Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

30508 Completed Projects

2882
AB
5105
BC
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projects by Category

Valorisation des données générées par les robots de traite pour appuyer la gestion de troupeau dans les fermes laitières du Québec et des provinces Atlantiques – Year 2

L’utilisation de robots de traite pour les vaches laitières est en hausse dans les troupeaux laitiers au Québec et dans les provinces Atlantiques. Ce système robotisé démontre des avantages pour la gestion du temps de travail, le bien-être et la productivité des vaches. L’utilisation des robots de traite génère un grand nombre de données qui peuvent être utilisées pour la gestion de troupeau. Cependant, l’information qu’ils produisent reste souvent confinée à la ferme. En plus, le très grand nombre de données générées limite leur utilisation par les producteurs eux-mêmes puisqu’il devient difficile de cibler l’information importante dans cette surabondance de renseignements. L’objectif de ce projet est de faire appel à la science des données pour trouver une méthode de valorisation des données de robots de traite, de façon à appuyer les producteurs dans leur gestion de troupeau. Cela mènera à une meilleure utilisation des données générées sur la ferme, en plus de créer un effet structurant dont tout le secteur laitier pourrait bénéficier.

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Faculty Supervisor:

Elsa Vasseur

Student:

Partner:

Lactanet (QC)

Discipline:

Life Sciences

Sector:

Agriculture and Food

University:

McGill University

Program:

Elevate

Valorisation des données générées par les robots de traite pour appuyer la gestion de troupeau dans les fermes laitières du Québec et des provinces Atlantiques

L’utilisation de robots de traite pour les vaches laitières est en hausse dans les troupeaux laitiers au Québec et dans les provinces Atlantiques. Ce système robotisé démontre des avantages pour la gestion du temps de travail, le bien-être et la productivité des vaches. L’utilisation des robots de traite génère un grand nombre de données qui peuvent être utilisées pour la gestion de troupeau. Cependant, l’information qu’ils produisent reste souvent confinée à la ferme. En plus, le très grand nombre de données générées limite leur utilisation par les producteurs eux-mêmes puisqu’il devient difficile de cibler l’information importante dans cette surabondance de renseignements. L’objectif de ce projet est de faire appel à la science des données pour trouver une méthode de valorisation des données de robots de traite, de façon à appuyer les producteurs dans leur gestion de troupeau. Cela mènera à une meilleure utilisation des données générées sur la ferme, en plus de créer un effet structurant dont tout le secteur laitier pourrait bénéficier.

View Full Project Description
Faculty Supervisor:

Elsa Vasseur

Student:

Partner:

Lactanet (QC)

Discipline:

Life Sciences

Sector:

Agriculture and Food

University:

McGill University

Program:

Elevate

Développement d’un modèle technico-économique de bioraffinerie forestière régionale et intégrée à La Tuque (QC, Canada) – Year 2

Au Canada, les résidus forestiers constituent une biomasse renouvelable, pratiquement non utilisée et abondante, qui peut être transformée en biocarburants. La valorisation de cette ressource permettrait ainsi de diminuer les émissions de gaz à effet de serre et notre dépendance aux énergies fossiles, particulièrement dans le secteur des transports. L’établissement en Haute-Mauricie d’une bioraffinerie industrielle de production de biodiesel de type « drop-in » à partir de résidus forestiers est considéré. Le projet consiste à évaluer la faisabilité socio-économique, technique et environnementale de cette bioraffinerie ainsi qu’à développer un outil pour évaluer des installations futures similaires. L’OBNL partenaire, BioÉnergie La Tuque, a pour mandat de promouvoir le développement des bioénergies à La Tuque. La réalisation de ce projet est primordiale pour assurer la réussite de son mandat et pour revitaliser, par création d’emplois, l’industrie forestière dans la région qui représente une partie considérable de l’activité économique.

View Full Project Description
Faculty Supervisor:

Simon Barnabé

Student:

Partner:

BioÉnergie La Tuque

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Elevate

Développement d’un modèle technico-économique de bioraffinerie forestière régionale et intégrée à La Tuque (QC, Canada)

Au Canada, les résidus forestiers constituent une biomasse renouvelable, pratiquement non utilisée et abondante, qui peut être transformée en biocarburants. La valorisation de cette ressource permettrait ainsi de diminuer les émissions de gaz à effet de serre et notre dépendance aux énergies fossiles, particulièrement dans le secteur des transports. L’établissement en Haute-Mauricie d’une bioraffinerie industrielle de production de biodiesel de type « drop-in » à partir de résidus forestiers est considéré. Le projet consiste à évaluer la faisabilité socio-économique, technique et environnementale de cette bioraffinerie ainsi qu’à développer un outil pour évaluer des installations futures similaires. L’OBNL partenaire, BioÉnergie La Tuque, a pour mandat de promouvoir le développement des bioénergies à La Tuque. La réalisation de ce projet est primordiale pour assurer la réussite de son mandat et pour revitaliser, par création d’emplois, l’industrie forestière dans la région qui représente une partie considérable de l’activité économique.

View Full Project Description
Faculty Supervisor:

Simon Barnabé

Student:

Partner:

BioÉnergie La Tuque

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Elevate

Improving the calibration of a multi-camera system for accurate tool tracking

This research aims at improving the accuracy of a 3D-vision tracking system. The physical set-up consists of a tool to be tracked, such as a drill, with one or more planar patterns attached to it and a set of cameras. This set consists of one to four camera clusters, where each cluster has one or more cameras. The current tracking system consists of several modules, including one for the calibration of the cameras (intrinsic and extrinsic), and another one for the calculation of the 3D coordinates of an unknown physical point, the tip of the tool. The quality of all subsequent processes heavily depends on the accuracy of the system calibration of the multi-camera set-up. This project focuses on these two modules by (1) evaluating the existing calibration method and (2) devising better algorithms to improve the accuracy of both the calibration and the estimated 3D coordinates of the tool tip.

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Faculty Supervisor:

Boubakeur Boufama

Student:

Partner:

Radix Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

Brain Decoding Models for neurodegenerative disease aided diagnosis and classification

Globally, brain-related diseases such as Alzheimer’s disease and Epilepsy have a huge toll on patients, loved ones, and healthcare systems. The research project aims to establish a model to better diagnose neurodegenerative diseases. There is a wealth of clinical test data, symptoms, and observations associated with the long list of neurodegenerative diseases. In
order to better understand underlying causes of these diseases, neuroinformaticians are developing software tools to link the volumes of data to underlying causes of each brain-related
illness. The research aims to apply computational tools and approaches to understand the brain and integrate symptom information to help interpret and treat neurodegenerative diseases. The project aims to develop a generic brain decoding model which would be able to aid diagnosis, understanding, and patient treatment. The project is a significant undertaking given the structural, functional, and environmental variables across patients thus making diagnosis particularly challenging.

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Faculty Supervisor:

Rustom Bhiladvala

Student:

Partner:

Beihang University

Discipline:

Engineering

Sector:

Education

University:

University of Victoria

Program:

Globalink Research Award

Flexible In-Home Caching for Video Streaming Services

NightShift optimizes customers’ bandwidth usage when using streaming services. It does this by taking advantage of off-peak bandwidth availability to cache digital media content
addressing both problems of limited bandwidth (which impacts real-time streaming) and bandwidth quotas (which can result in bandwidth throttling or overage charges). The goal of
this research is to explore interfaces that allow end-user control of local storage and download while still preserving digital rights security and the platform (e.g. Netflix) experience
of viewing content. In particular, we will explore:
• Intuitive web interfaces to manage local content.
• Intuitive web interfaces to communicate bandwidth consumption trade-offs to end users.
• Multi-device set-ups to support simultaneous viewing and content management both in terms of download and in terms of local content storage.

View Full Project Description
Faculty Supervisor:

Edward Lank

Student:

Partner:

Aterlo Networks Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Waterloo

Program:

Accelerate

Developing strategies for informed collaborative decision making forvegetation management on northern Rights-of-Way

Integrated Vegetation Management (IVM) is an approach that utility companies can use to manage vegetation under or near transmission lines and has been successfully applied in southern jurisdictions. IVM requires practitioners to understand and manipulate plant communities to meet management objectives, such as maintaining a low growing plant communities that help prevent the regrowth of trees. Selective herbicide application is a common technique used in IVM, however, questions remain regarding the effectiveness and environmental impact of IVM and herbicide use in northern boreal ecosystems. In addition, northern Indigenous communities that use rights-of-way (ROWs) and surrounding environments for trapping, hunting and traditional food and medicinal plant harvesting have expressed concerns regarding the use of herbicides. Our project will address both the environmental and social aspects of assessing the risks associated with IVM and herbicide use on northern ROWs in order to provide relevant local data for informed collaborative decision making. We propose to take a unique approach by simultaneously developing improved community engagement strategies while working closely with both industry and community members to provide key information for effective vegetation management of northern ROWs.

View Full Project Description
Faculty Supervisor:

Katherine Stewart;Maureen Reed

Student:

Partner:

SaskPower

Discipline:

Earth science

Sector:

Utilities

University:

University of Saskatchewan

Program:

Accelerate

Duplicate detection for billing systems

Merging different sub-companies into TELUS caused some of customer records to be repeated through the merged data-set. Algorithms are needed to determine the duplicate records. Currently a deterministic algorithm is being used in TELUS. In this project, we will investigate if machine learning can help to detect duplicates. Solving this problem has several parts. We have to preprocess the data and select some features from the TELUS records that help us in our model. A probabilistic model should be selected, implemented and tuned. Then, it is necessary to test the proposed model and compare that with the current systems.

View Full Project Description
Faculty Supervisor:

David Poole

Student:

Partner:

TELUS (Vancouver, BC)

Discipline:

Computer science

Sector:

Information and cultural industries

University:

The University of British Columbia

Program:

Accelerate

CryoDrive: The effects that implementation of cryogenic engines would have on underground mining processes

Cryogenic engines, such as the Dearman engine, produce work and substantial cooling with zero emissions at the point of use, due to their liquid nitrogen ‘fuel’ supply. Background work has shown that technically, (power, turn down ratio, responsiveness, torque), there are few identifiable factors that would prevent this type of engine from being very effective if installed in underground mining vehicles. For the mines, one important logistical difference implied in a switch to cryogenic engines is that liquid nitrogen would need to be distributed underground, rather than diesel fuel; distribution systems supporting the mining process would have to change too. The intern will draw upon the mining expertise at MIRARCO and work with the
Dearman Engine Company and Air Products Inc, to develop deeper understanding of the infrastructure required for large scale use of refrigerating cryogens underground and how the logistical arrangements may affect the safety and productivity of mining systems.

View Full Project Description
Faculty Supervisor:

Dean Millar

Student:

Partner:

Mining Innovation, Rehabilitation and Applied Research Corporation

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Laurentian University

Program:

Accelerate

Identification of medical marijuana cultivars with novel therapeutic potential

Neuropsychiatric disorders, including depression and anxiety, represent prevalent and disabling medical conditions affecting society. Despite the urgent need for novel pharmacotherapeutics to treat these conditions, there are few new drugs in development by the pharmaceutical industry. Cannabis has been used by humans for thousands of years to self-medicate a range of different neuropsychiatric symptoms, although few studies have addressed this issue in a scientific manner. With the dramatic rise of the medical marijuana industry in Canada, there is an urgent need to identify which cultivars may be of clinical benefit. We will therefore evaluate the potential therapeutic efficacy of different cannabis cultivars using sophisticated animal models. Cultivars which vary in their constituent cannabinoids will be tested using a panel of neuropsychological assays that assess both clinical properties as well as potential side-effects. Our industry partner will combine their expertise in neurochemistry with our results to help us identify key cultivars for clinical testing in humans.

View Full Project Description
Faculty Supervisor:

Alasdair Barr

Student:

Partner:

Cannevert Therapeutics Ltd

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Develop integrated management of bacterial canker disease for greenhouse tomato

Greenhouse industry is an important agricultural sector in Canada. Approximately half of the Canadian vegetables is produced in commercial greenhouses. Ontario greenhouse industry contributes to 40% of greenhouse production in Canada. As one of the most important greenhouse crops, tomato production is threatened by canker disease leading to significant loss for growers. Tomato canker disease is caused by Clavibacter michiganensis subsp. michiganensis (Cmm), a Gram-positive bacterium. This is a very difficult plant disease to eradicate or manage. In this proposal, the academic supervisor Dr. Ze-Chun Yuan and the participating intern will work closely with Ontario Greenhouse Vegetable Growers (OGVG, the partner organization) to develop integrated strategies based on natural chemicals and biological controls to reduce and manage tomato canker disease. The proposed research may also help improve tomato production and quality, nutritional value and flavor, thereby enhancing the market value and profit/revenue for greenhouse growers in Ontario and Canada.

View Full Project Description
Faculty Supervisor:

Ze-Chun Yuan

Student:

Partner:

Ontario Greenhouse Vegetable Growers

Discipline:

Life Sciences

Sector:

Agriculture; Other services (except public administration)

University:

Western University

Program:

Accelerate

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