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

Deep Learning for Acoustic-based Pipe Leak Detection

Current leak detection methods for water pipelines, such as fixed acoustic devices and Pipeline Inspection Gadgets (PIGs), require shutting off the water supply and are often impractical for field inspections. These methods demand extensive workforce and time and often fail to detect smaller leaks effectively, leading to significant water loss, increased operational costs, and potential infrastructure damage. XK Innovate Inc., a leader in water pipeline technology based in Toronto, Ontario, will collaborate with UBC Okanagan to develop a groundbreaking in-service water pipe leak detection system. This project introduces the HZ1 Free-Swimming Device, advanced deep learning models, and an intuitive Graphical User Interface (GUI) to detect leaks without disrupting the water supply. This innovative solution aims to reduce workforce requirements, operational costs, and water loss by enhancing accuracy and efficiency while fostering Canadian economic growth and public welfare. The project aligns with Canada’s innovation and workforce development policies and supports sustainable development by minimizing environmental impact and resource consumption. Additionally, it offers an invaluable opportunity for an intern to gain practical experience in data analytics, systems engineering, and environmental technology, equipping them with competitive skills for the job market.

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Faculty Supervisor:

Zheng Liu

Student:

Partner:

XK Innovate, Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Research and Development of an AI based Software to Recognize Realtime TV Commercials on Low-power Computing Equipment

This research will explore the possible use of video analysis, object detection, and machine learning models to identify TV commercials and advertisements in real-time on low-power computer systems. The partner organization focuses on software development and advertisement technology. The partner aims to solve the challenge of developing a lightweight power-efficient AI-based software that would be able to identify TV commercials or other advertisements in live video feeds in real time. This technology will help the company identify and quantify advertisements for tracking purposes. The interns would work on categorizing advertisement data, optimizing the system, and identifying key characteristics associated with TV commercials transitions.

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Faculty Supervisor:

Michael Guerzhoy

Student:

Partner:

Smart CashBackTV

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

An exploratory investigation of Geographic Information Systems (GIS) applications to support the Vietnam Cleaner Production Centre’s sustainable Pangasius bocourti (Basa Fish) industry project

This research project will explore how a Geographic Information System (GIS) analysis can aid in enhancing the sustainable Basa fish industry in Vietnam. Enhancement is achieved through increasing market value, reducing the impact on global seafood supply chains and reducing negative local environmental impacts. GIS is an application that allows for complex spatial analysis of large quantities of data, some of its frequent uses are to:
1. Determine optimal locations for: service centres, businesses based on demand, resource extraction industries, forestry or hydrology studies etc.
2. Create market segment analyses based upon locations, customer preferences or product preferences.
3. Create and implement models to predict future growth, demand, or environmental impacts.
The goal is to determine how a GIS application can help build the capacity of ongoing VNCPC and Hanoi University of Science and Technology work to improve the Basa fish industry in Vietnam. The expected outcomes of the research project are that GIS analysis will be used by VNCPC for network and point-based analyses to contribute to a sustainable Basa fish industry in Vietnam

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Faculty Supervisor:

Su-Yin Tan

Student:

Partner:

Hanoi University of Science and Technology

Discipline:

Computer science

Sector:

Education

University:

University of Waterloo

Program:

Globalink Research Award

Remote Video Surveillance using LEO Satellites Communications

Video surveillance systems have rapidly expanded, driven by their critical roles in security and traffic monitoring. This expansion has produced vast data volumes, causing bottlenecks in communication systems due to the time-sensitive and bandwidth-intensive nature of surveillance data. To address these challenges, research has increasingly focused on developing algorithms to compress redundant data effectively, evolving from traditional methods to advanced neural video compression techniques. These methods aim to transmit minimal data without sacrificing quality. Our approach utilizes the semantic communication paradigm, emphasizing the transmission of data’s meaning rather than the data itself, to enhance efficiency in low-bandwidth environments. We propose a semantic compression framework specifically for video surveillance that employs novel object detection models and varying levels of semantic abstraction. This framework is designed to convert surveillance footage into compact, meaningful representations, optimizing data transmission in scenarios like remote surveillance via satellite.

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Faculty Supervisor:

Lokman Sboui

Student:

Partner:

École Supérieure Privée d'Ingénierie et de Technologies (ESPRIT)

Discipline:

Engineering

Sector:

Information and Communications Technology; Artificial Intelligence; Environmental Science and Technology

University:

École de technologie supérieure

Program:

Globalink Research Award

CO24-150-ICESI1

This internship, in collaboration with the Public Actions Group of ICESI University (GAPI), focuses on the critical study of climate change’s impact on human migration and human rights. Our investigation will cover seven key topics: natural phenomena driving human mobility, the effects of climate-induced migration on human rights, the vulnerabilities of migrating groups, livelihood losses due to climate changes, environmental policies, climate litigation, and measures to mitigate environmental damage to populations. We aim to explore the relationships between climate change, human mobility and human rights focusing on three primary objectives: analyzing the impact of climate change on human mobility, assessing human rights violations among environmental migrants, and identifying effective protection policies. In addition to its regional focus, this research also seeks to draw broader lessons that can be applied to policies in other countries. The findings from this study will be pertinent to other regions experiencing similar climate-induced migration challenges. By providing a comprehensive understanding of the Latin American context, the research will offer valuable insights that can inform global policy discussions on environmental migration and human rights.

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Faculty Supervisor:

Yvonne Su

Student:

Partner:

Universidad ICESI

Discipline:

Sociology

Sector:

Sustainability & the Environment; Public Service, Policy, and Governance

University:

York University

Program:

Globalink Research Award

Vision-based Maneuver Classification for Autonomous Driving

The proposed research project aims to address the challenge of accurately detecting and classifying complex driving maneuvers in real-world conditions. Partnering with Matt3r Technologies Inc. in Vancouver, BC, this research will develop a deep learning model that uses multiple types of data, such as dashboard video, to achieve maneuver detection for autonomous vehicles. This innovation will enhance the safety and efficiency of Matt3r’s technology, making autonomous vehicles more reliable and safer, while also being cost-effective. The project will boost Matt3r’s technological capabilities, support economic growth, and contribute to public safety in Canada. Additionally, the intern(s) will gain valuable experience in artificial intelligence and machine learning, making them competitive in the job market to serve Canada’s economic growth.

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Faculty Supervisor:

Zheng Liu

Student:

Partner:

Matt3r Technologies Inc.

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program:

Accelerate

optimizing healthcare management using deep learning

Initially within the application procedure for searching appropriate combination of care seeker/giver matches it’s observed that user must select a range of options like the type of health care worker (HCW) needed for the job, credentials they require, their estimated rate, distance from the location desired, choosing level of experience HCW possesses, and checking whether or not they have any expertise for each disease that care is needed for which creates a burden for the customer to to be able to manually filter the search criteria according to their needs. And, the same can hold true for the care workers as well, at least after the initial setup they might need to filter the search criteria for jobs of interest every time based on some of the criteria mentioned above and parameters like healthcare setting, care schedule, care services, employment type, etc. Thus, an efficient optimization algorithm based on ensemble of models can eliminate the need to do manual repetitive tasks, find better combinations based on the need, increase user satisfaction. This approach takes into account that not all the parameters in finding a match have same level of importance. And as a result better care planning leads to less user frustration for both parties involved helping the platform to grow faster.

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Faculty Supervisor:

Russell Butler

Student:

Partner:

WeBookCare

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

Bishop's University

Program:

Accelerate

Ouverture d’un Costco à Rimouski : Assurer des retombées positives pour le secteur bioalimentaire du territoire du Bas-Saint-Laurent

Le détaillant Costco ouvrira une succursale à Rimouski en 2025. Ce projet mesurera les impacts socioéconomiques sur divers groupes d’acteurs du secteur bioalimentaire du territoire de l’installation d’un gros joueur comme Costco dans une région éloignée. Il vise aussi à documenter les pratiques d’approvisionnement de la compagnie et de la succursale à l’aune du développement durable, de l’achat local et de la responsabilité sociale des entreprises.

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Faculty Supervisor:

Laurence Godin

Student:

Partner:

Table de concertation bioalimentaire du Bas-Saint-Laurent

Discipline:

Sociology

Sector:

Agriculture

University:

Université Laval

Program:

Accelerate

Antennas and Lenses for Lunar Mission Applications

This project focuses on revolutionizing space communication through the design and optimization of customized conical horn antennas tailored specifically for space applications. Horn antennas are pivotal in facilitating efficient communication in space, offering unmatched versatility in controlling radiation patterns and providing high efficiency. This project aims to optimize horn antenna geometries and design metrics by employing advanced numerical techniques and optimization algorithms, in order to create antennas that meet the unique demands of space missions. Through meticulous customization of antenna geometry and iterative simulations, we ensure optimal performance, including minimized sidelobes and enhanced radiation pattern stability across frequencies. In addition, we will study and extend the requirements on the horn antennas’ radiation patterns to obtain the desired illumination profiles where and when the horn antenna serves as a spatial feed for other planar antenna arrays in space applications.

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Faculty Supervisor:

Elham Baladi

Student:

Partner:

AEM Antennas Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Optical characterization of 2D functionalized nanomaterials in the gas phase

Graphene is a promising new nanomaterial, single layers of graphite, with superior physical and electrical properties making it an ideal candidate for electrical applications; however, current graphene production methods are expensive and complicated. As a result, new materials that have similar properties to graphene, but are more amenable to high-yield production are currently being investigated. A strong candidate is reduced graphene oxide (rGO), which is synthesized by inserting oxygen into graphite making it easier to separate into single layers and then removing the oxygen to get graphene-like properties. The final rGO has similar properties to graphene; however, when removing the oxygen not all oxygen atoms will be removed and defects may be introduced. This can lead to changes in shape and size greatly affecting the final properties. This makes it crucial to understand the shape and size of any rGO produced, ideally in line with the manufacturing. This project looks to use time-resolved laser-induced incandescence (TiRe-LII). TiRe-LII uses a laser pulse to heat nanoparticles and records the incandescence as the particle cools. This data can be used to infer particle characteristics, size, and shape. This project examines the potential of using TiRe-LII to characterize rGO for in-line measurements.

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Faculty Supervisor:

Kyle Daun

Student:

Partner:

Universität Duisburg-Essen

Discipline:

Engineering

Sector:

Advanced Manufacturing; Nanotechnology; Energy and Utilities; Quantum Science

University:

University of Waterloo

Program:

Globalink Research Award

Stage ESPCI Paris automne 2024

Nous allons faire l’analyse par résonance magnétique nucléaire du solide de bétons contenant du métakaolin (argile calcinée). Il est considéré que le métakaolin pourrait éventuellement remplacer le ciment Portland, dont la fabrication est l’un des principaux contributeurs à l’émission de gaz à effet de serre. Ce stage se fera dans le laboratoire de Science et Ingénierie de la Matière Molle de l’école ESPCI à Paris, qui est une des références dans ce domaine.

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Faculty Supervisor:

Jérôme Claverie

Student:

Partner:

École Supérieure de Physique et de Chimie Industrielles de la Ville de Paris

Discipline:

Physics

Sector:

Education

University:

Université de Sherbrooke

Program:

Globalink Research Award

Maximizing Efficiencies – Identification of Optimization Based Best Practices for Commercial 3d-printing

The research project seeks to understand, model and analyze the potential efficiency impact of additive manufacturing (AM or 3D-printing) on select manufacturing processes. The research will involve identifying, testing and measuring optimization opportunities in current manufacturing processes by combining current best practices and technologies across various AM technology and services, operational research methods and standard data mining techniques. The project seeks to form the foundation for understanding how high quality 3D-printing service bureaus using current AM technologies can impact the manufacturing eco-system. The knowledge gained from this research project will help with continued research to investigate how high quality 3D-printing service bureaus can impact economic development through operational efficiencies across the global manufacturing supply chain.

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Faculty Supervisor:

Matthew Kyan

Student:

Partner:

Think2Thing

Discipline:

Business

Sector:

Manufacturing and Construction; New and Digital Media; Technology

University:

Toronto Metropolitan University

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.