Innovative Projects Realized

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

29670 Completed Projects

2811
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4990
BC
801
MB
663
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825
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8841
ON
9197
QC
95
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568
NB
1088
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Projects by Category

Innovation Through Customer Insights and Service Development

We-Watch is a for-profit, social enterprise that has created a mobile platform to report public safety incidents and collect evidence on these incidents from users near the location of the incident. We-Watch has partnered with West Queen West BIA, Downtown Toronto to conduct its first pilot project for their mobile application. During this pilot, the business owners of the BIA will have exclusive access to this mobile platform for 4 months. This project will involve running the pilot launch to uncover insights about the application usage patterns and behavior of the end customers, which will help design the future builds of the application and make improvisations on the identified bottlenecks. The project will also help explore other sales opportunities for the application, by looking at other target audiences such as industrial settings, homeowner associations etc.

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Faculty Supervisor:

Ashwin Joshi

Student:

Partner:

We-Watch Corp.

Discipline:

Business

Sector:

Information and cultural industries

University:

York University

Program:

Business Strategy Internship

Collective community gardening for food security and integration of African immigrants in Edmonton, Alberta

Cultural food insecurity, which is the inability to acquire, afford, and eat the traditional foods of one’s ethnic origin is a form of food insecurity that disproportionately affects new immigrant, especially the Black identifying Canadians. However, research that explores alternative ways to diversity Canadian food systems to accommodate new immigrants and to allow for smooth transition and integration of African immigrants are limited. The current project aims to address this knowledge gap by exploring the barriers and facilitators of use of collective community gardens in providing spaces for production of culturally familiar foods and in supporting the integration of new African immigrants in Edmonton, Alberta. In collaboration with Sinkunia Community Development Organization (SCDO), we will conduct a qualitative and quantitative study to investigate the barriers and facilitators of engagement to community gardening and the most preferred culturally familiar vegetables and fruits. This project will be an initial step towards the diversification of Canadian food system by contributing to creation of knowledge on the most preferred cultural vegetables and fruits.

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Faculty Supervisor:

Elizabeth Onyango

Student:

Partner:

Sinkunia

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

University of Alberta

Program:

Accelerate

An Intelligent Method for Bearing Anomaly Detection

Anomaly detection of machinery is a crucial aspect of predictive maintenance. It involves monitoring specific parameters related to the machinery’s condition to identify significant changes that indicate a potential fault. Bearings, which are important components in rotary machinery, are responsible for over 40 percent of rotary machinery failures. Consequently, researchers have been focusing on detecting anomalies in bearings. While there are various methods available for bearing anomaly detection, most of them require high engineering expertise to detect faults. Alternatively, techniques solely based on machine learning models are not always reliable and accurate. Additionally, detecting weak faults accurately has been challenging due to the complexity of bearing vibration signals. As a result, there is a lack of an intelligent method that can automatically and precisely detect faults. In this project, our goal is to develop an intelligent anomaly detection model, and conduct multiple validation tests using various datasets, including three public datasets, one lab dataset generated by the applicants, and industrial data from our partner organization to achieve an accurate, reliable, and robust model.

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Faculty Supervisor:

Xihui Liang;Parimala Thulasiraman;Carson Leung

Student:

Partner:

StandardAero

Discipline:

Engineering

Sector:

Aerospace; Artificial Intelligence; Energy and Utilities

University:

University of Manitoba

Program:

Accelerate

Monitoring Volume changes and IgA protein in complex biological mixture of vaginal discharge as a real-time ovulation detection

The female body goes through various hormonal changes at each phase of the menstrual cycle every month. These hormonal changes result in detectable biophysical changes, such as skin temperature variations. Moreover, the chances of pregnancy are noticeably higher during the ovulation phase which is a 4-5 days window. Our product, will have sensors inside it to non-invasively monitor these biophysical changes from the surface of the body and determine which phase the user is in with high accuracy. As the result, women can use this personalized information to increase or decrease their chance of pregnancy in a non-hormonal, non-invasive, personalized and accurate, reusable, and easy-to-use manner. This project seeks to prove the feasibility of developing this wearable device and the accuracy of the sensors in taking the parameters.

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Faculty Supervisor:

Bryan Koivisto;Gerd Grau

Student:

Partner:

Fibra Inc.

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Retail trade

University:

Toronto Metropolitan University; York University

Program:

Accelerate

Analysis of angled nozzle spray profiles and their suitability in site-specific applications.

Spot application of pesticide has economic and environmental benefits. To enable a real-time spraying, the timing of actuation after detecting the pest should be precise to enable hitting the target. One issue in spraying using wide booms is the need to place cameras on the boom itself to avoid possible costly mechanical modifications. As such, the short distance between the sensor (camera) and actuator (nozzle valves) requires nearly instantaneous detection and actuation which is not possible with the current state-of-the-art technology. During the internship, we plan to test and validate new angled nozzle tips that allow the sprayer to spray backwards to gain time that will allow the camera to detect the pest and send a signal to the nozzle valve. Also, we plan to test the spraying pattern while the valve is opening to verify the possibility of including the transitional period of valve opening in the spraying time.

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Faculty Supervisor:

Ahmad Al-Mallahi

Student:

Partner:

Indian Institute of Technology Tirupati

Discipline:

Engineering

Sector:

Agriculture and Food; Technology; Sustainability & the Environment

University:

Dalhousie University

Program:

Globalink Research Award

Navigating Canada’s food system: The experiences of racialized immigrants in Edmonton, Alberta

This research project will examine the experiences of racialized newcomers living in Edmonton, Alberta, who are living in food insecurity, a state where people have inadequate amounts and/or inappropriate types of food. Current research has studied food security more broadly; however, risk is higher among certain groups including individuals who are Black, Indigenous, or persons of colour. By engaging with culturally diverse people, this study will show and raise awareness of how their higher food insecurity risks require different solutions to meet their food needs. The partner organization, Multicultural Health Brokers, will benefit from this partnership, because they will be able to use the findings to help teach the public of how food insecurity is caused. It will also help in teaching people ways they can help to address cultural food security.

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Faculty Supervisor:

Elizabeth Onyango

Student:

Partner:

Multicultural Health Brokers Co-Operative Ltd

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

University of Alberta

Program:

Accelerate

Performance of Green Concrete Incorporating Recycled Face Masks

Over the past two years, the COVID-19 (SARS-CoV-2) pandemic has been the main global public concern affecting human health. A tremendous amount of personal protective equipment has been produced and used by the health service and every human. Hence, proper medical waste management becomes a critical problem which must be solved with a minimal environmental impact. On top of used protective equipment, face-covering masks were used extensively, forming a new non-biodegradable
waste stream that poses a considerable environmental risk to the ecosystem if not correctly disposed of. Thus, this waste must be recycled in an eco-friendly manner on an urgent basis. Hence, the proposed project aims to develop a new environmentally friendly recycling technique using waste generated during mask production in creating sustainable green concrete elements. Hence, the materials-structural design concept will be adopted, providing a full idea about potential construction applications for these new green materials while reducing environmental impact.

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Faculty Supervisor:

Ahmed Soliman

Student:

Partner:

Meltech Innovation

Discipline:

Engineering

Sector:

Manufacturing

University:

Concordia University

Program:

Accelerate

Industry-focused Best Practices: hPSC Biomanufacturing Training Practicum for Advanced Therapies Workforce Development

The Canadian Advanced Therapies Training Institute (CATTI), launched through a partnership between CellCAN and CCRM, is a centre of training excellence that is developing and scaling e-learning and on-site GMP training programs for efficient and rapid upskilling of the workforce required in Canada and internationally. Within the scope of this project, a Lab Technician/Research Analyst (intern) is required to to assist with the setup of the CATTI Training Lab, through equipment setup and maintenance, SOP creation, cell culture preparation, and receiving consumables and equipment and updating inventory. The intern will further assist in the development of complementary modules and courses structured around the CATTI virtual e-learning curriculum (currently available internationally) and practicum, to be delivered starting Summer 2023.

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Faculty Supervisor:

Sarah Lepage

Student:

Partner:

Canadian Advanced Therapies Training Institute

Discipline:

Life Sciences

Sector:

Education

University:

University of Guelph

Program:

Business Strategy Internship

Optimization of Electrical Drivetrain in Agricultural Application

This project will investigate the timely problem of electrification of heavy-duty agricultural equipment and their various implements. Electrification of these critical pieces of equipment, either fully or partially, is poised to yield significant benefits such as improved efficiency, better reliability, and lower cost of operation. In order to design an electrified version of a complex systems such as an agricultural equipment, extensive studies need to be conducted to determine the existing and envisioned power flow paths and to evaluate the benefits that electrification will introduce in terms of cost, efficiency, and operation. In collaboration with a leading manufacturer of agricultural equipment, this project aims to take a concrete step towards better designs of electrified drive trains for heavy-duty farming machinery.

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Faculty Supervisor:

Shaahin Filizadeh

Student:

Partner:

MacDon Industries Ltd.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Manitoba

Program:

Accelerate

Implémentation de normes éthiques en intelligence artificielle

L’objectif du projet de recherche est d’implémenter des principes éthiques en intelligence artificielle à partir des travaux de recherches doctoraux de l’étudiant, qui portent sur l’apport de la philosophie de la technique à l’éthique de l’intelligence artificielle, et plus précisément sur l’étude de la notion de responsabilité appliquée à la civilisation technologique et à la société de l’innovation. Il s’agira notamment d’approfondir la Déclaration de Montréal pour un développement responsable de l’intelligence artificielle, notamment sur le volet de la responsabilité. Le travail de recherche alliera une recherche théorique avec une approche pratique, via des entretiens avec les membres de l’écosystème de l’intelligence artificielle, aussi bien dans le secteur public que privé. Il s’agira donc d’approfondir les aspects liés à la responsabilité dans le développement et la gouvernance de l’intelligence artificielle. Une présentation des résultats est attendue, sous la forme d’un événement ouvert aux spécialistes et au public.

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Faculty Supervisor:

Marc-Antoine Dilhac

Student:

Partner:

Université Grenoble Alpes

Discipline:

Sociology

Sector:

Education

University:

Université de Montréal

Program:

Globalink Research Award

Effects of Photobiomodulation on cognitive, physical, and cerebral neurovascular function in Parkinson’s disease

Parkinson’s disease (PD) is increasingly prevalent, affecting ~170 per 100,000 Canadians annually. Currently, there is no cure for PD, warranting the investigation of potential new therapeutics. Photobiomodulation (PBM) is a low-level light therapy that has been proposed as an alternative treatment for neurodegenerative diseases, such as PD. However, there is a lack of data regarding the efficacy of PBM on individuals with PD, specifically cerebrovascular function. Accordingly, our study aims to attain pilot data to complete a full randomized control trial. The objectives of the study are to determine the effects of PBM in patients with PD on: (1) cognitive function;
(2) motor function; and (3) cerebrovascular function. In our double-blind cross-over study, participants will be assigned to both the treatment and placebo groups. To determine whether there is a difference in receiving PBM compared to placebo, participants will undergo a series of cognitive, neurovascular, cerebrovascular, and physical assessments to determine their respective functional status. These data will provide insight on the potential use of PBM as an alternative therapy for PD.

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Faculty Supervisor:

Anthony Bain

Student:

Partner:

Parkinson Society Southwestern Ontario

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

University of Windsor

Program:

Accelerate

Detection and Investigation of Email Exfiltration Events in Sun Life Cybersecurity Data, including Text Analysis

The current Sun Life anomaly detection methods are based on human inspection. The method is labour intensive and only a relatively small number of cases can be reviewed. There is no guarantee that the most suspicious interactions are in fact being sampled and reviewed. In this project we will focus on the develop of novel AL methods and user interfaces that can improve the process of labelling instances and recognizing if anomalies are likely to be malicious, and we improve the sensitive of automated anomaly detection models by adding text analysis into the process. Our work will involve cutting edge research in the emerging field of human-AI interaction, and improving the quality of detection our research to: a) Reduce workload for experts involved in the detection process; b) Improve trust/compatibility of the expert-model team; c) Develop new insights concerning the frequency and types of risky behaviours that are carried out by employees.

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Faculty Supervisor:

Mark Chignell

Student:

Partner:

Sun Life Financial

Discipline:

Engineering

Sector:

Finance and Insurance

University:

University of Toronto

Program:

Accelerate

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