Projets novateurs réalisés

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

30156 projets achevés

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Projets par catégorie

Enhancing Tower Inspection with 5G-Connected Drone Systems

Rogers Communications, with around 8,000 cell towers in Canada, faces challenges in manual inspections, which are slow and risky. In collaboration with Rogers, our research team is developing a cutting-edge solution: small drones enhanced with 5G and AI technology. This approach aims to revolutionize tower inspections by providing faster, more accurate, and safer methods. The drones, augmented with AI at the Mobile Edge Computing level,
will significantly reduce the weight and operational costs, while also minimizing safety hazards. The upcoming phase of our project focuses on advanced computer vision algorithms for comprehensive 2D and 3D analysis,
enhancing inspection quality. Additionally, we plan to integrate Augmented Reality for more efficient, hands-free data collection, eliminating traditional control methods. We are also exploring the potential of generative AI
technologies, such as ChatGPT, to develop intuitive navigation paths for drones. This will streamline operations and boost data collection efficiency, heralding a new era in cellular tower maintenance.

Voir la description complète du projet
Superviseur du corps professoral :

Chul Min Yeum

Étudiant :

Partenaire :

Rogers Communications Inc.

Discipline :

Engineering

Secteur :

Information and cultural industries

Université :

University of Waterloo

Programme :

Accelerate

Deep learning-based quality control for tissue motion tracking in 2D-cine MRI-guided radiotherapy

With real-time acquisition of 2D imaging planes, 2D-cine MRI is often used to visualize rapidly moving tumors and organs-at-risk during radiotherapy, and automatic image registration of 2D-cine MRIs at different time points can assist in tracking tissue displacements. However, when sudden large motions occur, automatic registration algorithms can fail to track the radiation target, potentially resulting in sub-optimal therapeutic outcomes and damaging health tissues. Unfortunately, there is still a lack of automatic methods to detect such events. Therefore, the proposed project will establish novel deep learning algorithms to efficiently and robustly detect large tissue motions and the associated causes, as well as failed tissue motion tracking during radiotherapy. The resulting algorithm is expected to allow effective quality control for existing tissue motion tracking systems in radiotherapy for optimized and consistent radiation dose delivery to the treatment target, leading to an improved quality of life for cancer patients.

Voir la description complète du projet
Superviseur du corps professoral :

Yiming Xiao;Hassan Rivaz

Étudiant :

Partenaire :

Elekta

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology; Manufacturing

Université :

Concordia University

Programme :

Accelerate

Discrete Fracture Network (DFN) application in rock slope engineering

This project is a collaborative endeavour between Rocscience Inc. and Dr. Mitri’s research group at McGill University. Rocscience is a leading firm specializing in the development of geotechnical engineering software. The project aims to validate the discrete fracture network modelling (DFN) approach as a tool for rock slope stability design/ analysis in civil and mining engineering. Data of known slope failures – road cuts and open pit mine slopes – will be collected and analyzed with traditional methods as well with DFN methods. A comparison of the predictions will serve to validate the DFN and reveal its limitations, if any. The project will train a Master of Science Student in Mining Engineering.

Voir la description complète du projet
Superviseur du corps professoral :

Hani Mitri

Étudiant :

Partenaire :

Rocscience Inc

Discipline :

Engineering

Secteur :

Mining; Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Analyse de la cinématique 3D de la marche chez des patients souffrant de douleur post-prothèse totale du genou

Les études démontrent que 15-20 % des patients sont insatisfaits en post prothèse totale du genou. Plusieurs de ces patients présentent de la douleur antérieure. Dans le cas du syndrome fémoro-patellaire, différents déficits biomécaniques pouvant expliquer ces symptômes ont été identifiés. Cependant, aucune étude ne s’est intéressée à la biomécanique du genou chez une population souffrant de douleur post prothèse. L’objectif de ce projet est d’analyser et de comparer la cinématique 3D du genou de patients souffrant de douleur post-prothèse totale du genou et ceux ayant une prothèse totale du genou asymptomatique. Ce projet permettra d’identifier des caractéristiques biomécaniques pouvant être associées au syndrome de douleur post prothèse totale du genou. Par la suite, nous pourrons transférer ces résultats à la clinique et permettre un traitement ciblé pour chaque patient.

Voir la description complète du projet
Superviseur du corps professoral :

Guy Grimard

Étudiant :

Partenaire :

Emovi Inc

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Accelerate

Environmental variability monitoring, data collection and modelling in CEA

Managing a consistent plant environment is critical to maximizing yield and quality of plant produced in a controlled environment agricultural (CEA) systems. The environmental conditions directly impact plant production which in turn impact plant product quality and marketability. The quality of the produced plant (leafy greens, or other plants) are influenced by both the environment and plant species/cultivar tested. Understanding and controlling the variability of the environmental conditions is critical for any plant production operation with the knowledge gained at one location able to be used to improve other production locations. The objective of this study is to design and build a small test growth chamber (< ½ m3) and evaluate and monitor the environmental conditions in the space using a suite of sensors and cameras to attempt to quantify the environmental parameters in this space. These environmental factors will be monitored and tracked, with and without plants, to understand sensor range and consistency. After construction of the testing system plants will be tested in the system to monitor plant growth and plant architecture to link the environmental data with plant production data and develop an environmental thermal and mass flow model to understand how this system operates...

Voir la description complète du projet
Superviseur du corps professoral :

Mark Lefsrud

Étudiant :

Partenaire :

Canadensys Aerospace

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Determining the effectiveness of GIS habitat models for beaver (Castor canadensis) to locate watercourses with high beaver habitat potential in British Columbia

Streams and rivers benefit people and wildlife. Climate change has caused streams and rivers in British Columbia to become drier. Man-made dams retain water but are difficult to maintain. North American beaver (Castor canadensis) build dams that retain water, and quickly repair damage, which help solve man-made dam challenges. Ducks Unlimited Canada wants to use beavers to build dams to transition away from their man-made dams and use beavers to restore habitat for waterfowl. This project will use a computer model called the Beaver Restoration Assessment Tool that determines a watercourse’s capacity to support beaver dam construction. The tool’s accuracy will be examined by comparing the tool’s results with field surveys, and then determine if any inaccuracies can be found with hydrological modelling. The project’s results will ideally help Ducks Unlimited Canada locate beaver habitat and use beaver to mitigate climate change impacts in streams and rivers, and restore wetland habitat for waterfowl.

Voir la description complète du projet
Superviseur du corps professoral :

Douglas Ransome

Étudiant :

Partenaire :

Ducks Unlimited Canada (BC)

Discipline :

Earth science

Secteur :

Finance and Insurance; Other services (except public administration); Professional, scientific and technical services

Université :

British Columbia Institute of Technology

Programme :

Accelerate

Développement d’un pipeline de recherche documentaire ciblée

La montée en puissance de l’intelligence artificielle générative permet de construire de nouveaux produits à la fine pointe de la technologie. Dans le cadre de ce stage, un assistant virtuel capable de lire et interpréter de la documentation technique sera développé. Cette nouvelle approche permettra d’interroger une banque de document en langage naturel (autrement dit, de la même façon qu’on interrogerait un collègue) et d’obtenir des réponses précises avec les références exactes ayant menées à leur génération.

Voir la description complète du projet
Superviseur du corps professoral :

Frédérick Guillot;Éric Boudreault

Étudiant :

Partenaire :

Optel Group

Discipline :

Computer science

Secteur :

Manufacturing

Université :

College d’enseignement general et professionnel de Ste-Foy

Programme :

Business Strategy Internship

Deployment of Pulsed Methane Pyrolysis for Regional Clean Hydrogen Hub Development

NuVista Energy (“NuVista”) intends to develop a commercial scale demonstration of a multi-purpose hydrogen hub with blending for gas-fired turbines and future transportation fueling leveraging the novel Pulse Methane Pyrolysis (PMP) technology to significantly reduce GHG emissions related to fuel gas consumption. The demonstration project will be located at our Wembley gas plant cogeneration facility in Grande Prairie, Alberta. This location is within 1 km of two large peaker plants and offers easy access to heavy transportation traffic.
The project will uniquely investigate hydrogen blending for gas – fired turbine application and provide initial operational experiences that can leverage Alberta’s abundant supply of low-cost natural gas feedstock to accelerate its use across various industries. The integrated research project will also be focused on technical evaluations of hydrogen blending in natural gas – fired cogeneration facilities, technology review of solid carbon applications and hydrogen fuel cell deployment in heavy transport sector. The integration of clean hydrogen production and the diverse, large-scale offtake opportunities will enable substantial emissions reduction for power generation, transportation sectors in the region and beyond.

Voir la description complète du projet
Superviseur du corps professoral :

Irene Herremans

Étudiant :

Partenaire :

NuVista Energy Ltd.

Discipline :

Engineering

Secteur :

Mining

Université :

University of Calgary

Programme :

Business Strategy Internship

Évaluation de la pathogénicité d’une souche d’entomopathogène Beauveria bassiana sur l’abeille domestique (Apidae : Apis mellifera)

Le champignon microbien, Beauveria bassiana, est un agent de contrôle des ravageurs très utilisés dans le monde. Son spectre d’action est large et ce pathogène peut avoir des effets négatifs sur les insectes bénéfiques en culture comme les abeilles domestiques. Celles-ci offrent un service de pollinisation indispensable aux cultures et les récentes inquiétudes au sujet de leur santé ont conscientisé les entreprises qui génèrent des nouveaux agents de contrôle. Anatis Bioprotection, est une compagnie québécoise qui développe et commercialise des agents de lutte biologiques contre les insectes ravageurs. Ils ont développé une souche de B.bassiania qui ne produit pas de toxines, mais il est avant tout impératif de déterminer la pathogénicité de cette souche en laboratoire dans le cadre du processus d’homologation de ce nouvel insecticide microbien.

Voir la description complète du projet
Superviseur du corps professoral :

Valérie Fournier

Étudiant :

Partenaire :

Anatis Bioprotection Inc.

Discipline :

Sociology

Secteur :

Agriculture and Food; Environmental Science and Technology; Sustainability & the Environment

Université :

Université Laval

Programme :

Accelerate

Brain Assistive Tool to Predict Emotional Regulation Failures in Older Adults

The way we regulate our emotions has important implications for our well-being and our social relationships.
Emotional regulation involves monitoring and controlling the intensity of one’s affective response to an external event and/or internal thought process. The impairment of emotional regulation then affects the person’s wellbeing; it also impairs the ability of the family members and/or medical team to help the person. The challenge, therefore, is to find a way to detect when emotional-regulation impairments will occur prior to an emotional outburst. Our project goal is building a portable device for daily use by older adults to detect early signs of emotional regulation issues. From this project, the partner organization will benefit by having a portable brain assistive tool that will assess status, progression and improvement of emotional regulation in older adults. This will improve the management of a person with emotional regulation issues by the medical team and/or family members.

Voir la description complète du projet
Superviseur du corps professoral :

Sergio Camorlinga;Stephen Smith;Amy Desroches

Étudiant :

Partenaire :

Misericordia Health Centre

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology

Université :

University of Winnipeg

Programme :

Accelerate

Screening new amines and adsorbents for CO2 capture with coding for mathematical modeling.

Carbon dioxide is considered one of the main greenhouse gases in the atmosphere. The gas causes huge environmental and social negative impacts. Therefore, it is necessary to reduce gas emissions to benefit the communities and societies. The project focuses on CO2 capture by amine solutions and solid materials. Besides the laboratory measurements, the work continues to optimize the entire capture process to lower the costs. As a result, the CO2 capture projects become more visible to investors. By lowering the CO2 emissions, the greenhouse gas concentrations in the atmosphere could be further reduced. The global warming effects could be mitigated by reducing the emissions. Furthermore, the studies can provide the technologies for other companies such as oil sand corporations to reach the net zero by the federal regulations.

Voir la description complète du projet
Superviseur du corps professoral :

Paitoon Tontiwachwuthikul

Étudiant :

Partenaire :

CSI Climate Change Solutions Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Regina

Programme :

Accelerate

Towards Causal Deep Learning to Model Ecosystems’ Response to Environmental Change

In ecological applications, Machine Learning (ML) predictions are used to make predictions about alternative scenarios. Such alternative scenarios however can change the distribution of features that the ML model relies on for predictions. The implication is that such uses-cases implicitly expect the ML model to generalize outside of the observational distribution. Unfortunately, this is often not the case, and ML models tend to be brittle outside of their training distribution. We will work on causal techniques for more robust ML for ecological applications.

Voir la description complète du projet
Superviseur du corps professoral :

Mathias Lécuyer;Joséphine Gantois

Étudiant :

Partenaire :

École Nationale Supérieure de Techniques Avancées

Discipline :

Computer science

Secteur :

Education

Université :

The University of British Columbia

Programme :

Globalink Research Award

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