Innovative Projects Realized

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

30156 Completed Projects

2861
AB
5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
NS

Projects by Category

A Study on the Effectiveness of Computer Vision Models for Addressing Environmental Problems Using UAVs and USVs

The research project, guided by Professor Stephen Smith, focuses on addressing environmental challenges related to water pollution and debris detection in the water areas, with a specific emphasis on garbage and waste detection on the water surface. The project entails a systematic literature review and analysis of various computer vision models to detect and classify garbage, which involves processing raw data from sensors on board aerial vehicles. Additionally, the project investigates how to plan the motion of the aerial vehicles over a body of water to detect and monitor garbage’s subsequent motion. The research will attempt to propose a new algorithm or modify an existing algorithm for more accurate waste detection in the water using computer vision techniques. While the project does not involve the direct use of unmanned aerial vehicles or unmanned surface vehicles, the intern will conduct a thorough investigation of their potential implementation in environmental monitoring. The expected outcomes of the project are generating insights into the effectiveness of computer vision models for environmental monitoring and management, and identifying potential applications for future research.

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Faculty Supervisor:

Stephen Smith

Student:

Partner:

Kharkiv National University of Economics

Discipline:

Computer science

Sector:

Artificial Intelligence; Sustainability & the Environment; Environmental Science and Technology

University:

University of Waterloo

Program:

Globalink Research Award

Establishing Travel Needs of Older Adults

Many older adults in Canada are becoming increasingly isolated from their communities. This is largely due to
the fact that Canadian cities are built with cars in mind, and many older adults rely heavily on driving to get
around. However, as they age and lose their ability to drive, many older adults often are unable to travel as
much as they used to, which greatly limits their activities and social interactions.
Unfortunately, there aren’t many good alternatives for older adults who can no longer drive. Public transportation
is often not very reliable or convenient, and walking or biking long distances can be difficult or unsafe. Taxis are
often too expensive to use on a regular basis, so many older adults end up relying on family and friends to give
them rides. This can be inconvenient, and it may make them feel like a burden on others.
To help combat this problem, it’s important to ensure that older adults can easily access important services and
amenities in their communities. However, this requires better transportation options that are specifically tailored
to the needs of older adults. To achieve this, we need to better understand what these needs are. This research
will be the first to study the transportation needs of older adults

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Faculty Supervisor:

Ajay Agarwal

Student:

Partner:

City of Kingston

Discipline:

Sociology

Sector:

Public administration

University:

Queen's University

Program:

Accelerate

Ai-based musical intervention to improve emotion through a personalized speaker

Mental disorders have a significant influence on the daily activities of Canadians. Musical intervention can provide a non-invasive treatment through changing emotional state and creating positive mood. The main objective of this project is to provide a long-term solution for musical intervention through an optimized machine learning framework for an intelligent real-time emotion recognition and musical intervention system integrated in an empathetic speaker. During music play, the emotional influence will be detected and according to the mood change measured from the brain signals, the music database will be customized. This project in partnership with Pi-Electronics, a leading company in acoustic technology with an extensive portfolio of advanced audio-visual electronic initiatives, is expected to achieve remarkable industrial benefits for musical intervention using smart speakers. Ultimately, it will provide a low-cost and low-risk solution to improve the subjective well-being and consequently quality of life for Canadians and worldwide users.

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Faculty Supervisor:

Soodeh Nikan;Abdallah Shami

Student:

Partner:

Pi Electronics Technology Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

The University of Western Ontario

Program:

Accelerate

Using analytic hierarchy processes to resolve multi-criteria decision making

Many real life decision consider a multitude of criteria, one such example is in healthcare where the patient’s condition, available resources, chance of recovery, cost etc all need to be consider when administrating care. An analytic hierarchy process makes the multi-criteria decisions by first converting the problem into a set of mathematical constraints by pair-wise comparing the importances of the constraints. This project aims to optimize this approach as well as uncover its convergence properties. The expected outcomes are for a more efficient algorithm.

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Faculty Supervisor:

Arthur Chan

Student:

Partner:

Osaka University

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Forecasting Vehicle Maintenance Needs and Breakdowns using Predictive Maintenance

Improving road safety has a direct impact on the lives of drivers as well as the costs incurred by companies operating commercial vehicles. One important aspect of road safety is timely and effective vehicle maintenance. By forecasting vehicle maintenance needs and predicting breakdowns before they occur, valuable insights can be provided to drivers and fleet managers ahead of time. This information allows them to make informed decisions on when to perform vehicle maintenance and avoid accidents arising from unexpected vehicle breakdowns while on the road. The goal of this project is to take advantage of Geotab’s data collected from more than 2 million connected vehicles to develop and evaluate models for forecasting vehicle maintenance needs and predicting malfunctions. The output of this project will be of value to Geotab’s customers, as well as to the wider community in understanding patterns for vehicle malfunctions and reducing accidents arising from them.

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Faculty Supervisor:

Andrei Badescu

Student:

Partner:

Geotab Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

University:

University of Toronto

Program:

Accelerate

Contact-Rich Visuotactile Manipulation

Robotic manipulation involving contact-rich tasks continues to be a challenging, yet critically important, research problem with many potential applications, including domestic assistance, automated agriculture, and advanced manufacturing. Many of these tasks involve both unstructured environments and complicated dexterous manipulation. Existing approaches that rely on purely visual sensors and predefined models are brittle and prone to failure. This research project will investigate how tactile sensing can provide a sense of touch to robot manipulators so that they can handle more difficult tasks.

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Faculty Supervisor:

Jonathan Kelly

Student:

Partner:

Samsung Electronics Canada

Discipline:

Computer science

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

A Machine Learning Framework for Exploring Mortality in Developing Countries with Verbal Autopsies

This research project, backed by Unity Health Toronto and the Centre for Global Health Research (CGHR), aims to explore the use of machine learning in predicting causes of death using verbal autopsy data from low-to-middle-income countries. Verbal autopsy is a cost-effective and efficient method for documenting deaths in regions with limited resources. By employing advanced analytics and artificial intelligence, this project seeks to improve the accuracy of determining causes of death, quickly identifying disease patterns and trends, which can ultimately improve public health policies, strategies, and preparedness. The success of this research is expected to strengthen Unity Health Toronto’s reputation as an innovator in global health research, enrich epidemiological understanding, and foster collaborations with global experts. Ultimately, the findings will benefit healthcare professionals, patient care, and contribute to the resilience of Canada’s healthcare system.

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Faculty Supervisor:

Frank Rudzicz

Student:

Partner:

Unity Health Toronto

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

University of Toronto

Program:

Accelerate

Olivia Xu – Ethics First: Fostering Social Responsibility in AI Development and Deployment through Intercultural and Interdisciplinary Collaboration

The proposed project aims to address ethical challenges associated with AI technologies by researching and promoting intercultural and interdisciplinary collaboration. This intercultural and interdisciplinary collaboration entails drawing insights from people who come from different cultural backgrounds, study different disciplines (engineering, philosophy, sociology, law, etc) and work in different sectors (industry, academia, non-profit, etc). With the goal of ensuring AI technologies and innovations are developed and applied in a way that is both responsible and socially beneficial, this project will help bring Canada’s critical technology sector (AI) to the forefront of a sustainable and equitable future economy.

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Faculty Supervisor:

Christian Muise

Student:

Partner:

Cansbridge Fellowship

Discipline:

Computer science

Sector:

Education; Other services (except public administration)

University:

Queen's University

Program:

Business Strategy Internship

Prototyping, validation, and optimization of an innovative solar-air heating system for window applications (Phase 2)

The increased pressure of natural resource depletion and environmental issues have largely promoted the search for renewable energy sources such as solar energy. Solar heating systems that use air or fluid to transfer the heat energy from solar irradiation to the indoor environment have surfaced as green solutions with high energy conversion efficiency (70%). However, current solar thermal applications have not yet targeted residential and commercial window applications, although these contribute to the largest portion of heat loss in buildings. With the aim of developing more energy-efficient solar-thermo products, Innovative North and University of Guelph collaborated to develop a novel solar air heating system through a Mitacs BSI-funded project (Phase 1). In the Phase 1 project, we successfully designed and optimized the heating system regarding the geometry and sizing, operation mechanism, air ducting system, and manufacturing processes. Through the Phase 1 project, a digital design model with a bill of materials was created. Since the heating system is highly interdisciplinary, a physical prototype is crucial for studying the mechanical, electrical, and manufacturing feasibility.

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Faculty Supervisor:

Sheng Yang

Student:

Partner:

Innovative North

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Guelph

Program:

Business Strategy Internship

PaceZero BSI 2023

PaceZero – Impact Due Diligence Framework Development. This project will further develop an Impact Due Diligence process map for Impact measurement analysis.

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Faculty Supervisor:

Norah McRae

Student:

Partner:

PaceZero Capital Partners

Discipline:

Business

Sector:

Finance and Insurance

University:

University of Waterloo

Program:

Business Strategy Internship

E-Commerce Regional Expansion and Fulfillment Innovation

The Partner Organization produces and sells an all-natural caffeinated energy drink, with about 1/3 of business direct to consumer through their ecommerce website. The organization has a planned expansion into Ontario and Quebec but no social media content generation capabilies or documented marketing strategy to support this expansion. Additionally, the product is heavy and is at risk of freezing in the winter, and the organization is seeing an increased number of damaged shipments for which the courier is not approving claims citing improper packaging as the reason. The goal of the project is to address these two areas.

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Faculty Supervisor:

Amy MacDonald

Student:

Partner:

Work Water Inc.

Discipline:

Business

Sector:

Manufacturing

University:

New Brunswick Community College

Program:

Business Strategy Internship

Adam Trotman – Studying the cross-applications of mining tailings and developing a strategy on how they can drive economic growth through commercialization

The project will investigate the cross applications of mining tailings and how they can drive economic growth.

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Faculty Supervisor:

Sandy Staples

Student:

Partner:

Cansbridge Fellowship

Discipline:

Business

Sector:

Education; Other services (except public administration)

University:

Queen's University

Program:

Business Strategy Internship

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