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

Advanced Oxidation Process in Fresh Produce Processing: Reducing water usage, extending shelf-life and enhancing food safety

Fresh produce remains the leading cause of foodborne illness and highlighted for carrying pesticide residues. Moreover, fruit and vegetables have been highlighted as one of the leading sources of food waste, in addition to a major user of water. Currently, post-harvest washing is used as a step to remove field acquired contamination. However, both microbes and pesticides are not inactivated by washing but more distributed between batches. In addition, washed produce spoilers quicker than unwashed and the amount of water used in the process can be in the order of 4 liters per kg of product. The proposed project will overcome all these issues by developing a process that harnesses the oxidative power of chloride radicals (through a process termed Advanced Oxidation Process; AOP) to inactivate microbes and degrade pesticides while using minimal amounts of water. In a further process, the oxidative power from AOP will be applied to degrade pesticides and chlorine-consuming constituents in water. This is primary to make the washing process more effective and reduce the water usage by negating the need to keep replenishing wash tanks. Collectively both technologies will enhance the food safety of fresh produce and extend shelf-life.

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Faculty Supervisor:

Keith Warriner;Ryan Prosser

Student:

Hongran Wang;Gustavo Bastos Machado

Partner:

Pride Pak Ltd.

Discipline:

Environmental sciences

Sector:

University:

University of Guelph

Program:

Accelerate

Preparation of Sentinel Wraps for Detection of Pathogens in Food Packages

The goal of this project is to develop and integrate the required technology to create food wrapping materials that can tell any untrained consumer if the food is safe to eat, without the need to use sophisticated equipment. This will be achieved by incorporating a barcode-type biosensor on an antifouling food wrap. The biosensor is capable of detecting traces of specific pathogenic strain of bacteria Escherichia coli O157:H7. Therefore, food contamination can be screened on the shelf via a simple handheld fluorescence detector device. We anticipate that the developed intelligent food packaging material will report the presence of target pathogens without the need to open the packaging. This research is undertaken in collaboration with an industry partner, Toyota Tsusho Canada Inc. (TTCI), who will ultimately validate and commercialize the final technologies and products.

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Faculty Supervisor:

Tohid Didar

Student:

Amid Shakeri

Partner:

Toyota Canada

Discipline:

Engineering

Sector:

Transportation and warehousing

University:

McMaster University

Program:

Accelerate

Development of a solution to assess the quality and to optimize AI-based video codecs

Current video codecs consider algorithms to analyze video imagery in order to find out which bits can be removed for file size reduction without subjective video frame degradation. Integrating AI with encoding process improves the quality of encoding and decoding. AI permits the software to proactively assess the quality of the encoded video before transmission. This allows the compressing system to detect and remedy any possible artifacts in the video frames. The main objectives of the company regarding this project can be summarized as 1) Quality assessment regarding the AI-based video codecs from the industry perspective. 2) Determination of codec capability of running on off-the-shelf hardware. 3) Evaluation of AI-based codecs optimization techniques such as vectorization, SIMD, GPU, etc. The enhancement in such technologies could improve the entertainment industry in the country and also potentially assist smart city projects in Canada.

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Faculty Supervisor:

Nizar Bouguila

Student:

Vahid Khorasani-Ghassab

Partner:

Avid Technologies Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

Concordia University

Program:

Accelerate

Development of Structural Health Monitoring Strategy for Port Cranes using a Sensor Network

Fatigue failure is one of the most common failure modes in steel structures when subjected to variable or repeated loading. Involving repeated loading, moving, and unloading containers, the quayside ship-to-shore cranes are prone to develop fatigue-induced cracks. Non-destructive inspection methods are mostly used in port cranes to detect fatigue-induced cracks. However, the methods have uncertainties on the initiation and location of the fatigue cracks and they must be manually and periodically conducted, which results in significant downtime and inspection efforts. This research project is to improve the current inspection practice by developing a method for more accurate identification of potential fatigue damage in the port cranes based on structural health monitoring techniques. The outcome of this project will improve the competence of the industry partner by extending its market converge to structural performance assessment.

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Faculty Supervisor:

Oh-Sung Kwon

Student:

Xu Huang;Jamin Park

Partner:

Titan International Industries Limited

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Let’s Do This Together! Developing a Knowledge-based Documentary Media, Community of Practice and Institute at the University of New Brunswick

Academic institutions and funding agencies are increasingly asking their researchers to conduct more outreach activities, including knowledge-mobilization endeavours. However, researchers often lack training and/or resources to effectively communicate with non-academic audiences. Using the DOCTalks Guide: Cross-sector Collaborative Practices for Knowledge-based Documentary Media, we propose a DOCTalks Institute for Knowledge-based Documentary Media and an associated Community of Practice at the University of New Brunswick. This project will employ one PhD intern for 12 months to conduct primary research using face-to-face interviews and online surveys in order to a) Identify UNB??s policies and procedures to establish a DOCTalks Centre; b) Prepare and execute a strategic plan to operate and fund the DOCTalks Centre at UNB; and c) Promote the Centre to other UNB faculties and research services. To test the efficacy of the Centre, the intern will study the documentary media project referred to as “APPLIED CANNABIS” providing an ethnographic account of the social practices that emerge as participants engage with each other on a documentary film. This investigation will identify skills, resources, and funding opportunities that will help encourage other researchers to produce knowledge-based documentary media as part of a their knowledgemobilization activities.

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Faculty Supervisor:

Paul De Decker;Rob Moir

Student:

Stephany Peterson

Partner:

Doctalk Inc

Discipline:

Other

Sector:

Information and cultural industries

University:

Program:

Accelerate

Emergency Management Planning for Indigenous Communities

For Indigenous communities, emergency management involves adopting community strategies and activities that meet the health and safety requirements of citizens while protecting, sustaining and enhancing the community infrastructure and resources that will be needed in the future. This research project will consider recent developments that resulted from the COVID-19 global pandemic and will explore how to promote collaborative emergency management planning between Indigenous governments and external stakeholders. The research will involve three steps: first, a review of current emergency management strategies employed by federal/provincial/territorial governments; second, a review of how emergency management strategies can be integrated into the administrative structures of Indigenous governments; and, third, a theoretical assessment of how to enhance the coordination of emergency management planning by Indigenous governments with external stakeholders in accordance with the inherent Indigenous right to self-determination.

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Faculty Supervisor:

Brent Mainprize;John Borrows

Student:

Wilfred Chanze Gamble

Partner:

Brian Payer and Associates Inc

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

A Principled Approach to Developing Machine Learning Models for the Synthesis of Structured Health Data

Under the current pandemic of Covid-19, sharing health record data has tremendous benefits to control the spread of the infection and save lives globally. In medical research and discovery, Electronic medical records (EMRs) play the essential role for medical discovery in two categories, namely 1) cross-sectional study and 2) longitudinal study. Cross-sectional study compares different population groups at a single point in time while in longitudinal study, researchers conduct several observations of the same subjects over a period of time. Sharing EMRs across medical institutes in a wide scale, both risk the privacy limit of patients. Recent research has been developed to mitigate risk including record simulation via advanced neural networks. While showing promise in certain applications, these models have limitations in handling cross sectional heterogeneous data and have not been applied to longitudinal EMRs. This proposal aims to develop a principled approach with rigorous methodology to derive (a) machine learning models to synthesize EMRs of health data and (b) utility analysis of the data synthesis.

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Faculty Supervisor:

Yan Liu;Linglong Kong;Bei Jiang

Student:

Yushi Jing;Lei Ding;Yangdi Jiang

Partner:

Replica Analytics

Discipline:

Engineering - computer / electrical

Sector:

Information and cultural industries

University:

Program:

Accelerate

3D Foot Scanner from Single View Smartphone & 3D Shoe Fit Computation

As a global leader of industrial footwear insoles, MegaComfort is actively engaged in developing innovative products to maintain healthy workers and prevent injuries. The goal of this research project is to provide a system that is able to scan a human foot from a single image or sequence of images (video) and be able to see how good of a fit the virtual 3D foot has when presented with a shoe cavity. The first objective of the project is to improve the architecture of the technique and provide viewpoint and operating performance requirements for use. The second objective is to develop algorithms that are able to register the 3D scanned foot point cloud model with a given point cloud shoe cavity model with the added constraint that the foot model should fit into the shoe model

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Faculty Supervisor:

John Zelek

Student:

Georges Younes;Frederic Boismenu-Quenneville

Partner:

MEGAComfort International Inc.

Discipline:

Engineering

Sector:

Other

University:

University of Waterloo

Program:

Accelerate

Autonomous Stair-Climbing Domestic Service Robot

The main goal of this project is to develop a more advanced version of the Robotic Stairclimbing Assistant (ROSA), a stair-climbing domestic service robot developed by Quantum Robotic Systems. ROSA can carry heavier household items (e.g., laundry baskets, bins, etc.) between rooms and up stairs. ROSA is meant to help seniors, people with compromised mobility, and isolated individuals cut off from caregivers during the COVID-19 crisis. The research conducted in this project will enable ROSA to use sensors and control software to navigate automatically along paths in your home that may include staircases. For example, starting point “A” could be a main-floor laundry room while ending point “B” could be an upstairs bedroom. The result will be a highly capable product that is unlike any other household robot currently available.

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Faculty Supervisor:

Ryan Billinger;Simon Yang

Student:

Matthew McEachern;Giang Dang

Partner:

Quantum Robotic Systems Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

Program:

Accelerate

Impact of Livestock Grazing on Grassland Herpetofauna

Grasslands cover approximately one third of the Earth’s surface but are among the most threatened and least protected habitats. Livestock grazing is one management strategy to restore degraded grassland ecosystems, but little is known about the effect of grazing on grassland reptiles and amphibians (herpetofauna). World-wide, herpetofauna are in decline and may be particularly susceptible to impacts from grazing. The goal of this project is to understand how grazing in mixed-grass prairies affects grassland herpetofauna species-at-risk using coverboard arrays to locate herpetofauna and quadrat surveys to characterize plant diversity. We will determine: 1) how grazing affects biotic (plant and herpetofauna species) and abiotic (thermal and moisture) environments, and 2) how biotic and abiotic environments change on a gradient from forest edge to the center of a mixed-grass prairie. Understanding the potential impacts of grazing will assist Nature Conservancy Canada (NCC) in management of mixed-grass prairie habitat throughout western Canada.

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Faculty Supervisor:

Pamela Rutherford

Student:

Candace Park

Partner:

The Nature Conservancy of Canada (MB)

Discipline:

Biology

Sector:

Other

University:

Brandon University

Program:

Accelerate

Deep learning-driven strategies for COVID-19 Detection and Risk Stratification

A critical step in the fight against COVID-19 is effective screening of infected patients for infection detection and risk assessment. While viral testing such as rt-PCR is the gold standard for infection detection as it is highly specific, it is moderately sensitive and is a very time-consuming, laborious, and complicated manual process that is in short supply. While faster viral testing methods are becoming available, they remain in short supply and do not provide important information on severity and extent. The goal of the proposed project is to investigate and develop deep-learning strategies for COVID-19 detection and risk stratification based on chest radiography. The objectives are designing tailored deep neural networks for COVID-19 detection for both chest X-ray and CT; risk stratification for both chest X-ray and CT, as well as strategies for secure clinical decision support.

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Faculty Supervisor:

Alexander Wong;John Zelek

Student:

Alex MacLean;James Lee

Partner:

Rogers Communication

Discipline:

Engineering

Sector:

University:

University of Waterloo

Program:

Accelerate

Utilization of high pressure processing (HPP) to deactivate viruses and pathogens

Hospitals, diagnostic laboratories and medical research organizations have witnessed an upsurge in the generation of biohazardous medical waste during the COVID-19 pandemic. This waste is potentially detrimental to the environment and public health and needs to be adequately decontaminated and disposed. Incineration is the most routinely employed technique to treat biohazardous waste but the method generates a sizable quantity of greenhouse gas emissions and toxic by-products. The current project will assess the efficacy of high-pressure processing (HPP) to decontaminate and reduce the volume of biohazardous waste. HPP is environmentally sustainable, economical and scalable to meet the current need of Canadian hospitals and also offers the added benefit of generating source material for the development of vaccines against COVID-19. The proposed project will bring together the laboratory of Vikramaditya Yadav at the University of British Columbia, one of the leading research groups in synthetic biology and bioprocessing in Canada, and AvantGarde, which operates BC’s only tolling HPP facility, and will deliver an economical and practical solution to the medical waste disposal problem that has been compounded by COVID-19.

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Faculty Supervisor:

Vikramaditya Yadav

Student:

Roza Vaez Ghaemi;Gaurav Subedi

Partner:

AvantGarde Coatings

Discipline:

Engineering - biomedical

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

Accelerate

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