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

Utilisation d’un microréseau hybride pour la production et le stockage de l’hydrogène

Cette recherche vise à concevoir, dimensionner et optimiser un système novateur pour produire, liquéfier et stocker l’hydrogène en exploitant l’eau de mer et le vent des côtes du Nouveau Brunswick. On compte maximiser son rendement énergétique et sa robustesse tout en minimisant le coût économique et environnemental. Ceci passe par le choix des sources d’énergie renouvelable (hydrolienne, éolienne, pile à combustible), le développement de l’architecture d’électronique de puissance, la modélisation des électrolyseurs et des composants du système, le dimensionnement, le contrôle, la simulation numérique et les tests expérimentaux.
L’intérêt réside dans la production de l’hydrogène, l’oxygène et l’électricité propres, durables tout en exploitant les ressources marines de manière innovante, fiable et rentable

Voir la description complète du projet
Superviseur du corps professoral :

Jamel Ghouili

Étudiant :

Partenaire :

Arthur Sivret and Fils Ltd.

Discipline :

Engineering

Secteur :

Construction and infrastructure

Université :

Université de Moncton

Programme :

Accelerate

Identifying resistant short-season soybean breeding material and QTL involved in sudden death syndrome (Fusarium virguliforme) resistance in two short-season soybean breeding populations

Soybean sudden death syndrome (SDS), caused by Fusarium virguliforme, causes yield losses amounting to $ 500
M and $ 32 M (CAD) in the USA and Ontario annually, with yield losses reaching 100% in affected fields in
epidemic years. Resistant cultivars are one of the most effective ways of minimizing yield losses due to SDS.
Despite having been originally detected in the USA in 1971, few short-season cultivars have been developed,
primarily due to its more recent discovery in Ontario (1995) and Québec (2020). Additionally, no studies examining
QTL presence in short-season soybean germplasm or cultivars have been performed, with studies focusing
primarily on long-season soybean or including all maturity groups making it difficult for short-season soybean
breeders to identify parents. This project aims to identify resistant material in order to improve resistance in shortseason
soybean

Voir la description complète du projet
Superviseur du corps professoral :

Valerio Hoyos-Villegas;Jacquie Bede;Valerio Hoyos-Villegas

Étudiant :

Partenaire :

CÉROM

Discipline :

Life Sciences

Secteur :

Agriculture and Food

Université :

McGill University

Programme :

Accelerate

Comparative analysis of the lettuce root microbiome under soil and hydroponic growing conditions

A comparative analysis of the root microbiomes of lettuce grown in soil to lettuce grown in hydroponic systems.
The microbial community composition for each root sample will be identified using DNA sequencing and compared
to determine differences between each sample. This information will help Ceragen improve their ability to identify
plant growth promoting microbes that can survive in a hydroponic environment.

Voir la description complète du projet
Superviseur du corps professoral :

Allyson MacLean

Étudiant :

Partenaire :

Ceragen Inc.

Discipline :

Life Sciences

Secteur :

Agriculture; Professional, scientific and technical services

Université :

University of Ottawa

Programme :

Accelerate

Étude des facteurs limitant la performance d’un réflectomètre optique cohérent dans le domaine temporel (C-OTDR) et optimisation par traitement de signal

L’objectif du projet est d’innover dans la conception d’un C-OTDR (Coherent Optical Time Domain Reflectometer) et de trouver le meilleur compromis entre la performance et les coûts. Les C-OTDR sont utilisés dans des marchés niches tels que les applications de mesure sur les liens sous-marins ainsi que dans différents types de senseurs haut de gamme tels que les senseurs de vibration acoustiques réflectométriques. Par rapport à un OTDR standard à détection directe, un C-OTDR permet en théorie de doubler la plage dynamique de mesure. Ceci est d’intérêt pour une large gamme d’applications qui sont présentement hors de portée des C-OTDR actuels en raison du coût. Une fois la conception bien maitrisée, un cahier des charges d’un C-OTDR basé sur un circuit photonique intégré (PIC) combinant les éléments clés sera réalisé afin d’investiguer la mise à l’échelle de la solution développée sur la plateforme technologique de silicium sur isolant (SOI).

Voir la description complète du projet
Superviseur du corps professoral :

Sophie LaRochelle

Étudiant :

Partenaire :

EXFO

Discipline :

Engineering

Secteur :

Information and cultural industries

Université :

Université Laval

Programme :

Accelerate

Risk assessment of OT and IT infrastructure components

Over 18,000 systems, including those of numerous government agencies and corporations, as well as 15 critical infrastructure companies in gas, oil, electricity, and manufacturing, were affected by the SolarWinds supply chain attack, resulting in an estimated recovery cost of over 100 billion1. This attack highlights the increased interconnectivity between IT networks and OT systems due to the growth in data processing needs and the adoption of Industrial Internet-of- Things (IIoT) devices. However, manufacturers often neglect security considerations and release potentially vulnerable IIoT devices, which can be easily exploited by adversaries.
Poorly designed devices may allow the execution of arbitrary commands and firmware reprogramming, which can have a profound impact on the security and resiliency of OT systems.
Despite existing security mechanisms to enhance IoT/IT security, many research and operational issues remain unsolved and unimplemented in practice. This project address some of the existing gaps and focus on the accurate risk assessment of OT/IT networks.

Voir la description complète du projet
Superviseur du corps professoral :

Natalia Stakhanova

Étudiant :

Partenaire :

International Minerals Innovation Institute;Cameco Corporation (Saskatoon, SK);Nutrien;BHP

Discipline :

Computer science

Secteur :

Mining; Professional, scientific and technical services

Université :

University of Saskatchewan

Programme :

Accelerate

AGROBOT: An Autonomous Robotics System for Automated weed detection and eradication

The research project involves three interns collaborating on an innovative solution to improve farm management by automating weed control. Intern #1 is tasked with developing a smart system that uses machine learning and
computer vision to distinguish between crops and weeds, ensuring the robot can identify what needs to be removed without damaging valuable plants. The other two students will focus on the robot’s movement and
operation: one will refine how the robot’s arms move precisely to target and eliminate weeds based on the identifications made by the first student’s system. The second will work on optimizing the robot’s ability to navigate
and plan its actions in the dynamic outdoor environment of a farm. This collaborative effort aims to create a robot that can autonomously keep fields free of weeds, reducing the need for chemical herbicides and manual labor.
For the industry partner, this project promises a state-of-the-art agricultural tool that enhances efficiency, sustainability, and crop yield, potentially transforming modern precision farming practices.

Voir la description complète du projet
Superviseur du corps professoral :

Mehrdad Saif

Étudiant :

Partenaire :

BHF Agrobot

Discipline :

Engineering

Secteur :

Agriculture; Manufacturing

Université :

University of Windsor

Programme :

Accelerate

Development of the anti-fouling hard marine coatings with increased resistance to grooming and cleaning

This proposal outlines the development of a novel polymeric hard marine paint with antifouling and easy-to-clean performance, mechanically compatible with the state of the art in-field grooming and cleaning technologies. This proposal targets reaching a 120 days of biofouling prevention in static deployment conditions, the chemical composition of the novel paint non-inclusive of toxins or biocides, typically utilized in the conventional anti-fouling systems to maintain the foul-free paint finishes. The significance of this research lies in its potential to redefine marine coatings, offering an environmentally friendly alternative to current biocide-reliant solutions, with the main objectives encompassing such novel and highly industry-sought improvements, as the superior mechanical durability, 0-toxicity to the aquatic environment, and applicability to the most wear-demanding market of ice-resistant marine paints.

Voir la description complète du projet
Superviseur du corps professoral :

Kevin Plucknett

Étudiant :

Partenaire :

GIT Coatings

Discipline :

Physics

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Dalhousie University

Programme :

Accelerate

Selective Dissolution And Precipitation For PVC Recovery In A Circular Vinyl Economy

This project aims to revolutionize PVC recycling in a circular vinyl economy by further developing and optimizing a novel approach called Selective Dissolution and Precipitation (SDP). PVC, a widely used plastic, poses recycling challenges due to its complex composition, especially in multilayer materials, like coated fabrics. SDP involves selectively dissolving PVC from mixed plastic waste and then precipitating it back in a purified form. This innovative method not only facilitates efficient PVC recovery but also minimizes environmental impact compared to traditional recycling methods. The project will investigate optimal solvents for selective PVC dissolution, optimize the reuse of recycled PVC from the process, and assess the economic and environmental feasibility of scaling up SDP for industrial. Successful implementation of SDP could significantly contribute to closing the PVC recycling loop, promoting sustainability, reducing landfill waste for multilayer systems, and increasing recycled content to reduce the reliance on virgin components, thus advancing the goals of a circular economy.

Voir la description complète du projet
Superviseur du corps professoral :

Li Xi

Étudiant :

Partenaire :

Oligomaster Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

McMaster University

Programme :

Accelerate

Assessing impingement risk and patient outcomes after total hip arthroplasty with optimized acetabular cup placement

Total hip replacement usually provides good outcomes for patients. Sometimes, if one part of the artificial hip is placed incorrectly, it can cause the hip to dislocate and require a second surgery to fix the implant. New computer software has been developed by our partner to guide the surgeon during the operation to place the artificial hip in the best spot for each patient. We will use x-rays taken with the patient in different leg positions after surgery to see if using this software will lower the risk of the hip dislocating, compared to patients who had hip replacement without the software. CT imaging will be conducted to gain a better understanding of possible bone and muscle quality factors influencing dislocation. Patients will also complete a questionnaire asking about their outcomes. If patients who had hip replacement with the software have better outcomes and less dislocation risk, this will provide evidence the partner can use to help support the use of the software more routinely in our healthcare system.

Voir la description complète du projet
Superviseur du corps professoral :

Brent Lanting;Matthew Teeter

Étudiant :

Partenaire :

Smith+Nephew

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Lawson Health Research Institute

Programme :

Accelerate

Assessing generalization training of the Puppet Academy system

A resource to measure collaborative practice and generalized learning within minutes needs to be easy of use, effective and provide intrinsic motivation to engage users. This project advances the company’s commercialization opportunities by expanding entry into larger organizations and provides an additional opportunity to expand market reach. In the future, the product can be used to conduct collaborative research within training institutions and as a training tool for pre-professional collaborative education and practice.

Voir la description complète du projet
Superviseur du corps professoral :

Lizbeth Escobedo

Étudiant :

Partenaire :

SaySo Communication

Discipline :

Computer science

Secteur :

Education

Université :

Dalhousie University

Programme :

Accelerate

Preventing ice accretion on electrical utility infrastructure by surface engineering

Every winter Quebecers, Canadians and basically anyone living in northern climates suffer from icing related failures (power blackouts, fallen trees, blocked roads, etc.). In the best case, meteorological forecasts and HQ’s ice-removal measures are timely, costly, and the society does not experience the severe effect caused by harsh winter weather. Currently applied active ice protection or removal systems are highly labor-intensive, energy­consuming and/or polluting processes. In the proposed collaborative research between McGill and Hydro-Quebec, we will translate promising laboratory research results obtained from finely woven metallic fabric with excellent passive ice-shedding ability to real world utility infrastructure. In this context, two master students will be trained and obtain valuable insights to the research environment at Hydro-Quebec’s industrial research center IREQ and at McGill University.

Voir la description complète du projet
Superviseur du corps professoral :

Anne-Marie Kietzig

Étudiant :

Partenaire :

Hydro-Quebec

Discipline :

Engineering

Secteur :

Sustainability and the Environment; Energy and Utilities; Clean Technology

Université :

McGill University

Programme :

Accelerate

Reinforcement-Based Large Language Models to Enhance Energy Management Platform

Reinforcement Learning in Large Language Models (RL-LLM) is revolutionizing how AI understands and responds to human language, improving virtual assistants in various fields. It teaches models to follow instructions effectively, even with vague prompts, reducing inappropriate responses and false information. RL-LLM’s application extends to sectors like healthcare, finance, and online shopping, enhancing product suggestions and aiding quick medical information comprehension.
The project further explores RL’s role in energy management, aiming to refine algorithms for decision-making accuracy. It integrates IoT and Edge Computing for efficient data acquisition, develops adaptive algorithms for changing energy patterns, and ensures ethical AI implementation. Ultimately, the project aims to advance Edgecom’s energy management platform for smarter, more efficient, and responsible solutions.
AI is a key development theme for Edgecom moving forward and this project will help supplement our limited expertise and experience in this field. This project will provide significant benefit to the company in the form of increased innovation and product development capacity, an improved product offering, and further differentiation versus competition.

Voir la description complète du projet
Superviseur du corps professoral :

Alireza Bakhshai

Étudiant :

Partenaire :

Edgecom Energy

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Queen's University

Programme :

Accelerate

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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.