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

The PEACE + FREEDOM Project – Remote Areas Using Hydrogen for Energy Self-Reliance

Remote areas have the world’s highest death rates and cost of operations. As the global community struggles with shared problems including pandemics and climate change, connecting remote areas with the global community is becoming increasingly important.
The current economic model of remote areas is dominated by reliance on oil, yet oil supplies are not reliable in remote areas, with frequent fuel supply shortages, and prices are not predictable and not sustainably affordable. The result is remote areas in most of the world do not have reliable, affordable energy. This is a primary obstacle to connecting remote areas with the global community.
With this need, hydrogen applications appear in transportation, communications, and electricity as an option to allow remote regions to be connected to the benefits of the global community. In this study, specific technical and economic applications of hydrogen will be studied, quantified and analyzed, like simulation model to hydrogen economy for transport and communications systems for remote areas, energy for propulsion systems used in transport, particularly aviation, buoyant Lift for use in airships and aerostats, global trends and prediction models for the economics of oil versus hydrogen and cost comparison (Helium vs hydrogen – Photovoltaic vs Hydrogen).

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Faculty Supervisor:

Loïc Boulon

Student:

Partner:

Solar Ship Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Business Strategy Internship

Enhancing adherence to online PBC wellness programming

Online wellness programming offers a promising avenue to positively influence the mental well-being of older adults with chronic conditions in a manner that is accessible and acceptable. This project aims to build on our collaborative relationship with the Canadian PBC Society to iteratively refine an online wellness program to the unique needs of individuals with primary biliary cholangitis, including strategies such as enhanced social interaction. Additional evaluation will also focus on the program impact on perceived fatigue.

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Faculty Supervisor:

Puneeta Tandon

Student:

Partner:

Canadian PBC Society

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

University of Alberta

Program:

Accelerate

Deep Learning Classification and model compression

Deep neural networks (DNNs) have achieved great success in many visual recognition tasks. However, existing state of the art deep neural network models are computationally expensive and memory intensive, hindering their deployment in devices with low memory resources or in applications with strict latency requirements. Therefore, a natural thought is to perform model compression and acceleration in deep networks without significantly decreasing the model performance. Developing models for inference on clients has multiple economical benefits, but it becomes difficult to match the performance of bigger architectures by simply training smaller architectures. Therefore, we have to look for solutions like Knowledge Distillation, Network Pruning, Quantization to obtain highly efficient models that can match the performance of bigger architectures.

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Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Jumio

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Social and Community Economic Development Planning in Toronto

“Social and Community Economic Development Planning” is a BSI project is comprised of four internships associated with four non-profit partner organizations engaged in organizing, advocacy and planning for affordable housing and community supports in low-income, racialized and marginalized neighborhoods. The shared context for this work is the ongoing gentrification in downtown Toronto , coupled with displacement pressures associated with transit-led redevelopment in suburban regions of the GTA. Two projects entail research that will support the partner in developing community benefits strategies associated with major infrastructure redevelopments. Two focus more explicitly on researching possibilities for supporting the development of community land trusts that could take land off the market in perpetuity and preserve affordability for low-income residents and businesses as well as social enterprises. The partner organizations, who are among Canada’s leading practitioners of community economic development, will benefit from background research to support strategic planning, popular education and engagement of low-income and marginalized constituencies.

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Faculty Supervisor:

Katharine Rankin;Lindsay Stephens;Jason Spicer

Student:

Partner:

Black Urbanism Toronto;North York Community House;Jane/Finch Centre;The Neighbourhood Land Trust

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

University of Toronto

Program:

Business Strategy Internship

Advancement of biosensor technologies for use in healthcare/cancer research and detection

The detection of specific carbohydrates is critical for several processes including biofuel production, textile finishing, food production and human health. These carbohydrates play roles in human health including stem cell differentiation, genetic diseases, and viral infection (i.e., COVID-19). Presently, the largest barrier to understanding the role carbohydrates play in human health is the lack of suitable tools to study them. Biosensors are devices that are used to detect and quantify the concentration of biomolecules or microorganisms. Protein-based biosensors, like those described in this proposal, are composed of one or more fluorescently labelled proteins that interact with a target molecule in solution. The interaction of the target molecule with the biosensor induces a change in the protein, which in turn, alters the position/ environment of the fluorescent dye. This change results in an altered fluorescence output, which can be measured. The challenge for developing new protein-based biosensors is that often multiple rounds of the design, build, and test cycles are required to find labeling positions that provide a change in fluorescence upon binding the target molecule yet do not disrupt the binding properties of the protein.

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Faculty Supervisor:

Trushar Patel

Student:

Partner:

Allos Bioscience Ltd.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Lethbridge

Program:

Accelerate

Mimicking medial-knee brace gait using PCA and biofeedback

Knee osteoarthritis is a disabling disease affecting millions of people worldwide. Knee braces have been adopted as a treatment strategy to help manage osteoarthritis pain. These braces apply a force to the knee, which, in theory, reduces the joint loads in the knee. They also however change the way people walk, which can also reduce pain. The purpose of this research is to determine whether the positive effects of the knee braces are due to the altered walking patterns, or the force they apply to the knee. If the altered walking patterns are what reduce knee pain, patients with osteoarthritis can potentially reduce treatment cost and avoid wearing a brace. This research is being performed in collaboration with HAS-Motion, who has recently released a product required to perform this research. This project will test the capabilities of this new product, before it is distributed, in a real laboratory environment.

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Faculty Supervisor:

Kevin Deluzio

Student:

Partner:

HAS Motion

Discipline:

Engineering

Sector:

Biotechnology; Health and Related Sciences & Technology; Biotechnology; Health and Related Sciences & Technology

University:

Queen's University

Program:

Accelerate

Heart and Stroke Atlantic Canada Cardiac Arrest Policy Strategic Plan

The Heart and Stroke Foundation of Canada has set out four high-level pillars for a nationwide campaign to improve response and outcomes for out-of-hospital cardiac arrest. Heart and Stroke in Atlantic Canada, which covers the provinces of Nova Scotia, Prince Edward Island, and Newfoundland and Labrador, requires a process that will translate the high-level pillars into a strategic and tactical advocacy plan that is tailored to each province’s current state in terms of legislation, political and public receptiveness, and infrastructure, as well as their anticipated needs over the next five years. The interns will conduct a thorough analysis of the current state within each province with regards to cardiac arrest response and policy, leverage political relationships that can enable systematic change, and create strategic campaigns in line with the specific needs and advocacy goals of each province, creating an evidence-driven and actionable roadmap for Heart & Stroke in Atlantic Canada to successfully carry out the campaigns.

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Faculty Supervisor:

Katie Dainty;Timothy Chan

Student:

Partner:

Heart and Stroke Foundation (NS)

Discipline:

Business

Sector:

Other services (except public administration)

University:

University of Toronto

Program:

Business Strategy Internship

Stream Data Analytics Pipeline Based on IoT Big Data Environment for Safer Fleets and Smart Cities

Road safety affects everyone, not just Geotab customers. With several years of driving and environmental data
from over 2 million connected vehicles we have an opportunity to make our customers safer, as well as our
communities and cities. To reduce accidents, we need to understand both the driving behavioural patterns that
are predictive of accidents, and the environmental factors involved. To achieve this, the data infrastructure
should be capable of processing a series of real-time telematics data, as well as time-series historical records
generated from existing machine learning models to respond to real world incidents within a short period of
latency.

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Faculty Supervisor:

Ben Liang

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

Face Matching 1 to N

Fraudsters and money launderers have no place in today’s digital economy. To protect against fraud and financial crime, businesses online need to know and trust that their customers are who they claim to be – and that these customers continue to be trustworthy. Jumio uses the power of AI, biometrics, machine learning and certified liveness detection to help you rapidly convert more customers, stop fraudsters from infiltrating your online ecosystem and get in compliance with KYCIAML. The main goal of this project is to identify an individual from a face image by searching in a gallery of stored face images. The idea is to employ machine learning techniques to solve this problem. For this purpose, we want to review and evaluate existing solutions in order to develop an in-house approach. The fundamental challenges to tackle are: the particular conditions of our data, the huge amount of data to be handled and the quick response time demanded by our use case.

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Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Jumio

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Efficient Multi-frame Obstruction Removal

Modern mobile phones have become the dominant photography device in recent years. However, their users are often not professional photographers. Thus, they lack the skills of choosing proper lighting, proper shot framing, and proper settings on the camera. In particular, photographs are often taken in unfavourable conditions where the scene of interest is obstructed by a fence or a window. We would like to remove such obstruction automatically. Capturing scenes from multiple viewpoints, not only helps to identify the obstruction better, but also helps in removing it. There are existing multi-frame obstruction removal methods, but they are too computationally intensive. This project will focus on a multi-frame obstruction removal approach that is accurate while keeping in mind the computational constraints that would enable mobile deployment. This is of major interest to Samsung as one of the leaders in the mobile phone industry.

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Faculty Supervisor:

Kiriakos Neoklis Kutulakos

Student:

Partner:

Samsung Electronics Canada

Discipline:

Computer science

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Community-based monitoring framework development for the Foxe Basin Kivalliq North Sapujiyiit/Guardians of the Sea Society

The proposed research project will be to provide an understanding and overview of Inuit women’s concerns, feelings, and thoughts regarding how their day to day lives are changing due to climate change and increased development in Nunavut. The partner organization (Sapujiyiit Society) will have the role of guiding the HQP through formulation of the research question, project design and implementation, assistance with research objectives and incorporation of perspectives of Inuit women. This work is aligned with government initiatives outlined in the throne speech and will help us understand the impacts of climate change on women. Outputs will be publicly available to be adopted and modified by other guardians programs.

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Faculty Supervisor:

Brent McKnight

Student:

Partner:

Sapujiyiit Society

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

An automatic syringe filling system that uses robotic arms controlled by deep learning algorithms to help pharmacy technicians with their tasks

In certain scenarios, in the hospitals, oral medications need to be administrated in a liquid form using syringes in order to avoid complications such as asphyxiation due to the blocking of airways, which is common in children. Consequently, a pharmacy technician may need to fill up hundreds of syringes per day for different units at the hospital such as pediatrics, geriatrics, and psychiatry.
These sets of repetitive tasks expose pharmacy technicians to high risks of work-related musculoskeletal disorders. For instance, tendinitis may occur during syringe filling due to poor wrist posture. In addition, the shortage of personnel is hitting our hospital pharmacy departments hard and is forcing the hospitals to make painful choices in the services they can offer. To address this problem, we will be using robots capable of integrating Deep Learning (DLs) algorithms. This robot can help pharmacy technicians with their tasks. As a result, pharmacy technicians can be assigned to other duties where their presence is needed.

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Faculty Supervisor:

Usef Faghihi

Student:

Partner:

Kobotik Inc.

Discipline:

Computer science

Sector:

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

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

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