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

A Framework for Assessing Regulations and Initiatives with Goals and Watson Analytics

Regulations are introduced to ensure the well-being, safety, and other societal needs of citizens and organizations. Yet, regulators often have difficulties assessing the performance of their regulations, and whether regulatory initiatives actually improve compliance. This project’s main objective is to investigate the suitability of a framework combining a standardized goal modeling notation with an existing cloud-based analytics and visualization tool (IBM Watson Analytics) for assessing compliance to regulations as well as the efficiency and effectiveness of regulatory initiatives. The intern will develop goal models for two regulations and companion initiatives from Environment and Climate Change Canada, and use existing data to analyse compliance and performance. Watson Analytics will help understand and interactively visualize correlations and trends. This framework will help regulators detect and understand, in an evidence-based and usable way, which parts of their initiatives and regulations do not work as expected, and enable them to take appropriate improvement actions.

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Faculty Supervisor:

Gregory Richards

Student:

Okhaide Akhigbe

Partner:

IBM Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

Assessing the effectiveness of shorebird roost site conservation strategies through the employment of Open Standards for the Practice of Conservation

The purpose of this project is to conserve critical shorebird roost habitats at high tide in the Minas Basin of the Bay of Fundy in collaboration with recreational beach users, local businesses and tourism operators. The project seeks to develop long-term solutions for creating safe spaces for roosting shorebirds by identifying innovative strategies whose effectiveness can be measured using the Open Standards for the Practice of Conservation protocol. This work will allow BSC to develop an in-house capacity for the protocol as well as a proof of concept guide.

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Faculty Supervisor:

Kate Sherren

Student:

Jaya Fahey

Partner:

Bird Studies Canada

Discipline:

Environmental sciences

Sector:

Environmental industry

University:

Program:

Accelerate

Building Resilience into Canadian Housing

Resilience is toughness, or the ability to function and bounce back after a traumatic event. In this Mitacs research project, the focus is on housing, and resilience results from features that protect Canadian lives and property from natural disasters. One of the ways that governments ensure the safety of Canadians is through The Canada Model Building Code. The insurance industry is also committed to protecting lives and property by contributing advice about resilience in Building Code Review Committees. However, simple resilience measures advocated by the insurance industry are not being adopted in the Code. The current research aims to understand why, and to shed light on the housing industry and its involvement in code revision.

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Faculty Supervisor:

Ruth McKay

Student:

Gary Martin

Partner:

Institute for Catastrophic Loss Reduction

Discipline:

Environmental sciences

Sector:

Environmental industry

University:

Program:

Accelerate

Using machine learning to investigate sympathetic activation of the autonomic nervous system during treatment of mild traumatic brain injury, chronic pain and post-traumatic stress disorder

The goal of the proposed research project is to further our understanding and clinical management of Canadian Forces service members and Veterans suffering from a complex medical triad of traumatic brain injury, chronic pain, and post-traumatic stress disorder. Over half of rehabilitation patients experience one or more of these complex medical conditions, often associated with intractable symptoms which do not respond to traditional treatment options, and impairing their ability to function effectively at work and in the community. Using a Computer Assisted Rehabilitation Environment (CAREN) this research will collect and consolidate a series of non-invasive whole-body biological measurements from patients during immersive therapy sessions in the CAREN Virtual Reality facility. High-performance computing and machine learning will be used to develop and deploy real-time estimators of sympathetic neural activation of the autonomic nervous system (SAANS). TO BE CONT’D

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Faculty Supervisor:

James Green

Student:

Roger Selzler

Partner:

IBM Canada

Discipline:

Engineering - computer / electrical

Sector:

Medical devices

University:

Program:

Accelerate

Numerical Prediction of Mode Splitting on Rotating Disks

This project aims to develop a numerical tool for predicting accurately resonance frequencies of high-heads hydraulic turbines. Both the presence of water and the rotation of the disk-like structure induce shifts in these frequencies compared to a standing disk in air, respectively added mass and mode split. The project is articulated around the following steps: 1) understanding the physical phenomenon causing mode split, 2) developing the numerical tool for natural frequency prediction of a disk, 3) comparing model results with experimental data (communicated by Andritz Hydro) and 4) if time permits, adapt the model to real turbine geometry.
The developed tool will enable the prevention of resonance induced fatigue, which may cause turbines to fail prematurely. TO BE CONT’D

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Faculty Supervisor:

Frederick Gosselin

Student:

Max LOUYOT

Partner:

Andritz Hydro

Discipline:

Engineering - mechanical

Sector:

Environmental industry

University:

Program:

Accelerate

Expanding the Circle of Courage: Understanding the Implementation of the Aboriginal Youth Mentorship Program

In line with Canada’s Truth and Reconciliation Commission, the intergenerational impacts of colonialism influence the health and well-being of Indigenous peoples. In response, culturally relevant programs, which focus on building the strengths of a community have been shown to be effective and sustainable. Indeed, a peer-led, resilience-based afterschool program, the Aboriginal Youth Mentorship Program (AYMP), is effective for preventing obesity and type 2 diabetes in Indigenous children. Based on AYMPs early success, the project has been expanded across Canada. As part of the expansion, AYMP is being transferred out of the ‘academy’ and into Indigenous communities. Therefore, the purpose of this project is to examine how AYMP is implemented across different communities. Specifically, this project will explore how AYMP can be sustained by the community through local ownership and relevance.

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Faculty Supervisor:

Kate Storey

Student:

Frances Sobierajski

Partner:

Safe Healthy Active People Everywhere

Discipline:

Epidemiology / Public health and policy

Sector:

Medical devices

University:

Program:

Accelerate

DC Interconnection Hubs

Conventional power systems are based upon ac voltages and currents. Connecting these systems is a simple matter and is done using transformers. Modern power systems wherein renewable energy sources are increasingly deployed often include dc voltages and currents. Connecting these systems is more challenging as conventional transformers will not be applicable. The proposed research is aimed at investigating and evaluating options for linking and interconnecting dc power systems. Power electronics is the enabling technology for achieving dc system interconnections. Various dc interconnection schemes will be researched and their merits and drawbacks will be thoroughly assessed using detailed computer modeling and simulation techniques as well as experimental work on a scaled down laboratory setup.

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Faculty Supervisor:

Shaahin Filizadeh

Student:

Luo Liu

Partner:

Manitoba Hydro

Discipline:

Engineering - computer / electrical

Sector:

Energy

University:

Program:

Accelerate

Upper Fraser River bull trout management evaluation

Bull trout in the upper Fraser watershed (UFW) of British Columbia are important top predators and serve as the basis of a recreational fishery. Anglers in the region have asked government to consider changing current fishing regulations for bull trout from catch-and-release to regulations that allow them to take a portion of their catch home. Allowing for this regulatory change would increase the types of fishing opportunities in the area but could harm bull trout populations. This is further complicated as there is little information on the ability to sustainably harvest bull trout, and as the species has conservation listing. TO BE CONT’D

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Faculty Supervisor:

Scott Hinch

Student:

Rachel Chudnow

Partner:

Freshwater Fisheries Society of BC

Discipline:

Zoology

Sector:

Environmental industry

University:

Program:

Accelerate

Automatic Modulation Classification using Deep Learning for wireless security applications

Applications of wireless security approaches are increasing in number by the day. One such application is detection and interception of rogue aerial intruders. Drone technology is growing at a tremendous pace and is expected to be a $12 billion industry by 2021. Coupled with this growth comes the increasing threat of rogue intruders disrupting day-to-day activities and sensitive infrastructure. Towards this end, rogue drone detection has become an important industry by itself and focuses on securing the airspace around us. In this project, we aim to build a deep learning framework augmented with traditional signal processing techniques to model and classify unknown wireless signals. This model would be able to learn from the time domain information of the signal (amplitude, phase) and be robust in conditions with varying Signal-to-Noise Ratio (SNR). TO BE CONT’D

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Faculty Supervisor:

Vijay Bhargava

Student:

Kevin Dsouza

Partner:

Skycope Technologies Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

Interoperative Performance Measurement of Surgeons using Deep Learning

Surgery is undoubtedly one of the most important events in a person’s life. It is thus imperative that a feedback system is in place to ensure that proper care is provided to patients during surgery. Currently, such systems involve experienced surgeons watching hours of surgery to determine how well the surgery was performed based on pre-defined criteria. This project aims to assign the surgeon’s performance rating based on data from their previous procedures. In doing so, surgeons will be assigned a technical competence rating based on their performance. A consistent rating will help differentiate surgeons that are very skilled at their craft and ones that require more training. It will also provide surgeons with additional incentive to hone their skills thereby increasing positive outcomes for their patients.

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Faculty Supervisor:

Sanja Fidler

Student:

Shuja Khalid

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Medical devices

University:

Program:

Accelerate

Application of Model Predictive Control to HVAC Systems in Smart Buildings

This project aims at applying the technique of Model Predictive Control (MPC) to control the thermostatic loads in HVAC systems in the context of smart buildings. The main objective of this project is to verify the capability of MPC-base control schemes developed in academic research projects with a real system operated by Fusion in terms of energy efficiency improvement and operational cost reduction. In the first phase, the model of a candidate building will be established and validated for the controller design. Then, the MPC controller will be implemented in centralized and decentralized manner at Fusion Energy’s systems for experimental validation. This project will allow further enhancing the collaboration between the academic research team and the industrial partner in the development of a full set of solutions for demand-side energy management in the context of the Smart Grid.

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Faculty Supervisor:

Guchuan Zhu

Student:

Saad Abobakr

Partner:

Discipline:

Engineering - computer / electrical

Sector:

Energy

University:

Program:

Accelerate

Quantifying the Computation Power and Transaction Latency of Pool Mining in Cryptocurrency Networks

In this project, using such mainstream cryptocurrencies as BitCoin and Ethereum as representatives, the intern will analyze the transaction collection strategies of their mining pools, and then collect transactions and the corresponding blocks data to build a large dataset, from which the computing power of different mining pools and their proportions will be analyzed, together with the transaction latencies of pool mining. We will also identify potential enhancement through the analysis and measurement, particularly on energy and delay optimization. Coinchain is a BC-based startup company focusing on advanced cryptocurrency and blockchain technologies, and their application in industrial and commercial scenarios. It delivers global enterprise-level blockchain solutions to leading companies worldwide, and provides one-stop customized services such as product and information platforms, as well as smart contracts and trading platforms. The interns will work closely with the Coinchain engineers and the outcome will help the industrial partner build a more effective cryptocurrency/token for its blockchain-based solutions.

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Faculty Supervisor:

Jiangchuan Liu

Student:

Lei Zhang

Partner:

Coinchain Capital

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Accelerate

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