Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

31 620 projets complétés

2978
AB
5221
C.-B.
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projets par catégorie

Autonomous Stair-Climbing Domestic Service Robot

The main goal of this project is to develop a more advanced version of the Robotic Stairclimbing Assistant (ROSA), a stair-climbing domestic service robot developed by Quantum Robotic Systems. ROSA can carry heavier household items (e.g., laundry baskets, bins, etc.) between rooms and up stairs. ROSA is meant to help seniors, people with compromised mobility, and isolated individuals cut off from caregivers during the COVID-19 crisis. The research conducted in this project will enable ROSA to use sensors and control software to navigate automatically along paths in your home that may include staircases. For example, starting point “A” could be a main-floor laundry room while ending point “B” could be an upstairs bedroom. The result will be a highly capable product that is unlike any other household robot currently available.

Voir la description complète du projet
Superviseur du corps professoral :

Ryan Billinger;Simon Yang

Étudiant :

Partenaire :

Quantum Robotic Systems Inc

Discipline :

Engineering

Secteur :

Technology; Health and Related Sciences & Technology; Manufacturing and Construction; COVID-19 related Research and Solutions; Quantum Science

Université :

George Brown College of Applied Arts and Technology; University of Guelph

Programme :

Accelerate

Maximizing Intrinsic Learning in an App-Based Approach to Language Learning

This research is focused on optimizing the language learning that occurs when students are allowed to practice English by conversing with native English speakers via a smartphone app, specifically Goji. Learning is best when the student maximizes the density of their practice, returning to practice often. This research will focus on the characteristics of the native English speaking “mentors” such as their personality, intelligence, and even physical appearance. We will assess the extent to which various characteristics predict how often a student chooses to practice and, through practice, the success level they achieve.
Our findings will be useful in terms of informing the mentor characteristics most relevant to student success. This will allow a more informed hiring process and, ultimately, a better learning experience for students.

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Superviseur du corps professoral :

Steve Joordens

Étudiant :

Partenaire :

GOJI

Discipline :

Sociology

Secteur :

Education

Université :

University of Toronto

Programme :

Accelerate

3-D Nanoscale Imaging of Coronavirus Analogues at Various Stages of Cell Infection

In the project, we will use an advanced microscope instrument, called a focused ion beam, to capture 3-D datasets of a coronavirus analogue and SARS-CoV-2 infecting cells to understand its biomechanical relationship at the cellular level. The intern will work on sample preparation, imaging of infection and turning those images into a computerized model to gain insights into the infection mechanism.

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Superviseur du corps professoral :

Nabil Bassim;Kathryn Grandfield

Étudiant :

Partenaire :

Fibics Incorporated

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

McMaster University

Programme :

Accelerate

High yield micro-algal cultures

Micro-algae, which are being used to derive biofuels from, are typically grown in large volumes of water in systems which either expose the algae to, or protect it from, the natural environment. There are two key problems associated with large-scale commercial biofuel production: the identification of high yield and high lipid producing algal species, and maintaining the optimal growing conditions at a commercial scale. The goal of this research is to identify algal cultures which can attain both high yield and lipid production, as well as an increased resistance to invasion and fouling.

Voir la description complète du projet
Superviseur du corps professoral :

Tamara Romanuk

Étudiant :

Partenaire :

SabrTech

Discipline :

Life Sciences

Secteur :

Agriculture

Université :

Dalhousie University

Programme :

Accelerate

Additive Manufacturing of customized imaging instrumentation for SARS-CoV-2 viral research

In the COVID 19 vaccine and anti viral therapy development, advanced optical imaging is used to measure the interaction of virus and the host cell Current microscopes is relatively slow and lacks required customization specific for COVID 19 research To address such a challenge, we plan to develop 3D print ing technology to build a customized microscope capable of high speed quantitative imaging of virus host interactions in live cell s for SARS CoV 2 virus research. The project will deliver an instrument to perfor m SARS CoV 2 vaccine and viral therapy development at McMaster.

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Superviseur du corps professoral :

Cecile Fradin

Étudiant :

Partenaire :

Additive Manufacturing International

Discipline :

Engineering

Secteur :

Manufacturing

Université :

McMaster University

Programme :

Accelerate

Next-Generation Precision Medicine Solutions – Diagnostics

As personalized medicine approaches aim to tailor treatments to individuals, improvements are needed in the detection of existing biomarkers and genomic, epigenomic, and proteomic changes that occur during disease development. This would have potential impact on medication selection and targeted therapy, reduce adverse effects, improve cost effectiveness, and shift the goal of medicine from reactive to preventative clinical decision making1. Liquid biopsies for cancer, in particular, have recently provided the advantage of early and easy screening but their use in replacing traditional methods of diagnosis needs to be validated before widespread adoption. The development of microfluidic approaches has greatly improved the sensitivity and specificity of single cell detection for many disease diagnoses. However, standardization and quality assurance need to be implemented to assure that assay performance is reproducible and robust. Within this proposal we are partnering with Cellular Analytics, a Toronto-based start-up company with a proprietary microfluidic platform (CytoFindTM) that detects protein expression on single cells. This technology will be used to develop and validate CytoFind as a diagnostic for two types of cancer and malignant pleural mesothelioma with the aim of improving clinical decision making and patient outcomes.

Voir la description complète du projet
Superviseur du corps professoral :

Stephane Angers;Shana Kelley

Étudiant :

Partenaire :

Cellular Analytics

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Développement et intégration de modèles prévisionnels de défaillance de machines critiques de sciage par extraction de profils de dégradation

Ce projet vise à démontrer la faisabilité technique et économique de déploiement d’une politique de maintenance axée sur le prévisionnel sur une ligne de production de sciage soigneusement choisie. Sur un horizon de 2 ans, le projet vise à développer, déployer une méthodologie normalisée de mise à niveau pour les scieries afin de migrer du niveau réactif vers une stratégie axée sur des prévisions. Également le projet vise à mesurer les coûts et les bénéfices d’une stratégie de maintenance axée sur des prévisions et finalement livrer à l’industrie du sciage québécois un processus documenté et une interface générique de prédiction des pannes et support de décision pour les responsables de la maintenance pour en faciliter le déploiement. Ce processus pourra ensuite être généralisé et adopté vers d’autres scieries semblables et engagé les scieries dans une direction de maîtrise et d’excellence opérationnelle.

Voir la description complète du projet
Superviseur du corps professoral :

Mohamed-Salah Ouali

Étudiant :

Partenaire :

FPInnovations (Pointe-Claire, QC)

Discipline :

Engineering

Secteur :

Agriculture; Manufacturing; Professional, scientific and technical services

Université :

Polytechnique Montréal

Programme :

Accelerate

Constructing an Integrated Platform that Maps Neighborhood COVID-19 Cases with Census and other Open Data

This project proposes to optimize a map-based web application, which integrates numerous Open Data sets with data on the number of daily cases of COVID-19 in each public health region in Ontario. The platform will be able to merge data from the province’s Integrated Public Health Information System (iPHIS) and offer real time information to government on possible local determinants of the growth in incidence of COVID-19 infections as well as what policies should be employed in arresting the spread of the disease. This will be driven by AI methods that are able to link COVID-19 cases with neighborhood characteristics such as age distribution, population density, occupational distribution, household income, commuting patterns, and density of retail businesses, as well with the presence of lockdown policies and corresponding levels of social mobility captured through Google data. The proposed platform has the potential to make significant policy contributions given the absence of a comparable market product and the current lack of understanding on how COVID-19 is spread within and across communities.The platform is especially relevant given the demand for data on local infections for hotspots and a need for understanding the impact of important determinants.

Voir la description complète du projet
Superviseur du corps professoral :

Anindya Sen

Étudiant :

Partenaire :

Evantage Media

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

The impacts of human activity and landscape change on Rocky Mountain mammal communities

Gaining an understanding of the interacting impacts of human activity and landscape change on wildlife is an important step towards better understanding how to manage and conserve wild areas. The effects of landscape change on mammal communities have been studied, but interacting disturbances are rarely addressed. In Alberta’s Eastern Rockies, human activity is prevalent in the form of various types of recreation and harvesting activities, and landscape features like cutlines and forestry roads allow people increased access to the landscape. To understand how human activity influences species distributions, we will use camera traps to quantify species’ occurrence across the landscape and human use of trails to assess how human use impacts mammals. We will also assess how mammal occurrence is affected by level of landscape protection (unprotected to protected parks and wilderness areas). Results from this study will help inform better conservation and management of public wilderness spaces.

Voir la description complète du projet
Superviseur du corps professoral :

Jason T Fisher

Étudiant :

Partenaire :

Yellowstone to Yukon Conservation Initiative

Discipline :

Life Sciences

Secteur :

Other services (except public administration)

Université :

University of Victoria

Programme :

Accelerate

3D Foot Scanner from Single View Smartphone & 3D Shoe Fit Computation

As a global leader of industrial footwear insoles, MegaComfort is actively engaged in developing innovative products to maintain healthy workers and prevent injuries. The goal of this research project is to provide a system that is able to scan a human foot from a single image or sequence of images (video) and be able to see how good of a fit the virtual 3D foot has when presented with a shoe cavity. The first objective of the project is to improve the architecture of the technique and provide viewpoint and operating performance requirements for use. The second objective is to develop algorithms that are able to register the 3D scanned foot point cloud model with a given point cloud shoe cavity model with the added constraint that the foot model should fit into the shoe model

Voir la description complète du projet
Superviseur du corps professoral :

John Zelek

Étudiant :

Partenaire :

MEGAComfort International Inc.

Discipline :

Engineering

Secteur :

Wholesale trade

Université :

University of Waterloo

Programme :

Accelerate

Development of online rapid cognitive-motor assessment tool to monitor COVID-19-related dysfunction post-discharge

There is recent evidence that surviving COVID-19 (particularly following ventilator use) could result in changes to how well your brain controls functions important for daily living. Currently, however, there are few choices for clinicians to test these functions prior to hospital discharge and at follow-up. This project will develop a web-based cognitive-motor integration assessment tool (e.g., thinking and moving at the same time, important for daily function) that can be used to monitor the integrity of brain networks for higher neurological function. The two-phase project will first develop an existing assessment into one that can be used over the internet. Second, both healthy and post-COVID survivors will use the new web-based tool so that its usability and functionality can be examined and refined. This project will assist individuals and their caregivers in assessing the outcomes and future risks associated with COVID-19 infection- and treatment-caused damage to the central nervous system.

Voir la description complète du projet
Superviseur du corps professoral :

Lauren Sergio;Marin Litoiu

Étudiant :

Partenaire :

ProPlayAI Inc.

Discipline :

Engineering

Secteur :

Information and cultural industries

Université :

York University

Programme :

Accelerate

COVID-19 : module pharmaceutique pour le développement accéléré de produits désinfectants

Galenit est une plateforme de formulation qui facilite le développement de produits de santé. Dans le cadre de ce projet, Galenit souhaite développer sa plateforme afin d’y intégrer l’aide à la formulation de produits désinfectants. Ce nouveau module permettra de développer plus rapidement de nouveaux produits désinfectants à usage topique pour répondre à la pénurie en cours suite à la pandémie liée au COVID-19.
Le module a pour vocation i) d’utiliser la technologie du machine learning / arbre décisionnel pour trouver et proposer aux chimistes des matières premières alternatives à celle présentement indisponible et ii) de valider en temps réel la conformité réglementaire des formules afin de mettre rapidement en marché des nouveaux produits désinfectants.

Voir la description complète du projet
Superviseur du corps professoral :

Fabio Petrillo

Étudiant :

Partenaire :

Galenit

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université du Québec à Chicoutimi

Programme :

Accelerate

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Mitacs — Retour sur innovation

Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.