Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Caractérisation de levures pour la production de bière faible en alcool et leur capacité à promouvoir la réduction des aldéhydes.

Les bières faibles en alcool ont souvent un goût de moût résiduel. Ce goût est causé par certains aldéhydes; des molécules qui proviennent du brassage de la bière et du touraillage du grain. Heureusement, durant la fermentation, ces aldéhydes peuvent être transformés en molécules aux arômes agréables. Ce projet s’intéresse aux différents facteurs qui peuvent maximiser cette transformation. En premier lieu, les pouvoirs réducteurs de différentes levures seront comparés. En second lieu, les conditions de fermentation seront modifiées afin de mieux comprendre la transformation des aldéhydes et les flaveurs qui en résultent. En dernier lieu, une étude qualitative sera menée sur les bières produites lors du projet. Mieux comprendre les interactions des levures et des aldéhydes et trouver des moyens de réduire leur concentration dans la bière aidera Lallemand à améliorer ses produits et développer de meilleures pratiques pour leur application.

View Full Project Description
Faculty Supervisor:

Alexandre Drouin;Luc Gaudreau

Student:

Partner:

Lallemand Bio Ingredients

Discipline:

Life Sciences

Sector:

Agriculture and Food; Biotechnology; Life Sciences (not health)

University:

Bishop's University

Program:

Accelerate

Design and Development of a Novel Web Application for Enhanced User Experience of Digital Books

The research project collaboration between APCI and WIMTACH will involve the identification of best technology methods and processes that will enable new modes of publishing to bridge the gap between the traditional paper and online methods. The focus will be on the efficiency of delivery so that cost models are minimized, opening new opportunities for authors, including those from disadvantaged communities, to publish novel material. The student intern will learn first hand experience on these new technologies and its applications to the current APCI platform. On the other hand, APCI will be able to bring their product to market and generate revenue, as well as, increase employment for the company.

View Full Project Description
Faculty Supervisor:

Angamuthu Tiruchengode Vijayalakshmi

Student:

Partner:

Applied Program Consulting Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Centennial College of Applied Arts and Technology

Program:

Accelerate

Prédiction intelligente des défaillances dans les structures mécaniques et procédés

L’une des orientations majeures de la quatrième révolution industrielle est de rendre intelligents les systèmes de contrôle des structures et des processus industriels, par l’intégration de capteurs au cœur du procédé. L’installation d’un nombre considérable de capteurs à travers les endroits les plus à risque a permis d’obtenir des bases de données, structurées, massives et hétérogènes. Par conséquent, les stratégies de collecte de données, de leurs traitements et d’intervention doivent être continuellement à jour et fiables afin de garantir le meilleur indice de santé des machines et la prédiction la plus précise des modes défaillances. Ainsi, l’objectif principal de ce programme est le développement d’approches intelligentes d’aide à la prise de décision. Ces approches seront appliquées à des problématiques industrielles propres à chacun des partenaires. La formation du personnel hautement qualifié dans les domaines d’apprentissage automatique, de fiabilité des systèmes mécaniques constitue aussi un des objectifs de ce programme.

View Full Project Description
Faculty Supervisor:

Hatem Mrad;Tikou Belem;Richard Simon

Student:

Partner:

Norda Stelo inc;Beap.ai;Groupe MISA

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Accelerate

Bringing Climate Change Resilience Decision Support to the Greater Victoria 2030 District Buildings and Beyond

The impacts and uncertainty of climate change effects are a challenge to building owners. This project seeks to make it easier for commercial building owners to improve the climate change resilience of their buildings. A tool for supporting decision makers in planning retrofit actions for their buildings will be produced that reflects the local context and the uncertainty. In partnership with BOMA BC the tool will be tested with buildings in the Greater Victoria District 2030 with the goal of creating a tool that can be used by practitioners. This work will serve as a foundation to expand to other local contexts in BC, Canada and the District 2030 network.

View Full Project Description
Faculty Supervisor:

David Bristow

Student:

Partner:

BOMA BC

Discipline:

Engineering

Sector:

Sustainability & the Environment; Commercial Services; Other

University:

University of Victoria

Program:

Accelerate

Development of an effective process with aid of micro-organisms and fungus for reduction of environmentally destructive effect of spill oil toward ocean ecosystem protection.

The risk of an oil spill in the marine environment always exists during offshore oil production and transportation. The oil spill can affect the marine ecosystem, including seabirds, aquatic organisms and even humans health, both directly and indirectly. The best solution to the oil spill incident is collecting the spilled oil, extracting that from the marine environment and potentially taking it back to the energy cycle. However, depending on the situation and severity of the oil spill incident, it can be partially possible or even impossible. The hydrocarbon degradation using microorganisms is a crucial step toward sustainable spill oil treatment and minimizing the spill oil footprint. This study aims to screen and select effective indigenous microorganisms such as bacteria and fungus that can decompose all types of hydrocarbon substances in crude oil.

View Full Project Description
Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Oil and Gas; Sustainability & the Environment; Biotechnology

University:

Memorial University of Newfoundland

Program:

Accelerate

Design and optimization of low-frequency piezoelectric energy harvesters

Portable electronic applications are typically powered by batteries, which have limited lifespan and size constraints. Energy harvesting from the spatial environment is a promising solution to sustainable power supplies for low-power portable devices and sensor networks. Vibration-based energy harvesting has received much attention due to the recent advances in microfabrication of piezoceramic materials. These smart materials can convert mechanical parasitic vibrations to electric charge through the direct piezoelectric effect. The resulting energy can be extracted after using an interface circuit. We propose a novel wideband piezoelectric energy harvester that can be used as a long-term reliable electrical power supply for small electronic devices based on the low-frequency nature of environmental vibrations (e.g., wind, ocean waves). Therefore, the proposed energy harvester in this research has a lot of potential to be commercialized and deployed in inaccessible regions, like offshore and deep marine environments.

View Full Project Description
Faculty Supervisor:

Lihong Zhang;Mohammad Al Janaideh

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Environmental Science and Technology; Clean Technology; Ocean Tech

University:

Memorial University of Newfoundland

Program:

Accelerate

lnfluence of odour presentation on panelist response variability

Olfactometry is the science of using human subjects to measure odours without bias, as no instrument yet can replace the human nose. Recently, the method presenting odours to panellists has been identified as a potential element affecting response and measurement variability. Furthermore, the sensitivity of electronic noses also developed to measure odours remains an issue. The objective of the research is to use 3 odours and present them in 3 different ways to 6 panellists, and compare panelists’ response to that of two widely used commercial noses. The experimental work will beconducted in the olfactory laboratory of Consumaj Inc. in St-Hyacinthe. TOBECONT’D

View Full Project Description
Faculty Supervisor:

Catherine Mulligan

Student:

Partner:

Consumaj Inc

Discipline:

Engineering

Sector:

Technology

University:

Concordia University

Program:

Accelerate

Sustainable functionalized magnetic particles for efficient treatment of marine oil pollution

Oily wastewater production and discharge from different sources such as industries and daily human activities are the main sources of marine oil pollution. More importantly, accidental oil spills occurred in oil extraction/production, refining, and transportation stages can cause detrimental impacts on the aquatic ecosystems and marine environments. In this Lab2Market project, we apply a special coating solution provide a proper dispersibility aqueous/continuous in various environments to optimize the adsorption performance by considering all affective physiochemical variables to be improved for on-site purposes.

View Full Project Description
Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Water; Environmental Science and Technology

University:

Memorial University of Newfoundland

Program:

Accelerate

Approche autonome pour la cartographie des réseaux urbains souterrains

Le géoradar (GPR) est une technique électromagnétique (EM) pour l’imagerie non invasive de supports opaques, souvent utilisé pour les levés souterrains. Le traitement des données GPR, surtout dans des zones urbaines souterraines, repose sur des opérateurs qualifiés et implique de nombreuses étapes coûteuses. Les résultats sont souvent basés sur de larges hypothèses et impliquent une intervention humaine, source parfois d’incohérence et de biais subjectif, ce qui rend les résultats peu fiables.
Ce projet justifie et vise à développer, un nouveau classifieur basé sur un réseau de neurones, pour détecter et interpréter automatiquement les signaux en vue de la localisation et les orientations des infrastructures souterrains. La causalité entre les services publics souterrains et leurs signatures GPR sera étudiée. En plus, il permettra de développer une expertise dans le domaine de cartographie des réseaux souterrains. Ceci permettra à Groupe ABS de développer son avantage concurrentiel.

View Full Project Description
Faculty Supervisor:

Gabriel J Assaf

Student:

Partner:

Groupe ABS inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

AK Platform – Soft skills learning as a key resource for faster job placement

Canada, a country composed presently of 20 percentage of immigrants, aims to be a world leader in global problem-solving. To do so, and to draw from the insights and ingenuity of the immigrant population, requires that Canadian organizations develop faster and more effective ways of adapting newcomers into the labor market. Especially, as extant research has found, that skilled immigrant workers are presently constrained within the labor market and this restricts Canadian organizational performance and curtails Canada’s competitiveness. Identifying the key soft skills needed in the Canadian labor market and finding innovative ways to pass this knowledge on is fundamental not only to reduce the length of time for immigrants and international students to adapt to Canadian culture but to also improve Canadian economic performance. This research project aims to review Canadian literature and academic publications containing soft skills analysis focusing on professional experiences in the Canadian Labor market for the last decade to identify the most coveted soft skills. The research will be conducted by a secondary research analysis systematic methodology with procedural and evaluative steps.

View Full Project Description
Faculty Supervisor:

Barry Wright

Student:

Partner:

Loonie AK

Discipline:

Sociology

Sector:

Education

University:

Brock University

Program:

Accelerate

Improved Deep Learning-based Sea-ice Monitoring System

This project will develop a robust software package that can be embedded with a camera system to provide an onboard sea-ice monitoring system. The software package consists of two main components: (1) Deep learning classification model, which involves a deep learning network trained to identify and classify sea-ice; (2) Lens artifact removal method, which is a set of morphological operations that remove any lens artifacts, which can be water droplets, particles, or objects on the camera lens obstructing the studied scene. This software package obtains the scene information in-situ, which is important for real-time sea-ice monitoring systems and enables the vessels to safely maneuver in such harsh icy water environments.

View Full Project Description
Faculty Supervisor:

Octavia Dobre

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Computer science

Sector:

Artificial Intelligence; Ocean Tech; Technology

University:

Memorial University of Newfoundland

Program:

Accelerate

Use of Artificial Neural Networks for Predicting the Offshore Wind Turbine Power Curve Using Various Training Algorithms in Newfoundland

Low predictive accuracy of energy output is one of the weakest points in wind power generation. Power curve of a wind turbine provides assistance in energy assessment, warranty formulations, and performance monitoring of the wind turbines. Wind turbines are being installed in offshore diverse climatic conditions causing substantial departure of these power curves from the warranted values. As industrial organizations being managed by enterprise-wide systems, a software like solution for the prediction of wind farm power output is desirable. The proposed wind farm performance prediction models should be able to forecast the amount of energy produced on different time scales such as 10 min, 1 hour and a day. Such prediction models would transform a wind farm into a wind power plant. Artificial Neural Network is such model that has been used in this study to accurately forecast the power output of a proposed offshore wind farm.

View Full Project Description
Faculty Supervisor:

Jianming James Yang

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Green/Alternative Energy; Clean Technology; Artificial Intelligence

University:

Memorial University of Newfoundland

Program:

Accelerate

Previous
1…1,5091,5101,5111,5121,5131,5141,515…2,473
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe