Projets novateurs réalisés

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

29 670 projets achevés

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4990
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801
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663
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825
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8841
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9197
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95
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568
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Projets par catégorie

Détection radar des mouvements humains en présence d’artéfacts environnementaux

Ce projet vise à mettre au point de nouvelles méthodes d’intelligence artificielle pour améliorer la détection de chutes à l’aide d’un radar. L’utilisation d’un radar permet la détection de chutes dans un domicile tout en protégeant la vie privée des personnes grâce à l’absence de prise d’image et ne nécessite aucun capteur porté. Cela permet d’alerter les soignants des chutes et permet ainsi de maintenir les personnes plus longtemps à domicile, en sécurité. Le but du projet est d’améliorer la détection de chutes lorsqu’il y d’autres objets ou sujets en mouvement dans la pièce. Ainsi, des rideaux qui bougent avec le vent, des?ventilateurs, la vibration d’un réfrigérateur ou encore des tuyaux dans les murs représentent des sources plausibles de “pollution” qui gêne la détection des chutes par radar. Pour améliorer la performance, nous développerons dans ce projet des méthodes d’apprentissage automatique pour identifier et séparer le mouvement d’une personne des sources de bruits.

Voir la description complète du projet
Superviseur du corps professoral :

Guillaume-Alexandre Bilodeau;François Nougarou

Étudiant :

Partenaire :

Morphée+ Inc.

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Information and Communications Technology; Clean Technology

Université :

Polytechnique Montréal

Programme :

Accelerate

Decolonizing our Data: Integrating Indigenous Perspectives and Ways of Knowing Within the Kingston Resiliency Dashboard Project

Based on the intersection of: (1) the lack in understanding the effects of COVID-19 on various municipal sectors; and (2) the necessity of integrating Indigenous perspectives and data concerning contemporary Indigenous communities within the Kingston area, in informing how to build resiliency, Indigenize projects, and decolonize research, this research seeks to Indigenize the Kingston Resiliency Dashboard Project where possible. This phase of the research project will be accomplished by using qualitative research methods and data analysis to comprehensively interrogate and critique existing dashboard indicators, and add/or change sections to forefront Indigenous perspectives. Moreover, the beginning phases of identifying and mapping Indigenous cultural heritage within Kingston and the greater area will be produced for Kingston & Area Association of Museums, Art Galleries and Historic Sites (KAM) in this project. We hope that in beginning to address these gaps, users of the dashboard can be presented with aggregated and accessible data that can shed light into the ways to build municipal and community resiliency- most importantly of which, involves processes of Indigenization.

Voir la description complète du projet
Superviseur du corps professoral :

Carolyn DeLoyde

Étudiant :

Partenaire :

Kingston Association of Museums, Art Galleries and Historic Sites

Discipline :

Sociology

Secteur :

Information and cultural industries

Université :

Queen's University

Programme :

Accelerate

Expanding the product spectrum of anaerobic digestion for a circular economy

Canada has enormous potential to recover renewable energy and chemicals from over 18 million tonnes of waste generated annually while simultaneously reducing greenhouse gas (GHG) emissions associated with landfilling that account for 13% of national methane emissions. The proposed project will develop the fundamental science and technologies needed to realize sustainable waste to chemicals manufacturing by producing high value medium chain fatty acids from food waste and wastewater biosolids for use as animal feed additives, industrial products, and transportation fuel precursors. Transfer of know-how and biotechnologies to project partner organizations will position them to effectively translate technologies to the waste and chemicals sectors.

Voir la description complète du projet
Superviseur du corps professoral :

Christopher Lawson

Étudiant :

Partenaire :

Veolia Water Technologies & Solutions;CBS Bio Platforms

Discipline :

Engineering

Secteur :

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

Université :

University of Toronto

Programme :

Accelerate

Analyse de la turbulence de bord dans un réacteur à fusion thermonucléaire

Dans le cadre du stage, le stagiaire sera amené à créer des outils d’analyse informatique afin de caractériser la turbulence du plasma (un gaz contenant des électrons libres) de fusion nucléaire. La fusion nucléaire est une technologie émergente permettant de créer de l’énergie propre en grande quantité par la fusion d’atomes en éléments plus lourds. Pour réaliser cette réaction, on doit placer le plasma dans des conditions extrêmes de pression et de température pour lui permettre d’atteindre et de maintenir une fusion stable. Les turbulences qu’il vivra pourraient faire perdre le contrôle du plasma aux expérimentateurs, ce qui aurait pour résultat l’échec de la réaction. Le but du stage est de créer des outils informatiques qui pourront analyser ces turbulences (spécifiquement les turbulences de bord) à l’aide d’image vidéo pour prévenir et diagnostiquer la perte de contrôle du plasma avant que celui-ci ne s’échappe du confinement. Cela permettra de préserver la réaction plus longtemps et évitera les dommages aux équipements.

Voir la description complète du projet
Superviseur du corps professoral :

Ahmad Hamdan

Étudiant :

Partenaire :

Université de Lorraine

Discipline :

Physics

Secteur :

Education

Université :

Université de Montréal

Programme :

Globalink Research Award

Optimal Numerical-Weather-Prediction Parameters for Wind-Power Forecasting

BC Hydro purchases power from four independent wind farms in British Columbia to supplement their hydropower. But wind is not steady, so BC Hydro must compensate for shortfalls or excesses in wind power to provide steady, reliable, economical power to its customers. To achieve this reliability, BC Hydro uses wind forecasts provided by the University of British Columbia (UBC). These forecasts are made with computer codes called Numerical Weather Prediction models that describe atmospheric airflow, but each model has a range of options.
This project will experiment with different model options to achieve the best wind forecasts. Intern 2 will test different representations of the bottom part of the atmosphere where wind turbines are located. Intern 1 will evaluate whether resolving the finer details of wind shifts with altitude are worth the extra computation time. Intern 3 will identify the best starting data for each forecast.

Voir la description complète du projet
Superviseur du corps professoral :

Roland Stull

Étudiant :

Partenaire :

BC Hydro (Burnaby, BC);University of British Columbia

Discipline :

Earth science

Secteur :

Utilities

Université :

The University of British Columbia

Programme :

Accelerate

Deep learning based ultrasound guidance for robotic spinal interventions

Pedicle screws are used often in a spinal fusion to add support and strength to the fusion while it heals. Traditionally, a large incision is made to implant screws and rods that stabilize the spine. In contrast, percutaneous pedicle fixation is a minimally invasive spine surgery technique, performed through the skin without a traditional large incision to implant screws and rods that stabilize the spine. The the BIROB Center (host institution) and Koellner Medical (https://koellner-medical.com) collaborate in the development of a new concept for robot-assisted percutaneous pedicle screw fixation. Previously, the Queen’s Perk Lab developed the concept of real-time tracked ultrasound guidance for planning and guiding percutaneous pedicle screw insertion and developed deep learning based ultrasound image segmentation. The overall objective of the project is to integrate deep learning real-time tracked ultrasound guidance in the BIROB-Koellner robotic spine surgery platform.

Voir la description complète du projet
Superviseur du corps professoral :

Gabor Fichtinger

Étudiant :

Partenaire :

Óbuda University

Discipline :

Computer science

Secteur :

Other; Artificial Intelligence; Biotechnology

Université :

Queen's University

Programme :

Globalink Research Award

A Smart Prosthetic Liner

Lower limb prosthesis users typically wear a silicone liner on their residual limb, which is the interface between their body and the prosthetic socket. Knowing the in-socket pressure distribution is extremely beneficial in ensuring proper socket fit and thus better gait and higher quality of life for amputees, considering the need of amputees for a limb monitoring system. The technology of self-sensing prosthetic liner is developed during the Ph.D. program of the intern. The technology must pass some development stages, as well as market research under the supervision of mentors before it can enter the market. During Lab2Market, the intern will be involved in different projects to learn about different aspects of the commercialization of the research product. It can form hypotheses about the business plan, potential customers, and entry points.

Voir la description complète du projet
Superviseur du corps professoral :

Fae Azhari

Étudiant :

Partenaire :

Springboard Atlantic Inc.

Discipline :

Engineering

Secteur :

Technology; Health and Related Sciences & Technology

Université :

University of Toronto

Programme :

Accelerate

Social prescribing, allyship, and community engagement for the evolution of health (SPACE for Health)

Social determinants of health, including factors such as social isolation, food insecurity, and income, play a big part in our health. To account for these important social factors, some healthcare organizations have begun to adopt a strategy called social prescribing which involves regularly asking people if they need help with social determinant of health issues and connecting patients with community resources that can help. The small amount of research on social prescribing has generally found that it makes healthcare and patients better but, many healthcare organizations either don’t have or are not satisfied with their current social prescribing program. We will work with several healthcare organizations in stroke, diabetes, and family medicine to improve their current social prescribing programs and measure the impact this has on patient health. This program is expected to improve patient/community health and create a supportive community which are the goals of Compassionate Community Kingston Canada.

Voir la description complète du projet
Superviseur du corps professoral :

Rylan Egan

Étudiant :

Partenaire :

Compassionate Communities Kingston

Discipline :

Sociology

Secteur :

Social Innovation; Health and Related Sciences & Technology; Other

Université :

Queen's University

Programme :

Accelerate

Portable and Handheld Near-Infrared Imaging Camera Utilizing Nanomaterials and Nanotechnologies

The near-infrared imaging is a technique widely used in many medical applications, such as tissue imaging and non-invasive imaging of lymphatic systems. The market was estimated to be USD 950 million in 2021 and is expected to grow at a compound annual growth rate of 10.1% to 2028. The conventional near-infrared system commonly employed is bulky and costly. To this end, we aim to develop a compact and cost-effective near-infrared imaging camera that everyone can have at home for regular screening of health conditions, which could potentially help early-stage cancer diagnosis. To keep the product cost low, we combine and leverage the mature semiconductor technology and advanced nanomaterials.

Voir la description complète du projet
Superviseur du corps professoral :

Xihua Wang

Étudiant :

Partenaire :

Springboard Atlantic Inc.

Discipline :

Engineering

Secteur :

Nanotechnology; Health and Related Sciences & Technology

Université :

University of Alberta

Programme :

Accelerate

A computer vision system for the evaluation of swine welfare based on analysis of lesions on carcases

Human-caused bruises, tail lesions caused by tail biting, ear lesions, among other things, in slaughter pigs are detrimental to animal welfare, a violation of the Animal Welfare Act, and a source of public concern. Animal-based indicators of welfare are quantifiable characteristics on the animal that are reflective of what the animal has experienced. The evaluation of animal welfare indicators on swine carcasses could offer a cost-effective method to welfare analysis and quality assurance. In this project, we propose a system which will perform welfare assessing images from carcasses, obtained by camera installed in a slaughter. The purpose of this project is to develop a computer vision system that uses deep learning and indicators of welfare on swine carcasses to accurately inform about the welfare of swine on-farm, and the relationship between welfare indicators and total or partial condemnations.

Voir la description complète du projet
Superviseur du corps professoral :

Yolande Seddon;Seok-bum Ko

Étudiant :

Partenaire :

Maple Leaf Foods (Mississauga, ON);Olymel

Discipline :

Engineering

Secteur :

Agriculture; Wholesale trade

Université :

University of Saskatchewan

Programme :

Accelerate

Development of a culture process to expand and differentiate satellite cells, a first step en route to prototyping a cultivated bovine meat

This project consists of the first steps toward the development of a prototype of cultivated bovine meat and to produce at pilot scale. Starting from proprietary (Meatleo Inc.) bovine satellite cells, five (5) key objectives have been set: (1) To develop and validate a protocol, including a serum-free culture medium, to expand bovine satellite cells and to differentiate them into muscle fibers; (2) To develop and validate a protocol, including a serum-free culture medium, to expand bovine progenitor cells and to differentiate them into adipocytes.

Voir la description complète du projet
Superviseur du corps professoral :

Patrick Vermette

Étudiant :

Partenaire :

Meatleo Inc.

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Sherbrooke

Programme :

Accelerate

AI-based interpretation of lung ultrasound

Lung ultrasound is an efficient and widespread method used in bedside diagnostic examinations. The interpretation of ultrasound in emergency care is an extremely difficult task, especially for less experienced physicians. The objective of the project is to implement and validate comprehensive AI-based approach using deep learning to assist in identifying diagnostically relevant imaging features and making diagnosis.

Voir la description complète du projet
Superviseur du corps professoral :

Gabor Fichtinger

Étudiant :

Partenaire :

Óbuda University

Discipline :

Computer science

Secteur :

Artificial Intelligence; Biotechnology; Other

Université :

Queen's University

Programme :

Globalink Research Award

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