Innovative Projects Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Quantum Resistant High Speed Blockchain Project

Secure, open, distributed computing platforms are able to provide trustable peer-to-peer transactions without the need for trusted intermediaries. However, as quantum-computers gain power and capability, the cryptographic systems they are built on are threatened. This project will provide the system described here with quantumresistant cryptographic protocols to ensure both system security and user privacy, and build a formal mathematical model to verify the safety and liveness of the system. This is essential for the company’s value proposition, as both users and investors need to be assured that these characteristics will be stable into the foreseeable future.

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Faculty Supervisor:

Ceit Butler

Student:

Deepanshu Gupta;Nguyen Anh Tuan Dinh;Mohammad Jamshed Qureshi;Estella Yeung;Dixin Xu

Partner:

TrustWave

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

George Brown College of Applied Arts and Technology

Program:

Accelerate

Preliminary Design of Distributed Hydroponic Grow Systems in Residential Buildings as a Means of Addressing Market Interest and Food Supply Chain Disruption Due to COVID19

Hydroponics is a farming method that does not require soil, but rather utilizes a porous medium to hold plants so that waste of irrigation solution is minimized. This type of farming is considered more expensive than traditional open-field agriculture. However, it has been found to function well in enclosed spaces with a controlled environment, especially in cold climates where open-field agriculture is challenging. This project aims to assess the feasibility to perform such farming inside of residential units by having all of the necessary equipment, such as the utility elements of a system reservoir, fertigation, and irrigation components, be located with other household utility equipment (e.g. laundry, furnace, central vacuum). Meanwhile, the medium or components for growing, tending, or aesthetics would be located within living areas (e.g. kitchen, foyer, breakfast nook).

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Faculty Supervisor:

Lexuan Zhong

Student:

Artur Udovichenko

Partner:

ColdAcre

Discipline:

Engineering - mechanical

Sector:

Agriculture

University:

University of Alberta

Program:

Accelerate

Watershed Modelling for Stormwater Infrastructure Planning and Design Under Climate Change in Pouch Cove, NL

Climate change will continue to increase vulnerability and risk to the impacts of extreme events and the complexity of processes that determine the potential for increased flood flows makes it difficult to properly design storm water infrastructure (such as storm sewers and culverts). The Town of Pouch Cove was able to conduct a risk and opportunity assessment directed at identifying climate vulnerabilities, and generating solutions/action items aimed at mitigating these risks and vulnerabilities. The Town’s existing storm water management system was identified as a clear infrastructure and public safety vulnerability. The objective of this project is to incorporate science-based quantitative knowledge and qualitative local knowledge into an integrative decision-support protocol for planning and design of sustainable and resilient storm water infrastructure. This work will use watershed approach to explore potential strategies to design a sustainable storm water drainage system that reduces the risk of flooding and failure of vital infrastructure.

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Faculty Supervisor:

Joseph A Daraio

Student:

Abena Amponsah

Partner:

Town of Pouch Cove

Discipline:

Engineering - civil

Sector:

Administrative and support, waste management and remediation services

University:

Memorial University of Newfoundland

Program:

Structural and thermal performance of optimum 3D printed parts from continuous carbon fiber-Poly Ether Ether Ketone composites

Additive manufacturing, also called 3D printing, of composites can manufacture final parts with high strength and stiffness. In this project, carbon fiber composites with a high temperature polymer are used for 3D printing. A custom 3D printing head installed on a robotic arm is used for manufacturing. Specimens are 3D printed to evaluate structural and thermal properties of final parts. Automated manufacturing of composites using robotic 3D printing is efficient for fabricating small-scale parts with low volume and can open new opportunities for composites. In addition, robotic 3D printing can simplify and shorten the research and development activities on raw material optimization for automated manufacturing.

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Faculty Supervisor:

Kazem Fayazbakhsh

Student:

Seyed Hossein Miri

Partner:

Teijin Carbon America Inc

Discipline:

Aerospace studies

Sector:

Manufacturing

University:

Ryerson University

Program:

Accelerate

Learning Disabilities Association of Canada (LDAC) Research Hub: Synthesizing the last decade of Canadian research on specific learning disorders

The objective of this project is to develop a user-friendly, online database of Canadian research that directly relates to Specific Learning Disabilities (SLD), and provide research report synthesizing the contents of the research hub to date. This project will benefit Canadians, as it will provide stakeholders involved with SLD easy access to information. Parents, teachers, psychologists, social workers, employers, and individuals with a SLD, will benefit from being able to access a database, which strictly focuses on SLD and disorders often associated with SLD, such as attention deficit hyperactivity disorder (ADHD), anxiety, and depression. Easy access to specific research will help to educate Canadians on a variety of aspects of SLD such as causes, diagnostic criteria, assessment, underlying cognitive processing difficulties, learning strategies, and assistive technology.

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Faculty Supervisor:

Gabrielle Young

Student:

Thi Mai Hanh DO

Partner:

Learning Disabilities Association of Canada

Discipline:

Education

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Cannabis pest complex in Ontario, Canada, and the use of companion crops in outdoor cannabis production

With the recent legalization of recreational cannabis in Canada, cultivation of cannabis sativa has increased significantly, including rapid adoption of outdoor cultivation. Given the cheaper cost of production compared to indoor cultivation, the growth in outdoor cultivation will likely outpace that of indoor. However, while outdoor cannabis cultivation faces many of the same pest challenges as indoor cultivation, there are no pesticides registered for outdoor cannabis. Growers must rely on other integrated pest management (IPM) tactics to manage pests. Conservation biological control involves modifying the landscape to promote beneficial insect and repel pests. We will evaluate the effectiveness of various companion plants such as marigold, sunflowers, and aromatic herbs to attract beneficials and repel pests. Developing an understanding of the insect diversity associated with outdoor cannabis and how companion crops affect these insects would allow growers to make more informed and sustainable IPM decisions given the lack of registered insecticides.

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Faculty Supervisor:

Cynthia Scott-Dupree

Student:

Lillian Auty

Partner:

JC Green Cannabis Company

Discipline:

Environmental sciences

Sector:

Agriculture

University:

University of Guelph

Program:

Monitoring the Impact of COVID-19 Isolation Policies on Public Wellness using IoT – A Public Health and Work from Home Perspective

Social isolation is having a significant impact on the quality of life, physical activity, and sleep patterns of our population. While self-isolation and social distancing provide the most successful method for limiting the progression and spread of infectious diseases like COVID-19, we often overlook the impact of these rules on our population. This impact is also observed in the quality of the work environment available for employees working from home, where they often lack the necessary equipment and conditions to comfortably and safely work from home.
Through the use of data ecosystems developed at the UbiLab, we propose to monitor the impact of quarantine rules on household-level and individual-level physical activity, sleep, mental health, and work-related stressors and ergonomics.
During Phase 1, from a public health perspective, the proposed ecosystem would be useful in understanding the impact of COVID-19 in our population, monitoring the ongoing impact and the changes in our behaviours caused by public policies implemented. In Phase 2, our team will explore the use of this data to better inform work from home guidelines.

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Faculty Supervisor:

Plinio Pelegrini Morita

Student:

Niloofar Jalali;Aaishwarya Bansal;Kirti Sundar Sahu;Pedro Augusto da Silva e Souza Miranda;Tatiana Silva Bevilacqua

Partner:

Thinktum

Discipline:

Epidemiology / Public health and policy

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Study of swine metabolism in a cell line model

Understanding swine metabolism is important to the pork industry, for the improvement of feed efficiency and meat quality, in addition to animal wellbeing. We have recently discovered two stress genes (Luman/CREB3 and LRF/CREBRF) that regulate animal responses to stress. Mutation of these Luman or LRF gene resulted in animals that are more tolerate to stress, in the meantime being lean with very low abdominal fat. Here we propose to further our study on how these genes regulate metabolism using a swine liver cell system. We believe that the proposed research will cast light on the underlying mechanism of why our mutant mice are lean, at the molecular and cellular level. The outcomes of this research will not only benefit the pork industry by increasing production efficiency and enhancing animal welfare, but may also help understand and treat various metabolic diseases of humans.

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Faculty Supervisor:

Ray Lu

Student:

Briana Locke;Brandon Smith

Partner:

Alliance Genetics Canada

Discipline:

Biochemistry / Molecular biology

Sector:

Agriculture

University:

University of Guelph

Program:

Accelerate

Broken Promises: Museum Exhibit Development during the Covid-19 Pandemic

Broken Promises is the capstone output of Landscapes of Injustice, a multi-year, intersectoral project exploring the dispossession of Japanese Canadians during the 1940s. The project illustrates the violation of human and civil rights at a time of perceived insecurity; measures taken in the name of national defence; the enduring harm of mass displacement, and loss of home and property; and human resilience. The traveling exhibit is one of the major research outputs of the project. Adapting to new requirements for museums during Covid-19, this research will enable the launch of the LOI museum exhibit at the Nikkei Museum in September 2020, by developing interactive displays in line with new museum guidelines, and innovative digital resources that extend the reach of our exhibit. Working with the Nikkei National Museum, and University of Victoria, this project advances knowledge on this important history, and represents new research on museums adapting to Covid-19.

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Faculty Supervisor:

Jordan Stanger-Ross

Student:

Yasmin Amaratunga Railton

Partner:

Nikkei National Museum & Cultural Centre

Discipline:

History

Sector:

Arts, entertainment and recreation

University:

University of Victoria

Program:

Accelerate

Advanced AI for Demand Forecast, Assortment Planning and Plan Monitoring in Fashion and Apparel Retailing

Retailers require reliable demand forecasts for their operations management and planning. Demand forecasting for fashion products is, however, an extremely challenging task. A good solution for this problem should address at least the following three questions: (i) high volatility of demand and its dependence on external factors (ii) forecasting flexibility for different spatio-tempo-hierarchical aggregation levels, and (iii) forecasting for new products without historical data. The other aspect of the problem is to follow the gradual actualization of the demand in time, update the forecasts, and detect anomalies. The outliers and anomalies could subsequently be translated to corrective responses to meet the demand and minimize costs and lost opportunities. The main objective of the project is to explore the state-of-the-art algorithms for time-series forecast and anomaly detection followed by the design and implementation of a demand forecast and monitoring framework that could appropriately address the three above-mentioned forecast challenges and detect anomalies in demand.

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Faculty Supervisor:

Nizar Bouguila

Student:

Ornela Bregu;Rafiul Hasan Khan

Partner:

FIND Innovation Labs Inc.

Discipline:

Engineering

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:

Fatemeh Esfahani

Partner:

Innotech Medical Industries Corp

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Characterization of a DTI Tractography Pipeline for 3D Visualization of Spinal Cord Pathology

Spinal cord pathology causes significant burden to the individual and society-at-large. Treatment is complex and made more difficult by difficulties in clinical imaging of the cord microstructure. Using recent advances in image acquisition techniques and image processing toolsets, this project will investigate a semi-automated pipeline to visualize boundaries of spinal cord pathology for the purpose of translation to computer-assisted neurosurgery. This project is expected to provide critical information to the industry partner to establish appropriate protocols for their industry-leading commercial products in this area.

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Faculty Supervisor:

Stewart McLachlin;Alexander Wong;Michael Hardisty

Student:

Vignesh Sivan

Partner:

Synaptive Medical Inc.

Discipline:

Engineering

Sector:

University:

Program:

Accelerate

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