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

SARS-CoV-2 Genomics for COVID-19 wastewater tracking

This project aims to develop SARS-CoV-2 genomics tools to apply to the tracking of COVID-19 in municipal wastewater. Detection of SARS-CoV-2 genetic material in wastewater has been used to estimate prevalence of the virus in the corresponding community. This has the potential to be a relatively inexpensive early warning system that is complementary to testing in the clinic. However, genome sequencing to differentiate between lineages or genetic variants, which could be used to track origin of outbreaks, has not yet been applied to wastewater. There are still a number of technical challenges that must be solved in processing the wastewater samples such that the viral genetic material is suitable for sequencing, There are also bioinformatics challenges to solve, related to extraction of meaningful genome sequence information from complex mixtures of microbial communities, and mixtures of different SARS-CoV-2 genetic variants. The two interns will therefore directly address these two challenges, with one of them focusing on genome sequencing, and the other on bioinformatics.

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Faculty Supervisor:

Jozef Nissimov;Trevor Charles

Student:

Danielle Rose;Isaac Ellmen

Partner:

Metagenom Bio Inc.

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Development of advanced planning and estimating model for scaffolding manhour

Heavy industrial construction projects consist of oil refinaries which generally involve complex structures, large-scale sites, and large numbers of workers from different disciplines such as civil, mechanical, and chemical. These disciplines may require similar or completely different scaffolding systems in order for workers to not only access their working areas but also move material horizontally and vertically. The variability of scaffolding systems required by the different disciplines operating on these complex sites can be a primary cause of increased project costs and project time delay. Due to this variability, construction company is challenging to estimate and plan the scaffolding time and cost accurately and efficiently. In practice, scaffolding is estimated and planed by 60% of the total project cost or approximately 30–40% of the total man-hours of construction works in the project. This approximate planning and estimating method leads to be difficulty to complete the construction projects on-time within the budget. To eliminate current scaffolding estimating and planning practice, this research proposes to develop a scaffolding manhour predictive model using an artificial neural network (ANN) algorithm which is a deep-learning algorithm.

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Faculty Supervisor:

Sang Han

Student:

Wenjing Chu

Partner:

PCL Industrial Management Inc

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Concordia University

Program:

Accelerate

Semantic Search and Visualisation using Machine Learning and Natural Language Processing

This project tackles the issue of knowledge incompleteness and lack of domain coverage in resume and job posting matching caused by the exploitation of domain-general resources. A variety of co-operative semantic/ontological resources will be used to filter out irrelevant resumes. A two-way (candidate to job and job to candidate) semantic-based automatic suitability ranking is proposed. The suitability is determined by the semantic distance of resumes and job postings, evaluated by their word embeddings. An efficient semantic space created through the Convolutional and Recurrent Neural Networks will be utilized with different word embedding mechanisms along with different classification methods. The project also investigates the potential of knowledge graphs in illustrating inconsistencies between the resumes and job postings. This study develops an automatic system capable of precisely detecting, extracting, and visualizing the resume and job posting’s relevant skills as well as the implicitly encoded semantic dimensions of applicant resumes.

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Faculty Supervisor:

Behrouz Far

Student:

Elias Abdollahnejad

Partner:

HireGround Software Solutions

Discipline:

Engineering - computer / electrical

Sector:

Administrative and support, waste management and remediation services

University:

University of Calgary

Program:

Accelerate

Design, Development, and Control of the Battery Management Systems (BMS) for Off-road Vehicles Built by Dumur Industries

The objective is to design, develop, and test the power system in a next-generation rough-terrain utility vehicle developed by Dumur Industries, with particular focus on the battery used and its own power management system. The vehicle propulsion is via tank-type tracks that transmit power from the front to the back wheels via continuous chain-type tracks.
The vehicle runs on a Diesel Internal Combustion Engine (ICE) connected to a generator. The generator provides a high-voltage (HV) DC link to the battery bank and also to two Electro Motors (EM) driving the two front wheels, via multiple converters, independently. Independent control of these EMs can generate turning maneuvers along with straight-line motion.
In this context, the following sub-projects will be carried out:
• Design and development of the battery system and its connection to the ICE + generator and the Motors.
• Design, development, and testing of the internal BMS and external BTMS system.
• Development of a predictive maintenance algorithm for the BMS/BTMS.

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Faculty Supervisor:

Mehran Mehrandezh

Student:

Mehdi Hedayatpour

Partner:

Dumur Industries

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Regina

Program:

Accelerate

Digital Distribution and Online Resources for e-Learning

This research will help VUCAVU.com, a non-profit online streaming platform for independent Canadian film and video artworks, determine how best to serve a widening range of users and partners given growing interest prompted by COVID-19 restrictions. The primary focus will be on educational stakeholders who need online access to audio-visual resources due to significant expansion of remote-learning programs. Other users to be included in the research include arts organizations who are engaged in or need access to online programming and presentation solutions to continue their activities. From this research, we will establish best practices for the media arts sector and sustainable working models that serve not only the needs of VUCAVU.com’s users but also ensure fair compensation for the creators and rights holders of artworks on streaming platforms. This will ultimately contribute to the financial viability, resilience, and overall success of the VUCAVU platform.

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Faculty Supervisor:

Michael Zryd

Student:

Emily Collins

Partner:

VUCAVU

Discipline:

Medicine

Sector:

Information and cultural industries

University:

York University

Program:

Accelerate

Understanding customer behavior in usage of secure and reliable IoT devices: Industrial, commercial, and residential approaches

The main objective of this research project is to determine the factors that can be used to understand customer behavior associated with using secure and reliable IoT devices. This will allow for non-intrusive products to be designed with more reliability and less security risks. This will require an in-depth study into user behavior, user experience, IoT network security, reliable protocols, and product design. The completion of this project will allow Deprolabs Technology to develop a framework for designing and developing any new IoT product that could be adopted by all industrial, commercial, and residential users.

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Faculty Supervisor:

Srinivas Sampalli

Student:

Majid Nasirinejad

Partner:

Deprolabs Technology Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Food Convergent Innovation Canada Start-Up:Developing data and methods to support the digital backbone of the agri-food system in the Covid19 context

Food Convergence and Integrity (FCI) Canada is being formed to help agri-food companies mitigate the disruptions of Covid-19, increase interactions and innovations among Canadian agrifood companies and enable new agrifood business streams. Through its member platform, it will enhance resilience and competitiveness of the Canadian agri-food sector, resulting also in increased food security for Canadians.
This Mitacs supported research project supports the formation of FCI Canada, bringing together researchers from a multitude of disciplines and institutions, to develop a comprehensive map of the agri-food sector and insights that serve to guide companies and consumers through the COVID19 disruption, recovery, and reimagination of a resilient and vibrant agri-food sector serving Canadians from coast to coast to coast.

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Faculty Supervisor:

R. Sandra Schillo;Laurette Dube;Jian-Yun Nie;Anna-Liisa Aunio;Francine Rodier;Hugues Plourde

Student:

Caiyi Zhao;Ye Zoey Zhu;Hassan Ebrahimi;Yang Yang;Keerthana Nallamari Devanand;Taowa Munere-Tardif;Jiaqing Murphy;Camille Bielza;Julia Ortiz;Erica Kao;Marilyne Chicoine

Partner:

Bivizio

Discipline:

Computer science

Sector:

Agriculture

University:

Program:

Accelerate

Therapeutic Properties in Landscape Design

This research project aims to review, analyze and build upon the current body of knowledge concerning the therapeutic potential of landscape design. It will review the health outcomes of natural settings at healthcare facilities and examine the design processes behind these. Project partner Virginia Burt Designs is a leading practitioner in this aspect of the field of landscape architecture. By comparing the research with targeted case studies of VBD’s work, the final product of this research will provide tangible design guidelines, reinforcing and expanding on established principles, that will be of functional use to landscape design professionals.

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Faculty Supervisor:

Martin Holland

Student:

Timothy Bailey Edwards

Partner:

Virginia Burt Designs

Discipline:

Environmental sciences

Sector:

Professional, scientific and technical services

University:

University of Guelph

Program:

Accelerate

Development of Machine Learning Algorithms for Inferring Biomarkers Underlying Multi-Modal Physiological Signals of Patients with COVID-19

COVID-19 is a global pandemic disease and the best way to stop it is controlling its spread and treating the infected individuals. Detailed measures of clinical characteristics and outcomes in patients with COVID-19 like Reverse transcription-polymerase chain reaction (RT-PCR) are not accessible to a large population and require patients to spend hours waiting at the hospitals. As well, it is not yet known that the lung is the only host of this virus; an inflammation of the heart has been recently reported in patients with COVID-19. Most recent studies imply that COVID-19 might directly impact on the heart. Therefore, relying on one method for detecting COVID-19 is not sufficient, multi-modal sensors indicating different physiological activities are required. There is no unique solution to capture different but relevant physiological signals underlying COVID-19. Given medical imaging techniques (chest CT scans), pulmonary function tests (PFTs), and electrophysiological recordings (e.g., ECG and blood pressure) of patients with COVID-19, we, in collaboration with Dena Corporation and University of Toronto, aim to develop machine learning and signal processing algorithms for detecting biomarkers underlying COVID19 and inferring their correlational patterns.

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Faculty Supervisor:

Milad Lankarany

Student:

Behnaz Poursartip;Idir Mellal;Vaibhav Bachuwar

Partner:

Dena Corporation

Discipline:

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

North Perth Ontario: Developing a Response Plan

The consequences of the COVID-19 pandemic are far-reaching and extend beyond the spread of the disease and efforts to quarantine it. With emergency management efforts underway, opportunities exist to develop more effective and efficient response measures to increase the resiliency of our communities amidst this and future public health crises. Developing impactful resilience strategies requires a regional- and community-scale focus. While most Canadians live in urban centres, nearly 20% of the national population resides in small and/or rural centres. Across Canada’s rural landscape are communities facing unique realities, complex challenges, and numerous opportunities. In partnership with The Salvation Army – Listowel, this project will examine North Perth County as a case study to explore what planning activities are required in small and rural communities to best support ongoing recovery efforts and to increase resiliency and well-being over the long-term. Outcomes from this project will support rural communities to develop effective local policies and planning strategies to respond to the coronavirus pandemic and future disruptive events.

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Faculty Supervisor:

Leith Deacon;Wayne Caldwell;Silvia Sarapura;Sara Epp

Student:

Patricia Butt

Partner:

The Salvation Army

Discipline:

Environmental sciences

Sector:

Other services (except public administration)

University:

University of Guelph

Program:

Accelerate

Myant Response To COVID-19 Pandemic – Research and Technology Development for Smart Textile Solutions

A textile-based solution to remotely and continuously monitor COVID-19 symptoms
Myant proposes to create a wearable textile solution with a compact electronic module able to record ECG, breathing movements, chest motion and sound, skin temperature, and blood pulse (oximetry and pulse shape to estimate blood pressure) in order to monitor key physiological metrics for individuals with and without Covid19, from their residence, geriatric care, or hospital ward, and communicate those metrics to health care professionals to detect health changes and support medical decision.
Building A Novel, Innovative, Scalable and Sustainable Canadian Filtration System for PPE Facemasks
Develop and scale the manufacturing of PPE surgical masks and N95 respirators that are washable and reusable, utilizing multi-layer filtering, anti-viral, and anti-bacterial fabrics. They are knitted using automated robotic machinery with N95 equivalent textile structures introduced in the production of the mask, minimizing post processing and additional labour or materials. As part of this project the developed solutions will be tested and validated to ASTM F2100 standards/specs.

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Faculty Supervisor:

Ramin Farnood;Nasser Ashgriz;Babak Mohamadpour Tosarkani;David Alter;Reena Kilian;Chul Park;Hani Naguib

Student:

Maryam Ebrahimiazar;Gabriela Chaves

Partner:

Myant Inc

Discipline:

Engineering - mechanical

Sector:

University:

Program:

Accelerate

Elucidating the pathogenesis of COVID-19-related coagulopathies and evaluation of medical countermeasures

Various blood clotting disorders have been associated with COVID-19. The underlying cause of the problem remains unknown. This research project aims to tease out the underlying biological causes and evaluate potential treatments.

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Faculty Supervisor:

Christoph Licht;Edward Conway;Edward LG Pryzdial

Student:

Valentina Bruno;Alexander Leatherdale;Patrícia De Oliveira Benedet;Zhara Naghdi

Partner:

Paragon Ventures

Discipline:

Medicine

Sector:

Professional, scientific and technical services

University:

Program:

Accelerate

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