Projets novateurs réalisés

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

31 133 projets complétés

2940
AB
5159
C.-B.
837
MB
685
NL
882
SK
9292
ON
9695
QC
97
PE
601
NB
1161
NS

Projets par catégorie

Exploring the transformational potential of regenerative tourism in Southern Ontario

Tourism growth has led to unsustainable and careless practices. An emergent response disrupting such carelessness is regenerative tourism. Regenerative tourism is a transformational approach exploring ways to co-create benefits with local communities and their ecosystems while providing authentic experiences for visitors. While interest in regenerative tourism is growing there are limited studies exploring the benefits for communities in Canada. In response to this gap the aim of this study is to gain new insights about the processes required to engage, co-create, and co-design tourism with communities in Southern Ontario. Considering regenerative tourism in Ontario is particularly important given concerns regarding overtourism and easing of pandemic restrictions. The goal of the project is to explore opportunities for making regenerative tourism impacts with communities to promote flourishing communities and authentic experiences for visitors. Best practices will be shared, as well as educational resources to support other communities pursuing regenerative pathways.

Voir la description complète du projet
Superviseur du corps professoral :

Karla Aileen Boluk

Étudiant :

Partenaire :

Regional Tourism Organization Four Inc.

Discipline :

Sociology

Secteur :

Administrative and support, waste management and remediation services; Other services (except public administration)

Université :

University of Waterloo

Programme :

Accelerate

Projects allocation and advanced scheduling of concurrent construction projects

This project proposes multi-criteria decision-making and mathematical programming (optimization) techniques to design an integrated decision-making tool to assist organizations in managing this complex process and achieving more efficiency. For the first problem, allocating project managers, we develop a multi-criteria decision-making method that will offer the possibility to optimize the usage of PMs’ time considering the specific constraint and the knowledge necessary for the projects. In the second problem, scheduling and supply chain coordination for construction projects, we will consider a portfolio of different concurrent projects and the objective to minimize the total logistics costs. We will formulate this problem as a mixed-integer linear programming model. The integration of logistics decisions with scheduling brings a second level of complexity (NP-hard), and it is important to develop heuristics solution approaches for solving real industrial problems.

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Superviseur du corps professoral :

Amin Chaabane;Mustapha Ouhimmou

Étudiant :

Partenaire :

ARIV inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

École de technologie supérieure

Programme :

Accelerate

SARIT micromobility vehicle

The interns in this project will use their skills in researching parts and products that can be used to achieve the subprojects that we set out to create on the micro-mobility car. In some areas the students may use the machine shop and equipment found in the engineering building on York University campus to create parts. Lastly, the car will have to be tested for insurance and the received data collected to find an insurance suited for the car.

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Superviseur du corps professoral :

Andrew Maxwell

Étudiant :

Partenaire :

Stronach International Inc.

Discipline :

Engineering

Secteur :

Manufacturing

Université :

York University

Programme :

Accelerate

Evaluation of Hemp Seed Products to Ameliorate Fatty Liver Disease and Reduce Cannibalism in Laying Hens

Laying hens need a reliable source of protein and energy for egg production and maintenance that does not induce fatty liver disease (FLD). As egg production moves in the direction of group housing scenarios, more management techniques, including nutritional management, that reduce losses due to feather pecking and cannibalism will also be required. Hemp has anti-inflammatory properties that may prevent FLD. It has anti-microbial properties that may positively affect the gut microbiome of chickens. This may be of interest for hens not housed in conventional cages, thus more susceptible to pathogens. Hemp contains omega-3 fatty acids and CBD, which could positively affect the fatty acid profile of eggs. CBD also has a calming effect in animals and may reduce the incidence of feather pecking and cannibalism in laying hens housed in alternative housing conditions.
The project will include two feeding trials. One trial will be conducted in conventional cage housing to measure the effects of hemp by-products inclusion on fatty liver disease and the potential benefits to the current laying industry. The second trial will be held in an alternative housing system which will meet the requirements of the future Canadian industry after the removal of all conventional cages by 2036.

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Superviseur du corps professoral :

Stephanie Collins

Étudiant :

Partenaire :

Egg Farmers of Canada

Discipline :

Life Sciences

Secteur :

Agriculture; Manufacturing

Université :

Dalhousie University

Programme :

Accelerate

Potential of solar thermal/PV generation for a district energy system and generating a community building electrical and thermal load profile.

This research investigates means for achieving net zero energy dwellings and neighborhoods through maximizing solar potential of dwelling units, isolated and in assemblages. This study will help the community planner to design an efficient layout to achieve maximum solar fraction. Optimum combine building loads in community will lead to a more energy efficient mechanical and electrical design and system. EnergyPlus, building simulation program will be used for estimating the response variables of energy solar potential and energy demand. Climatic, environmental and regulatory data employed in the simulations relate to northern regions and particularly to regions of Canada with similar climate to Toronto. While the specific results obtained are applicable to regions of similar climatic conditions, the methodology employed is generally applicable, and this forms the central focus of this study.

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Superviseur du corps professoral :

Alan Fung

Étudiant :

Partenaire :

S2E Technologies Inc

Discipline :

Engineering

Secteur :

Construction and infrastructure; Finance and Insurance; Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Agricultural Restoration: Building Resilience for Turbulent Times

Restoring degraded land for food production is a major global challenge. The turbulent waves of extreme weather experienced across western North America over the past year continue to shake agricultural producers – farmers must contend with both extreme rainfall and drought while still maintaining financially and ecologically viable systems. This research project will determine the most financially viable agricultural methods for improving soil quality and carbon sequestration on a degraded former horseracing track. Multi-year field trials will be conducted at the Sandown Centre for Regenerative Agriculture on Tseycum traditional land in North Saanich, British Columbia and the results will be shared with the wider agricultural community.

Voir la description complète du projet
Superviseur du corps professoral :

John Volpe

Étudiant :

Partenaire :

Sandown Centre for Regenerative Agriculture

Discipline :

Life Sciences

Secteur :

Agriculture

Université :

University of Victoria

Programme :

Accelerate

Response of tidal marsh revegetation to novel sediment enhancement in the Fraser River Estuary, Canada

Tidal marshes are productive and economically important, providing valuable ecosystem services including disturbance regulation, waste treatment, and the ability to sequester carbon. Sturgeon Bank is a large tidal ecosystem that had a total tidal marsh area of 543 ha at its greatest extent this century. At least 160 ha of tidal marsh at Sturgeon Bank has died off between approximately 1989 and 2011. In addition to increased relative sea level and increased salinity, leading hypotheses as to causes of tidal marsh recession at the western delta front include sediment deficit and goose herbivory. The Sturgeon Bank Sediment Enhancement Pilot Project provides an opportunity to explore an innovative method for tidal marsh restoration. Dredged sediment will be added to the southwestern Sturgeon Bank mudflat over a two-year period, forming three 150 m long and 100 m wide mounds. This applied research project will explore the need to supplement sediment enhancement with tidal marsh revegetation, including the creation of goose exclosures and revegetation by planting bulrush plugs.

Voir la description complète du projet
Superviseur du corps professoral :

Eric Anderson

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

Contrastive Representation Learning on Temporal Point Process Data

The general goal of this project is to improve the downstream tasks by learning better
representations of the data, especially multimodal data pairs, like image/text pairs or user/item
interaction pairs. The user/item interaction data plays an important role in e-commerce, and
analyzing these data can help improve the banking system, e.g., recommendation, risk control, and
etc. The existing methods in this area mostly focusing on using deep neural networks, especially
graph neural network, to learn the connections and dependencies. Here, we want to leverage the
contrastive learning methods into this field, as it shows great power in learning image/text data
pairs representation and expect the learned representations to have better zero-shot performance
at prediction tasks, such as predict the future events.

Voir la description complète du projet
Superviseur du corps professoral :

Arvind Gupta

Étudiant :

Partenaire :

Layer 6 AI

Discipline :

Computer science

Secteur :

Information and Communications Technology

Université :

University of Toronto

Programme :

Accelerate

Valorisation des fibres naturelles dans l’élaboration des matériaux de construction à faible empreinte écologique.

Notre projet de recherche consiste à développer des bétons d’isolations à partir des fibres de jute recyclées. Il faut savoir que les fibres utilisées sont issues du recyclage des poches de jute. Après leurs utilisations, les poches de jute sont jetées dans la nature et considérées comme déchets. Ainsi, les poches de jute sont récupérées, par la suite, les fibres de jute recyclées sont extraites grâce à un procédé de défibrage. Ces fibres sont par la suite mélangées avec de la chaux et/ou du ciment pour l’obtention d’un matériau composite (béton d’isolation) économique et écologique. Une fois le béton formulé, ces performances hygrothermiques et mécaniques sont évaluées.

Voir la description complète du projet
Superviseur du corps professoral :

Ammar Yahia;Rafik Belarbi

Étudiant :

Partenaire :

CIMMS

Discipline :

Engineering

Secteur :

Construction; Sustainability & the Environment

Université :

Université de Sherbrooke

Programme :

Accelerate

Securing an IIoT SaaS platform using blockchain and machine learning methods

Industrial Internet of Things (IIoT) is a scalable platform that integrates devices over the internet and runs different services such as energy and facility management easier than SCADA and similar industrial control systems (ICS). These platforms shall be designed securely and manage devices in a safe environment. However, existing IIoT platforms are not secure by design. Edgecom Energy has developed an IIoT platform based on blockchain technology to address security concerns. This project wilk further improve the security of this IIoT platform at the levels of Operational Technology using blockchain and machine learning methods.

Voir la description complète du projet
Superviseur du corps professoral :

Daniel Amyot;John Mylopoulos

Étudiant :

Partenaire :

Edgecom Energy

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Ottawa

Programme :

Accelerate

Land use implication of developing renewable energy resources: A case study of Atlantic Canada

The path to reaching net-zero emissions by 2050 in Atlantic Canada is both time- and resource-constrained. Energy system models can be used in this context to compare climate change mitigation options and to strategically plan for meeting climate change goals through cost-effective and timely means. Motivated by these circumstances, Net Zero Atlantic is building an open-source energy system model for Atlantic Canada that will serve as a shared tool for answering questions about the future of our region’s energy system. To provide the best utility to regional decision-makers, the Atlantic Canada Energy System (ACES) model must be able to demonstrate energy system solutions that are feasible given the types and characteristics of the resources available in Atlantic Canada. A critical dimension of resource development, land use, is currently not accounted for in the optimization decisions made by the ACES model, which is consistent with the configuration of most capacity expansion energy system models. The lack of land use tracking within the ACES model and other similar models is concerning given the significant land use requirements associated with renewable energy development that have been well established within literature.

Voir la description complète du projet
Superviseur du corps professoral :

Taco Niet

Étudiant :

Partenaire :

Net Zero Atlantic

Discipline :

Mathematics

Secteur :

Professional, scientific and technical services

Université :

Simon Fraser University

Programme :

Accelerate

Geometry Projection Based 3D Object Detection

Unmanned aerial vehicles (UAV) have been deployed in many real-world applications such as payload delivery, agricultural laboring, and aerial photography. Based on GPS-based localization algorithms, these drones have achieved many advancements in industry automation. However, since common GPS receivers do not work indoors, an accurate computer vision (CV) technique is required to resolve the problem in indoor-UAV localization and navigation. In this research project, we aim to address the problem of 3D object detection, tracking and analysis of indoor UAV by deploying a deep-learning-based CV algorithm. The success of this project will support the development of indoor UAV navigation and task-related operation. Also, the study in this field will expand the application in computer vision and boost the full automation in warehouse inventory management.

Voir la description complète du projet
Superviseur du corps professoral :

Igor Gilitschenski;Babak Taati;Steven Waslander

Étudiant :

Partenaire :

SOTI Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

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.