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

IoT based Image Processing Analytics and Network Connectivity for Automated Drone Surveillance

Unmanned Arial Surveillance is rapidly gaining acceptance for various applications, such as monitoring of long power transmission lines, pipelines and mass transit systems that extend for hundreds of kilometers. Unmanned Aerial Vehicles (UAVs) such as drones provide the flexibility to reduce costs. In the case of natural disaster occurrence such as earthquake, flood or hurricane, drones can quickly fly over to high risk areas where human access would be impossible or dangerous and provide information for rescue operations, etc. In this project, the goal is to develop an automated drone for surveillance purposes that can provide real-time monitoring for the target application. Hardware and software provided by AirMarket will be integrated in this project. The solution will be used to generate a framework for the next stage drone technology that can make drones fly beyond visual line of sight.

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Faculty Supervisor:

Zukui Li

Student:

Farough Motamed Nasab

Partner:

AirMarket

Discipline:

Engineering - chemical / biological

Sector:

University:

University of Alberta

Program:

Implementation, Parameterization and Validation of a Confinement-Dependent Constitutive Model for Brittle Failure of Rock

With ever-increasing societal demands for mineral and energy resources, mining and civil tunnelling projects are developing deeper and more complex underground excavations. Experiences are showing that the response of rock at these depths is significantly different and much more hazardous than that previously encountered at shallower depths for which many of our current engineering design tools were developed. The research proposed here will be conducted in collaboration with an industry partner with significant experience in underground engineering design, with the objective of implementing and validating new mathematical models developed specifically for rock behaviour at these greater depths. This will be accompanied by research to develop procedures and guidelines for determining the rock mass properties required as input for these new mathematical models. To help validate the new engineering design tools being developed, data from a deep operating mine that has experienced such problems will be used.

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Faculty Supervisor:

Erik Eberhardt

Student:

Masoud Rahjoo

Partner:

Golder Associates

Discipline:

Geography / Geology / Earth science

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

Change detection of wetland vegetation under contrasting water-level scenarios in coastal marshes of eastern Georgian Bay

Great Lakes coastal marshes are economically and ecologically important ecosystems that purify water, reduce flooding risks, and provide habitat for the most diverse community of plants, reptiles, and fish along the shoreline. Most of the coastal marshes in Lakes Ontario and Erie have been destroyed or degraded by land-use changes, but those in eastern Georgian Bay are still in pristine condition; however, water-level fluctuations associated with global climate change and human activities are threatening their ecological integrity. Beginning in 1999, water levels declined to abnormally low levels and remained low for 14 years. Uncharacteristically, this was followed by an abrupt increase in 2014 that have since continued to climb to record high levels in 2020. A survey of fish and plant communities from 2003 to 2019 showed that the quality of the fish communities have deteriorated between the two periods of contrasting water levels. Since the fish community is known to be dependent on the structure and function of the plant community, we hypothesize that the deterioration in the fish community can be attributed to a structural change in wetland vegetation.

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Faculty Supervisor:

Patricia Chow-Fraser

Student:

Prabha Rupasinghe

Partner:

Georgian Bay Great Lake Foundation

Discipline:

Biology

Sector:

Education

University:

McMaster University

Program:

Building Performance Evaluation of Leading Energy Efficient Homes in Southern Ontario

The focus of this project is on building performance evaluation (BPE) in residential houses in Southern Ontario. Eight green homes will undergo BPE to see how well they are performing. The project will compare current building performance to the designed building performance. This comparison can help to see whether a “performance gap” exists. A performance gap is a difference between the actual building performance and the designed building performance. It will use on-site testing, collection of existing data, and observations from residents of the homes. If a performance gap exists, causes will be identified and studied.
The project will benefit Sustainable Buildings Canada (SBC) as they work to improve building standards in Canada. SBC can use the project to grow their understanding of the causes of performance gaps in homes. The knowledge gained from the project can be used by design teams to improve building design in the future.

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Faculty Supervisor:

Mark Gorgolewski

Student:

Laura Goetz

Partner:

Sustainable Buildings Canada

Discipline:

Architecture and design

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

Simultaneous localization and mapping using a magnetic quantum sensor

Vehicles that are able to autonomously move in the air, on the ground, or underwater must fuse various forms of sensor data together in order to ascertain the vehicles location relative to objects or a map. Typical sensor data includes inertial measurement unit data and some sort of positioning data, such as GPS data. However, positioning data is not always available, especially indoors and underground. SBQuantum (SBQ) has developed a novel quantum magnetometer that can measure the Earth’s magnetic field gradient. This project proposes sensing and mapping the magnetic field gradient using SBQ’s sensor in order to deduce the position of a vehicle or hand-held device. In particular, the focus of this project is the research, development, testing, and deployment of a navigation solution using magnetometry data provided by SBQ’s quantum magnetometer, as well as assessing just how reliable and accurate a magnetometry-based navigation solution is. The proposed navigation solution can potentially be used as an inexpensive means to position vehicles or hand-held devices such as smartphones in, essentially, any environment, when GPS is not available.

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Faculty Supervisor:

James Richard Forbes

Student:

Natalia Pavlasek

Partner:

SB Technologies Inc

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Temporal soft clustering for profiling and predictive analytics in elderly care homes

Nxtgen Care provides monitoring services for elderly care homes across North America. Their product provides detailed analysis in visual formats to understand the resident’s requirements and directing care in that direction. To meet this goal, voluminous data is collected from the various activities of the residents. Through this project, this data is processed and directed in a way to optimize resources for effective scheduling in a timely manner. This is done with the help of advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques. The movements of the residents will be tracked in a timely manner to understand the behaviour and scheduling the care accordingly. This project focuses on providing effective care to elderly people along with effective resource management.

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Faculty Supervisor:

Pawan Lingras

Student:

Maria Kuzhippallil

Partner:

Nxtgen Care

Discipline:

Other

Sector:

Health care and social assistance

University:

Saint Mary's University

Program:

Accelerate

In Tune with Global Youth Mental Health

The mental well-being of youth is critical at a personal, familial, and societal level. The rise of mental illness, addictions, and suicide in youth, especially among those living in low- and middle-income countries, is of significant concern. Our global health team at the University of Toronto and Centre for Addiction and Mental Health (CAMH) has focused on providing mental health and positive development curriculums for transitional youth in collaboration with international and local partners. While the benefits of these programs are well demonstrated, youth feedback suggests that other novel approaches may enhance program value and uptake. Music is known to benefit overall health, promote socialization, and divert youth from risky behaviours. In partnership with the CAMH Foundation, we propose to create partnerships with community musicians to enable the integration of music into existing mental health education programs for disadvantaged youth in Canada, Central America, and Asia. We anticipate that the integration of music will help create a platform for self-expression and bonding that encourages learning and dialogue regarding mental health and addictions, and that promotes well-being.

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Faculty Supervisor:

Arun Ravindran

Student:

Angela Paric

Partner:

CAMH Foundation

Discipline:

Other

Sector:

Other services (except public administration)

University:

University of Toronto

Program:

Development of an advanced Control Strategy for chemical dosing in sewers

The process of chemical dosing in sewers for mitigating the effects of odor nuisance and corrosion needs a lot of improvement in terms of on-line control of the variable amount of buffered iron salt that needs to be applied for different operating conditions and different sewage flowrates. In order to achieve this goal, this project aims at developing a lab-scale sewer simulator which operates in a similar manner to sewage water networks. This system will also be modelled and analyzed in terms of the chemical and biological aspects of the process of chemical dosing as well as the typical sewage flow patterns encountered. A control algorithm will be developed and tested that enables this dosing process to happen efficiently so that costly chemicals will not be wasted and hydrogen sulfide effects in sewers will be mitigated.

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Faculty Supervisor:

Anthony G Straatman

Student:

Mahmoud Elhalwagy

Partner:

USP Technologies

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Western University

Program:

Defining epigenetic drivers of primary and metastatic medulloblastoma – Year two

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:

Professional, scientific and technical services

University:

University of Toronto

Program:

Elevate

Resistant Starch Prebiotic Effects in Chronic Kidney Disease (ReSPECKD) study – Year two

Chronic Kidney Disease (CKD) is associated with a reduced quality of life and an increased risk of kidney failure, cardiovascular events, and all-cause mortality. The goal of this project is to investigate whether the consumption of resistant potato starch (RPS) in addition to current standard care for CKD will reduce uremic toxins and symptoms by altering gut microbiota in patients with CKD. Strategies to reduce the production of these toxins by the gut microbiome in patients with CKD are highly desirable because they may lead to reduced symptoms and delay the onset of dialysis. A clinical trial will be conducted at the partner’s site, the Chronic Disease Innovation Centre (CDIC), to investigate the impact of RSP consumption on gut microbiota and whether these changes impact the concentrations of uremic toxins and uremic symptoms in patients with CKD. Delaying the onset of dialysis in a patient by 6 months has the potential to save upwards of $30,000 in healthcare expenditures. CDIC works with the Manitoba Renal Program which oversees the care of patients with CKD in Manitoba. The Elevate Fellow will support the start up and completion of the clinical trial at CDIC.

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Faculty Supervisor:

Dylan MacKay

Student:

Maryam Shamloo

Partner:

Seven Oaks Chronic Disease Innovation Centre Inc

Discipline:

Epidemiology / Public health and policy

Sector:

University:

University of Manitoba

Program:

Elevate

Data – Driving Recovery in the aftermath of COVID-19’s 1st Wave, Steadying for the 2nd

Numerous studies in the application of Machine Learning to mental health have demonstrated a range of benefits in the areas of diagnosis, treatment and support, research, and clinical administration. COVID-19 is an unprecedented health crisis causing a great deal of stress in populations in Canada. In this project, our aim is to apply practical machine learning approaches to study whether the effects of medical cannabis can help address anxiety, depression and sleep challenges exacerbated by COVID-19. Patient reported scores in the standardized medical questionnaires will be used to determine which specific cannabinoid therapy dosing regimens (Eg: High CBD versus Balanced CBD/THC versus High THC) are effective and, specifically, for which particular subsets of patients experiencing anxiety, depression and/or sleep challenges. The significance of this project is to advance the clinical delivery of precision-based cannabinoid medicine to address the SUA/MH (substance use and abuse/mental health) challenges COVID-19 is presently exacerbating.

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Faculty Supervisor:

Sheela Ramanna

Student:

Negin Ashrafi

Partner:

Ekosi Health

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Winnipeg

Program:

Accelerate

Workforce Innovation Through Social Enterprise

Social Enterprise is a catalyst for social and economic empowerment and inclusion, and has been identified as an innovative opportunity to address workforce challenges and economic sustainability in Southwestern Newfoundland. The goal of this project is to facilitate evidence-based research and analysis and to disseminate resources and practical tools which encourages and supports social enterprise growth in Southwestern Newfoundland and Labrador as an innovative tool for addressing workforce challenges, supporting rural sustainability, encouraging small business enterprise, and building a stronger economic foundation for the future.

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Faculty Supervisor:

Liam Swiss;Roberto Martinez Espineira

Student:

Celestine Muli;Peace John Godwin

Partner:

Community Education Network for Southwestern Newfoundland Inc

Discipline:

Economics

Sector:

Other services (except public administration)

University:

Memorial University of Newfoundland

Program:

Accelerate

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