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

Synthesis of Graphene Quantum Dots with Blue and Red Emissions from Albany Graphite

Among various types of graphitic nanomaterials, graphene quantum dots (GQDs) have ignited tremendous interest in the past few years owing to their small lateral size, quantum confinement, and large perimeter per mass. GQDs are categorized based on their emitting colors (e.g. blue, green, yellow, red and white). Among various emitting colors, GQDs with blue and red emission are of paramount importance and used in a wide array of applications, such as bioimaging, LEDs, transistors, waste-water treatment, solar cells, biosensors and drug delivery. Our industry partner, ZEN Graphene Solutions Ltd. (“ZEN”), has discovered a large and very rare igneous-related graphite deposit in Northern Ontario called the Albany Graphite Deposit [www.zengraphene.com]. This research project aims to generate the knowledge and expertise for ZEN to convert Albany graphite into high-value GQDs. This research project will be conducted by 2 HQP (1 PDF and 1 MASc) over one year with 7 major tasks.

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Faculty Supervisor:

Mohammad Arjmand;Mohammad H Zarifi

Student:

Ali Akbari Sehat;Sara Dordanihaghighi

Partner:

ZEN Graphene Solutions Ltd

Discipline:

Engineering - other

Sector:

Mining and quarrying

University:

Program:

Accelerate

Pneumatic Based Clean Powering Options for Buses

This project aims to develop a pneumatic (compressed air) powertrain to be used in a 40-feet bus for municipal transit and school buses. Since the transportation sector is one of the prior contributors of Canada?s GHG emissions ( 24%), any alternative solutions to conventional vehicles carries significant importance to reach the GHG target that Canada promised under Paris agreement. Due to the nature-friendly characteristic of the developed system, it may contribute to achieving the GHG emissions target. Interns involving in this research project will have a significant opportunity to apply their theoretical knowledge to the field and get an excellent experience to further develop their abilities. The partner organization will utilize this research to expand the business and have the upper hand over the competitors. On top of all, ecological problems due to GHG emissions and possible solutions will be pointed out once again through this research project.

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Faculty Supervisor:

Ibrahim Dincer

Student:

Ali Karaca

Partner:

Air Lab Inc

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Ontario Institute of Technology

Program:

Accelerate

Quantifying the contribution of physical contact to athlete training load and performance in women’s rugby sevens

The combination of high-speed running and contact in a rugby sevens (sevens) match is tiring and potentially harmful to athletes. Closely monitoring athlete training loads improves in-game performance and protects from injury. Non-contact injuries, including those from sprinting, account for 10.0% of women’s sevens injuries, making contact-related injuries, including those from tackles, far more common. The velocities and forces of collisions have been studied in men’s rugby union, league, and sevens using wearable technology like GPS units. However, limited information exists describing contact in women’s rugby. There is a major gap in understanding of the effects of contacts on performance outcomes in women’s sevens. This project will develop models to explore the physical and tactical outcomes from contacts in games. This will support improved athlete monitoring and management; keeping athletes safer and helping teams win games.

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Faculty Supervisor:

Marc Klimstra

Student:

Amarah Epp-Stobbe

Partner:

Canadian Sport Institute Pacific

Discipline:

Physics / Astronomy

Sector:

Arts, entertainment and recreation

University:

University of Victoria

Program:

Accelerate

Optimizing the placement of Med-El’s BoneBridge implant: image-guided positioning and biomechanical efficiency – Year two

Med-El’s BoneBridge implant provides the sensation of sound to hearing-impaired persons. The device’s transducer is surgically implanted in the skull. Key surgical problems are to find a location on the individual patient’s skull that is thick enough to house the transducer and to place and configure the transducer to maximize sound energy transfer to the cochlea, the organ of hearing. This project will (1) develop software for patient-specific, image-based BoneBridge placement planning and (2) investigate how BoneBridge placement and configuration affect energy transfer. The software will allow surgical planning by identifying the best position(s) for the implant from clinical images taken preoperatively. Our biomechanical investigations provide guidelines to surgeons on optimizing device performance by providing information on sound energy transfer patterns in various implantation scenarios. Med-El, surgeons and patients will benefit because the software and guidelines we develop will make implantation easier, safer, and optimal.

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Faculty Supervisor:

Hanif Ladak

Student:

Seyed Alireza Rohani

Partner:

MED-EL Canada Corporation

Discipline:

Medicine

Sector:

Manufacturing

University:

Western University

Program:

Elevate

Using Deep Learning to Leverage Data Transfer and AI in Smart Vehicles

Smart autonomous vehicles have now become a reality while the efforts are ongoing to improve the safety, security, efficiency, and performance. In the fast paced digital world, all devices including the vehicles generate a huge amount of data every second which has to be analyzed, stored, and communicated with other devices to reach the next technology milestone. Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Device (V2D) communication protocols enable such communications for the smart connected vehicles. Ongoing research is focusing on further optimizing the information processing and data transfer technology to build a scalable and fault tolerant smart vehicle information system that uses a cloud infrastructure and massive parallel stream processing. We will build deep learning models to extract useful knowledge and data patterns from streaming vehicular data with a view to create a minimalistic and standardized dataset that can be efficiently transferred to other vehicles or to the cloud infrastructure for further analysis.

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Faculty Supervisor:

Farhana Zulkernine

Student:

Priyanka Trivedi

Partner:

Canadian Urban Transit Research and Innovation Consortium

Discipline:

Computer science

Sector:

Transportation and warehousing

University:

Queen's University

Program:

Accelerate

Objective Assessment of Suicide Ideation using Measures of Electrophysiology Data and Machine Learning

Digital Medical Experts Inc. (DME) is a Canadian start-up company in the business of developing cloud-based point-of-care monitoring systems for the management of psychiatric illnesses. DME has developed algorithms to diagnose and predict optimal treatment for major depression disorder and schizophrenia, and has been allowed patents describing its technology in Canada, the USA, and Australia.
As part of this proposal I will be working with DME to develop and assess the viability of an objective measure of suicide risk taken directly from electroencephalogram (EEG) and electrocardiogram (ECG) recordings. We have already shown that particular interactions of electrical signals in the brain, known as cross-frequency couplings, can be used to characterize brain activity in ways relevant to psychiatric clinical practise. By developing data-driven algorithms, we will examine the robustness of these features for identification of suicidal ideation. If found acceptable the algorithms will be optimized and incorporated into a point-of-care monitoring system (that has already been developed by DME) using portable and wireless dry electrode EEG headsets.

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Faculty Supervisor:

Flavio Kapczinski

Student:

Sinisa Colic

Partner:

Digital Medical Experts Inc

Discipline:

Psychology

Sector:

Information and communications technologies

University:

McMaster University

Program:

Elevate

Development of a UV-LED disinfection system for ice-machines.

Contamination by microorganisms is a well-known problem for commercial ice machines. Frequent applications of sterilizing chemicals are necessary to keep the ice machines sanitary, a costly and time-consuming process. The sources of this contamination are microorganisms associated with the water used as the source for ice production, the incoming air to the ice machine, and the interior surfaces of the ice machine. Disinfection of contamination sources using ultraviolet (UV) radiation inactivates microbes prior to their establishment inside the ice machine. This research investigated the application of UV-based water treatment systems using a novel UV radiation source—UV light-emitting diode (UV-LED)—for efficient disinfection of ice machines. The findings of this research are very important for providing safe ice products cost-effectively by utilizing UV-LED systems.

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Faculty Supervisor:

Fariborz Taghipour;Charles Haynes

Student:

Milad Raeiszadeh Oskouei

Partner:

Acuva Technologies Inc

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of British Columbia

Program:

Accelerate

Developing a virtual reality simulator and an algorithm to assess visual-vestibular interaction (VVI)

The effect of different factors in the field of view on the vestibular (balance) system including color, intensity, object motion, self-motion sensation, etc. are investigated in this study. Electrovestibulography (EVestG) is used to quantitatively measure vestibular responses from the ear canal, noninvasively. Currently, there is an ever- increasing interest among the health-related authorities to use visual stimulation to improve symptoms of vestibular and cognitive disorders. However, these methods have their own limitations such as being subjective (questionnaires), expensive (imaging studies), time consuming and do not provide information over time. The combination of virtual reality and EVestG method will allow us to explore the effect of individual factors in the field of view on the balance system. The repeatability, cost efficiency and objectiveness of our proposed method can have a significant clinical application to explaining vestibular compensation, substitution and rehabilitation.

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Faculty Supervisor:

Zahra MK Moussavi;Brian Lithgow

Student:

Mehrangiz Ashiri

Partner:

X-Bioanalysis

Discipline:

Engineering - computer / electrical

Sector:

Life sciences

University:

University of Manitoba

Program:

Accelerate

Design of a real-time on-site biosensor system to monitor harmful pathogens and protect canola production

Canada is one of the largest canola producing countries. The industry contributes about $20 billion revenue to the Canadian economy. Currently, canola farmers rely on the weather forecast (temperature, moisture, etc.) to decide whether to apply a fungicide. As the Internet-of-Things and sensor technologies get more advanced, farmers are deserved to have better technologies for intelligent farming. In this project, we propose the design of Internet-of-Things devices to monitor Sclerotinia sclerotiorum, a deadly airborne spore for canola. The sensing chip is cheap (less than $10), easy-to-use and internet-connected. The device can perform real-time monitoring of spores on-site. By using such a device, farmers can reduce their use of fungicides. Soils get protected from the fungicide contamination, and consumers can avoid taking in chemically treated canola oil.

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Faculty Supervisor:

Jie Chen

Student:

Lukas Menze

Partner:

Hidaca Inc.

Discipline:

Engineering - computer / electrical

Sector:

Agriculture

University:

University of Alberta

Program:

Accelerate

Assessing Quality of Life for Canadians with Mobility-Limiting Disabilities through use of Emitto Technology: Creation of Implementation and Knowledge Translation Frameworks

Many people in Canada are aging and/or may be living with a disability. These people often have to rely on caregivers, and are limited in what they can do independently. Novalte has developed a SMART technology system that connects to WiFi devices in the home to allow someone living with a disability more independence and control over their home and space. This project will involve creating implementation and knowledge translation frameworks to support a larger research project on the system and help in its rollout to a larger number of users. This will help the company provide information to health authorities and potential funders and users to show that their device helps users and their caregivers life healthier, happier lives.

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Faculty Supervisor:

Joseph Ferenbok

Student:

Naomi Vera Zingman-Daniels

Partner:

Novalte Inc

Discipline:

Biology

Sector:

Health care and social assistance

University:

University of Toronto

Program:

Accelerate

Geographic mapping for small-diameter gas pipelines in a city

Geographic location of a pipeline is important information for pipeline maintenance and fault detection. Usually, the geographic location of a pipeline on the ground can be measured directly with global positioning system (GPS) technology, but it is much difficult to determine the geographic position of an inaccessible underground pipeline in a city. In this research, a new geographic mapping methodology is proposed for small-diameter gas pipelines in a city. A pipeline mapping micro robot equipped with a micro electro mechanical system (MEMS) based inertial measurement unit (IMU) and odometers is developed. The technique of motion identification and measurement is proposed based on the odometers. A new estimation approach is proposed to reconstruct robot path based on the features of a pipeline, the bending angles and the identified motion modes. The geographic location of a pipeline is obtained by the path optimization algorithm. The proposed methodology can help the partner organization obtain the 3-dimensional (3D) map of old gas pipelines in a city, facilitate the maintenance and leak position detection, so as to reduce troubles in the pipeline and avoid economic losses.

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Faculty Supervisor:

Stevan Dubljevic

Student:

Shuo Zhang

Partner:

Cenozon

Discipline:

Engineering - chemical / biological

Sector:

Oil and gas

University:

University of Alberta

Program:

Elevate

Defining epigenetic drivers of primary and metastatic medulloblastoma

Medulloblastoma (MB) is the most common childhood brain cancer. Current treatment for these tumors is invasive involving irradiation of the entire brain and spine. Although some types of MB respond well, others have an abysmal prognosis, and the lack of less invasive therapies means that children undergoing treatment suffer from severe developmental defects and reduced quality of life. Since metastasis (cancer cells which leave initial tumor site and travel to other locations in the brain and spine) is the single biggest risk factor for poor prognosis, the Taylor Lab at SickKids is interested in generating metastatic MB cell models and determine how their characteristics differ from non-metastatic MB cells. Types of MB which metastasize frequently are observed to have aberrations in the processes that control gene expression (epigenetic proteins) in the cell. Changes in gene expression can favorably alter the environment in cells to promote uncontrolled growth and ability to metastasize. By collaborating with the Structural Genomics Consortium (SGC), we are screening metastatic MB cells with their library of chemical compounds that target epigenetic proteins.

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Faculty Supervisor:

Michael Taylor

Student:

Stephen Armstrong

Partner:

Structural Genomics Consortium

Discipline:

Biology

Sector:

Life sciences

University:

University of Toronto

Program:

Elevate

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