Innovative Projects Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Validating and improving predictive models using spectral reflectance measurements for the estimation of Methylene Blue Index of soft tailings

Annually, large number of tailings samples are collected by operators and sent to laboratories for measurement of Methylene Blue Index (MBI). This procedure is costly, time-consuming, and results are a function of the methods used and personnel expertise. In prior research we developed predictive models for the quick and consistent estimation of tailings MBI from hyperspectral measurements using a limited number of dry samples. The proposed research focuses on assessment of the robustness of the established models to tailings composition and adapting the spectral models to be applicable on saturated tailings. This would enable the industrial partners to quickly estimate MBI in a wide range of tailings observation conditions including on-site and in-situ on saturated samples and could significantly reduce the costs and inconsistencies associated with laboratory measurements.

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Faculty Supervisor:

Benoit Rivard

Student:

Iman Entezari

Partner:

Suncor Energy Inc.

Discipline:

Geography / Geology / Earth science

Sector:

Oil and gas

University:

Program:

Accelerate

Analysis of Waste Heat Boilers using Computational Multiphysics

Waste heat boilers provide an important function in many industries, taking hot process flows and cooling them down while at the same time creating valuable steam which can be used to save power in other parts of the plant. This project will use Computational Multiphysics Simulations (CMS) to model the inner workings of these important boilers. CMS uses a mix of theoretical and experimental equations to model real world fluids, particularly how they move, boil, and spread heat. CMS field has seen major advances and adoption in many industries in the past decades helping to make more fuel efficient cars, aeroplanes, electronics, and now in our case, waste heat boilers. These more efficient systems help reduce both costs for the consumer and the carbon footprint of the goods produced, benefiting our wallets and environment.

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Faculty Supervisor:

Nasser Mohieddin Abukhdeir

Student:

Victor Guiguer

Partner:

Industrial Ceramics Limited

Discipline:

Engineering - chemical / biological

Sector:

Advanced manufacturing

University:

Program:

Accelerate

Sustainability Planning and Performance Assessment in the District of North Vancouver

The Centre for Sustainable Development at Simon Fraser University is a leader in sustainable development theory and practice. The Centre conducts sustainable development research in BC and worldwide; carries out sustainable development projects in partnership with communities and agencies, and facilitates effeicient use of university resources in responding to requests for assistance on sustainable development issues. The North Shore Community Foundation envisions a healthy and vital community with enhanced quality of life for all. The main objective of this project is to help achieve this vision by assessing the sustainability of the District of North Vancouver and assisting the Foundation, the District, and citizens in making decisions grounded in sustainability and long-range planning. The North Shore Community Foundation will be provided with a customized sustainability performance framework that will guide the community on its path toward sustainability.

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Faculty Supervisor:

Mark Roseland

Student:

Danny Ross

Partner:

North Shore Community Foundation

Discipline:

Environmental sciences

Sector:

Environmental industry

University:

Program:

Accelerate

EARtrode, a wireless in-ear custom-fitted intelligent brain computer interface – Year 2

Brain-computer interfaces (BCI) can directly translate human intentions into discrete commands, bypassing the motor system. Most non-invasive BCI systems currently in use are based on electroencephalography (EEG) recording technology. While traditional EEG-based BCIs achieve high information transfer rates, these systems have two major limitations. First, they cannot be used in daily life as they do not tolerate natural movements. Second, the equipment, a cap or headband and electrodes, would be inadequate for social settings. Thus, the goal of this project is to develop a wireless EEG-based BCI system able to both tolerate natural movement and record brain signals using miniaturized electrodes placed unobtrusively in and around the ear. The specific goals of this project include the adaptation of existing in-ear EEG device to fulfill the functional requirements of the project, the validation of the quality of the EEG signals recorded and the design of the new paradigms for real-time experimentation.

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Faculty Supervisor:

Jérémie Voix

Student:

Olivier Valentin

Partner:

EERS Technologies 4.0 Inc

Discipline:

Engineering - mechanical

Sector:

Medical devices

University:

Program:

Elevate

Radio Acoustical Virtual Environment: from Lab to Field – Year 2

In a world that is getting noisier and as more people are at risk of noise-induced hearing loss the NSERC-EERS industrial research chair in in-ear technologies (CRITIAS) and its industrial partner EERS, have joined forces to address the existing issues in hearing protection devices (HPD). Difficulties in communication is the most prevalent reason why HPDs are not worn in noisy environments. The goal of this project is to enhance communication for talkers wearing HPDs in noise. This is done by capturing speech from inside the occluded ear, denoising it and extending its frequency bandwidth. Once enhanced, the speech signal is sent to listeners within a spatial range of a talker. This range is determined by monitoring the vocal effort of the talker and the level of background noise. Such a Radio Acoustical Virtual Environment enhances the quality of communication in noise and encourages the continuous use of HPDs in noise.

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Faculty Supervisor:

Jérémie Voix

Student:

Rachel Bouserhal

Partner:

EERS Technologies 4.0 Inc

Discipline:

Engineering - mechanical

Sector:

Information and communications technologies

University:

Program:

Elevate

Business Technology Management (BTM) Body of Knowledge (BOK)

Business Technology Management (BTM) is a rapidly emerging trans-disciplinary research area and professional discipline in Business Administration. It seeks to provide an integrated framework for the strategic use of Information and Communication Technology (ICT) and the digital transformation of organizations. This research project will develop the first BTM Body of Knowledge (BOK) and provide a systematic, exhaustive, and evolving framework for professional practice standards. An innovative Semantic Web application will be developed to enable a highly structured and well-indexed contents. It will help make BTM job knowledge easily accessible, customizable, and reusable for decision-making by professionals, employers, higher education, and other associations involved with IT-related standards, certification, and accreditation.

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Faculty Supervisor:

Stéphane Gagnon

Student:

Sylvia Andriamaharosoa, Jamal Ghebli, Shankar Iyer, Issam Talha, Beatriz Torres, Miloud Eloumri, Peiwen Gao, Moufid Jarada, Guillaume Marquis, Lily Murariu

Partner:

Information Technology Association of Canada

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Program:

Accelerate

Data-driven Innovation for the Supply Chain and Retail Industry

The project is a partnership between Polytechnique Montréal, HEC Montréal, UQAM and JDA Canada. JDA Labs is investigating new approaches to help incorporate “big data” science and analytics into everyday supply chain decisions. It relies on new approaches that employ sensor technologies, new analytic capabilities and simulation techniques to not just sense and respond, but anticipate and act by making complex decisions while decreasing the risk exposure. The project benefits are strengthening the agility to support the customer, reducing the cost of poor quality and delivering superior customer service while reducing the dependency on inventory to help maintain the competitive edge.

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Faculty Supervisor:

Yossiri Adulyasak, Jean-Francois Cordeau, Louis-Martin Rousseau

Student:

Pierre Cournut, Amira Dems, Simon Thevenin

Partner:

JDA Software

Discipline:

Mathematics

Sector:

Information and communications technologies

University:

Program:

Accelerate

Combining Internet of Things (IoT) technologies to understand product and consumer behavior in retail environments

The project is about developing a «smart store» system that will allow understanding customer and product behavior. This system will be based on Internet of Things (IoT) technologies allowing any object (product or person) to communicate automatically with its environment. Hence, our system will be used for tracking items and monitor consumer behavior in real time. In a retail environment, we will be able to answer questions such as (i) How many times an item has been picked up or tried by a customer? (ii) How long the item stayed off the shelve? (iii) How long the customer stayed in a specific zone? Near a specific shelve? (iv)What are the most/less visited zones?

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Faculty Supervisor:

Ygal Bendavid

Student:

Samad Rostampour

Partner:

9266-5777 Québec Inc

Discipline:

Business

Sector:

Information and communications technologies

University:

Program:

Accelerate

Quantifying the value added by the first large ensemble of high-resolution climate-change simulations over Québec

Regional Climate Models (RCMs) allow generating climate-change projections into the future over a limited region of the globe at high spatial resolution. The production of large ensembles of simulations from a same RCM is an emerging field of research allowing to explore in detail the interaction between climate change, natural climate variability and extreme events, at the local scale where climate impacts occur. This project takes advantage of the first high-resolution large ensemble over Québec that was recently produced by Ouranos in the scope of the Québec-Bavarian collaborative ClimEx project (www.climex-project.org). This research will address the question of ?added value? by high-resolution large ensembles compared to lower-resolution smaller ensembles in order to guide Ouranos’ partners and other climate data users on how to best integrate such a dataset into the climate-change impacts and adaptation framework.

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Faculty Supervisor:

Rene Laprise

Student:

Moussa Bopp

Partner:

Ouranos Inc

Discipline:

Geography / Geology / Earth science

Sector:

Environmental industry

University:

Program:

Accelerate

Historical reconstruction of long-term forest dynamics in southern Quebec to improve sustainable forest management

European colonization and industrial development have profoundly transformed the forested landscapes of north-eastern North America. Consequently, historical forest characteristics, such as forests prior to settlement and industrial exploitation (i.e. the presettlement forests), serve as a model for developing a sustainable forest management. In this project, we aim to reconstruct long-term changes in forest landscapes of southern Quebec. Early land-survey archives are logbooks reporting the original survey of townships mostly surveyed throughout the XIXth century and which contain highly valuable information about forest composition for this period. These data will be used to reconstruct presettlement forest landscapes. Additionally, paleoecological data from lake cores (e.g. pollen records) will be used to assess millennial changes in forest vegetation. This research project will provide key knowledge to improve sustainable management of southern Quebec’s forests to the partner organization (TEMBEC inc. forest product company) and to other actors from the private and public sectors.

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Faculty Supervisor:

Olivier Blarquez, Yves Bergeron

Student:

Léa Peter, Victor Danneyrolles

Partner:

Tembec Inc.

Discipline:

Geography / Geology / Earth science

Sector:

Forestry

University:

Program:

Accelerate

Développement d’un outil d’analyse technico-économique des modes de restauration et évaluation de l’impact de la végétation sur le bilan d’eau des digues en stériles miniers du parc à résidus de la mine Canadian Malartica

Les mines à ciel ouvert produisent une importante quantité de rejets accumulés sur le site minier en période d?exploitation. Une fois les activités de la mine terminées, le site doit être restauré de manière à ne plus générer de contamination et à être remis dans un état visuellement acceptable. Afin d?assurer une restauration efficace des aires d?accumulation des rejets miniers, la mine Canadian Malartic teste directement sur son site, depuis quelques années, diverses méthodes de restauration pouvant être utilisées. Le stage réalisé sera une combinaison de 2 sous-projets : développer un outil d?analyse technico-économique des méthodes de restauration considérées et/ou testées par la mine Canadian Malartic et faire le suivi de cellules expérimentales mise en place pour évaluer l?effet de la revégétalisation sur le bilan hydrique d?une des aire d?accumulation de rejets à restaurer. 

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Faculty Supervisor:

Bruno Bussière

Student:

Nathalie Chevé

Partner:

Mine Canadian Malartic

Discipline:

Environmental sciences

Sector:

Mining and quarrying

University:

Program:

Accelerate

Genetic evaluation of sow efficiency traits using single step genomic evaluation methods – Year 2

Most economically important traits associated with lactation and reproduction in pigs are either less heritable, sex-limited, expressed later in life, or difficult to measure on a routine basis. Genomic predictions using single step best linear unbiased prediction (SSBLUP) methodologies, which utilizes information on phenotypes, pedigree and markers from genotyped and non-genotyped animals simultaneously, is an alternative to phenotype and pedigree based (BLUP) methods. The goal of this project is to develop genome enhanced estimated breeding values (EBVs) for sow reproductive traits using single step methodologies. The objectives are to 1) develop single step EBVs for sow traits associated with lactation and reproduction 2) to estimate the accuracies of prediction using SSBLUP and compare it with the pedigree based estimates and 3) to incorporate single step methodologies into routine genetic evaluations. The overall outcome is to demonstrate and integrate SSBLUP genomic selection methodologies to improve key economic reproductive traits.

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Faculty Supervisor:

Graham Plastow

Student:

Dinesh Moorkattukara Thekkoot

Partner:

Genesus Inc.

Discipline:

Agriculture

Sector:

Agriculture

University:

Program:

Elevate

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