Innovative Projects Realized

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

29670 Completed Projects

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Projects by Category

Innovation in Expanded Pharmacy Care Health and Wellness Approaches in the Grocery Retail Environment

Health care systems in Canada and countries around the world are challenged by increasing
demands for services, while providing those services within fixed health agency budgets. To address
these challenges, the Ivey International Centre for Health Innovation, Loblaw Company Limited and
Green Shield Canada has formed a collaborative partnership. The proposed research will engage
academic and industry researchers, key decision-makers, pharmacists and dietitians in examining
and exploring the impact of new, expanded models of pharmacy care in retail grocery store settings
that focus on achieving health and wellness outcomes for communities. In addition, the impact of
expanded pharmacy practice roles will be examined for potential program development opportunities
for employee health products designed to enhance employee health and wellness outcomes in
workplace settings.

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Faculty Supervisor:

Anne Snowdon

Student:

Partner:

Loblaws Inc;Western University

Discipline:

Business

Sector:

Health and Related Sciences & Technology

University:

Western University

Program:

Accelerate

Machine Learning Solutions for Detecting Suspicious and Abnormal User Access Roles and Entitlements

The latest cybersecurity incidents (e.g., Desjardinds, CapitalOne) have shown that the current cybersecurity solutions are not always effective in capturing and preventing attacks, especially when it comes to insider attacks that originate from within the targeted organization. In this project which will be conducted in collaboration with Xpertics, we aim to build a new solution for extracting and analyzing users’ access and entitlement data within a cloud environment, in order to detect suspicious and abnormal access activities and permissions. We will capitalize on the strength of deep learning to build strong prediction models with high accuracy. At the end of this project, the company will have an effective cybersecurity solution that could be used to prevent unauthorized access to its resources and identify the suspicious access attempts that try to manipulate the internal security measures of the company.

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Faculty Supervisor:

Jamal Bentahar;Omar Abdul Wahab

Student:

Partner:

Xpertics Solutions Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Anatomy Detection of Cats and Dogs using Localization

The proposed work is an application of artificial intelligence and medical imaging. When positioning a dog to have an X-ray image taken of its paw, a neural network trained in canine anatomy can be configured to inform radiologists if the patient’s paw is improperly placed or even drive motorized hardware to automatically center the patient’s anatomy with respect to the imaging hardware. Diagnostic X-ray images like DICOMs contain header information about the subject including species, anatomy imaged, and the orientation of the image. This information is filled out manually, but the aforementioned neural network could be configured to automatically populate this DICOM tag information. The methods developed in this research will be immediately applicable to the partner organization; these tools will be integrated within iMi’s x-ray imaging system for use in veterinary clinics. Additionally, automatic anatomy detection will allow iMi to develop new hardware informed by this technology.

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Faculty Supervisor:

Alex Thomo

Student:

Partner:

Innotech Medical Industries Corp

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Inclusion of Genetic Information to Better Inform Coffee Choices

Coffee is one of the world’s most popular beverages due to the delivery of caffeine and diverse flavours. The genetics of how caffeine is processed in the human body is fairly well understood. With the decrease in cost and increase in popularity of consumer genetics, we are interested in learning how modern genetic analysis techniques can benefit the choice of caffeine and flavour for coffee consumers. We plan to look at candidate genes that relate to caffeine clearance rates within volunteers, then deliver blends of coffee customized to individual volunteers’ caffeine tolerances and preferences. Additionally, the genetics of flavour perception, and taste associated genes are fairly well known. Based on candidate taste genes, will also test which blends of coffee are preferred based on flavour perception with respect to bitter taste genes.

View Full Project Description
Faculty Supervisor:

Marc Ekker

Student:

Partner:

Beverage Genetics

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Ottawa

Program:

Accelerate

Analyzing a Large User Community using theSocial Network Analysis Framework

In this project we will conduct Social network analysis (SNA) of MyCA user network, in order to
assess the interplay between social influence and the diffusion of information within the MyCA
platform. SNA offers a convenient method to represent and analyze interactions among the
components of a system. SNA can thus provide an abstract representation of the MyCA a system,
and allow us to study its function and organization. We will work with CA to determine ways to use our
insights to increase participation of MyCA members such that their connections and contributions will
bring overall value to the community. The results of this analysis will help us determine how to
structure the platform and support community users such that greater value can be realized by
community users, CA employees, and CA product owners.

View Full Project Description
Faculty Supervisor:

Kelly Lyons

Student:

Partner:

CA Technologies

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

Microemulsion technologies for the extraction and delivery of herbal oils and oleoresins

Herbal oils and oleoresins are components extracted from flowers, bark, leaves, roots, or fruits. These extracts are used as fragrances, flavoring agents, antimicrobials, and therapeutic agents with a market value of more than USD 8.5 billion and 7% annual growth. Steam and solvents are used to extract oils and oleoresins (respectively), but they have limited extraction efficiency, are energy-intensive, and emit greenhouse gases (GHG). Solvent extraction can also emit volatile organic components (VOCs) and produce flammable environments. This project seeks to develop aqueous extraction and delivery systems for herbal oils and oleoresins using food-grade surfactants and emulsified solvents. The example herbal oil, clove oil, and oleoresin, capsaicin, are both used as flavoring agents, as antimicrobials, and as medicinal compounds. Micellae delivery systems (partner organization) will use the findings from this work to develop a safe aqueous extraction process and delivery systems for cannabinoids.

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Faculty Supervisor:

Edgar Acosta

Student:

Partner:

Micellae Delivery Systems

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Assessment of aeration performance and energy consumption of different biological wastewater treatment systems for small communities in Ontario

Attached growth wastewater treatment processes such as the rotating biological contactor (RBC) have been recognized as more energy efficient compared to suspended growth processes. Hannah Environmental Equipment Inc. specializes in producing high energy efficient RBC systems providing high modular flexibility suitable for various plant sizes. The proposed project aims to assess the application of RBCs in the Canadian environment and compare that to current secondary wastewater treatment technologies in terms of energy efficiency, treatment performance, and environmental impact. This study will provide a comprehensive energy and cost assessment of the RBC ?technology and its capacity for greenfield and retrofit applications ?to increase treatment capacity, reduce treatment costs, and provide opportunities for energy savings and reduction in greenhouse gas emissions. The analysis will provide scientific evidence based on real data from local wastewater treatment plants to allow Hannah to accelerate their growth and optimize their performance in the Canadian market with their RBC technology.

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Faculty Supervisor:

Rania Hamza

Student:

Partner:

Hannah Environmental Equipment Inc.

Discipline:

Engineering

Sector:

Utilities

University:

Toronto Metropolitan University

Program:

Accelerate

Optimization of organic nutrient solution using ion and bacterial community monitoring for plant oil production

Organic nutrient use in hydroponic solution increases the sustainability of these systems by using waste. These solutions can be adequately reused if real-time nutrient concentration calculation is made with the use of electrodes. With the use of Ion Specific Electrodes (ISE), the relative absence or presence of an element can be calculated in real time. Theoretically, the use of these organic nutrient solutions could prove to be superior than inorganic solution for yield because of the microbiome. Through modulation of microbial communities in the plant root environment, discovery of beneficial microbes responsible for increased plant oil production is possible.

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Faculty Supervisor:

Mark Lefsrud

Student:

Partner:

Cannafish Corporation

Discipline:

Engineering

Sector:

Agriculture

University:

McGill University

Program:

Accelerate

Development of a Deep Learning algorithm to improve the image quality of the pictures taken by Quartet® real-time

1 in 5 people suffer from a mental illness, such as depression, Alzheimer’s & Parkinon’s during their lifetime. Currently, there are no treatments for these diseases, because the underlying causes of these diseases is not known. Neurescence has developed a technology that is essential for understanding how local and long-range neuronal circuits form to create healthy brain function, hence understand how these neuronal circuits are disrupted in each disease. This project is related in developing the technology required to obtain crucial information that will help companies and academic institutions to develop new treatments for brain diseases. The result is not only helping to push our knowledge of the brain and find better therapies, but also helping Neurescence realize its commercial goals, resulting into creation of jobs for highly skilled workers in STEM fields.

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Faculty Supervisor:

Ofer Levi;Taufik Valiante

Student:

Partner:

Neurescence Inc.

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Manufacturing

University:

University of Toronto

Program:

Accelerate

SPT-based Methods for Estimating Installation Torque and Capacity of Helical Piles

Helical piles are extensively used across Canada in various engineering applications. Current design methods estimate the axial capacity of helical piles using soil strength parameters when site investigation is available. Alternatively, helical piles can be designed from an empirical torque correlation when installation torques are available. However, it will be more valuable to the industry to have direct design approaches based on geotechnical site investigation. Greentown Homes Ltd., the industrial partner in Edmonton, has built numerous foundations using helical piles in various soil conditions in Alberta. For the proposed project, the intern will first supervise in-situ pile installation of building foundations, record torque values, and collect geotechnical properties of soil at different sites. The intern will compile and analyze the Greentown database of site investigation and installation torques. Using the Greentown and other databases, the intern will develop an empirical method for helical capacities based directly on the SPT, and an empirical correlation between the torque and SPT blow counts.

View Full Project Description
Faculty Supervisor:

Lijun Deng

Student:

Partner:

Greentown Homes

Discipline:

Engineering

Sector:

Construction and infrastructure; Real estate and rental and leasing

University:

University of Alberta

Program:

Accelerate

CDL-Recovery Intern

The Creative Destruction Lab is a seed venture development program for massively scalable science and technology based ventures founded to positively impact the human condition. The CDL has instituted a unique summer program in light of the COVID-19 pandemic that accelerates ventures that address Covid-19 in terms of information-based solutions. CDL-West, based at UBC Sauder School of Business, supports CDL-Recovery in venture recruitment, venture management, pedagogy, virtual event management and in achievement of mentor-delegated objectives. Given that CDL-Recovery exists above and beyond regular CDL-West programming, the CDL-West interns are crucial to the programs execution.
The CDL-West interns will support all elements of CDL-Recovery but will have special emphasis on virtual event management and providing consultative support for the benefit of the ventures’ achievement of mentor-delegated objectives. Projects may include market analysis, customer development, financial analysis, and other core activities related to building early stage start-ups as designated by program mentors and allocated by the CDL-Recovery team.

View Full Project Description
Faculty Supervisor:

Robert Helsley

Student:

Partner:

CDL Canada

Discipline:

Business

Sector:

Biotechnology

University:

The University of British Columbia

Program:

Business Strategy Internship

Computer Vision for Crop Weed Identification

Aid in the development of a Machine Learning Model for utilization by an Agricultural Robot. This Robot performs several tasks, primarily the mechanical removal of weeds from vegetable farms. Therefore, the machine learning model is concerned with informing the robot of locations of interest points of the weed and crop plants, as viewed from several sensors mounted on the robot. Other sensors of the robot, such as GPS, and wheel odometry, can be brought to bear as well.

View Full Project Description
Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Nexus Robotics

Discipline:

Computer science

Sector:

Agriculture

University:

Université de Montréal

Program:

Accelerate

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