment resulting from improvements in public health attributed to investments in urban greenspaces. The tool will focus on three pathways: improvements in physical health, improvements in mental health and health benefits associated with improved climate resiliency. The tool will provide provincial, municipal and community organizations a mechanism to support informed program, policy and planning decisions and will help users better understand and communicate the value of greenspace investments.

View Full Project Description
Faculty Supervisor:

Jeffrey Wilson

Student:

Partner:

Green Analytics

Discipline:

Sociology

Sector:

Information and cultural industries; Professional, scientific and technical services; Wholesale trade

University:

University of Waterloo

Program:

Accelerate

Real-time quality monitoring tool development for remote laser welding ofsheet metal assemblies in automotive applications

Individual stamped sheet metal components need to be joined to create sheet metal assemblies
used in a car. Powerful laser light delivered by a robot is used to quickly weld these assemblies by
making dozens of individual welds within a few minutes. For economical production, it is essential
to minimize the total production cycle time. At the same time, high-quality welds must be
produced. Undetected defective weld joints would lead to severe penalties if delivered to the
company’s customer. Currently, all assemblies must be manually inspected. An automated realtime
laser weld monitoring system is being investigated. The system monitors the intensity of the
radiation emitted at the weld. It has been found that the system is not meeting the company’s
requirements. The proposed project intends to identify the defects that need to be detected, design
experiments where defects are reproduced artificially, and correlate these with the observations of
the monitoring system.

View Full Project Description
Faculty Supervisor:

Gene Zak

Student:

Partner:

Van-Rob Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

Queen's University

Program:

Accelerate

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