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

Private conservation in a changing landscape: a perspective on Land Trust Organizations in Canada

Land Trust Organizations acquire and protect private land for conservation purposes. They have become the fastest growing tool for biodiversity conservation of private land in Canada. Despite their growth and the recognized importance of private protected areas; there is little information about them. This research aims to understand who the Land Trust Organizations are (e.g. size, level of protection, funding, governance structure, ecological monitoring) and the important opportunities and challenges they face. This baseline information on Land Trusts will contribute to making an informed decision of a nation-wide collaboration model of the organizations. This will support the changing of their political systems, to help humans live within Earth’s carrying capacity.

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Faculty Supervisor:

Jessica Dempsey

Student:

Karen Kalynka

Partner:

Land Trust Alliance of BC

Discipline:

Environmental sciences

Sector:

Other services (except public administration)

University:

University of Victoria

Program:

Accelerate

Active Learning for Fish School Recognition in Echograms in the Bay of Fundy

OERA use hydroacoustic echosounder surveys to evaluate the impact on marine life of tidal turbines in the Bay of Fundy. OERA use Echoview software to read in the raw sensor data (e.g. voltages) and convert it to a visual representation. Echoview contains some algorithms to detect the bottom of the ocean. However, the Fundy data is very noisy from several sources including air bubbles, “entrained air” pushed below the surface of the water, and irregular surfaces on the bottom of the ocean. In order to analyze the survey data, manual pre-processing is currently required to annotate the data. This manual process delays the turnaround, potential consistency and provides opportunity for inconsistency.
This project will train a machine learning model to detect and filter noise in the hydroacoustic sensor data, allowing OERA to improve the accuracy, consistency and manual effort required to pre-process its data. By identifying “bad regions” in hydroacoustic data collected near underwater turbines in the Bay of Fundy with a model to automatically extract these regions from future survey data, OERA will be able to apply greater speed, consistency and accuracy to data processing to prepare for rigorous analysis.

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Faculty Supervisor:

Sageev Oore;Evangelos Milios

Student:

Scott Lowe

Partner:

Offshore Energy Research Association of Nova Scotia

Discipline:

Computer science

Sector:

Mining and quarrying

University:

Dalhousie University

Program:

Accelerate

Machine learning classification for pump fault and failure detection

This project aims to develop an automated ability capable of detecting faults with pumps. This is referred as “Automated Fault Detection and Diagnosis” (AFDD). Equipment performance begins to worsen throughout time due to various reasons, where these reasons are referred to as “faults”. Generally, there is an understanding of the various faults and causes for equipment failure, but the challenge arises in development of a tool capable of accurately and automatically detecting these issues. An AFDD tool would receive sensor data from a pump and use various algorithms to 1) “Detect” a fault and 2) “Diagnose” the exact fault. The expected outcome of this project is an algorithm that can read data from installed equipment and use it to determine whether or not the equipment is (a) operating correctly, (b) operating with a problem (fault), or (c) in danger of failing, and provide both the building owners and Armstrong service team with the necessary information to fix it.

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Faculty Supervisor:

Jennifer McArthur

Student:

Rony Shohet

Partner:

Armstrong Fluid Technology

Discipline:

Architecture and design

Sector:

Manufacturing

University:

Ryerson University

Program:

Accelerate

Bacteriophage Endolysin Proteins Development

In response to the antimicrobial resistance crisis, several nations (including Canada, U.S., and Europe) have drastically limited the use of medically important antibiotics for livestock production. As a result, alternative methods must be explored for disease prevention and treatment in animals from bacterial infections. The intern will explore the effects of using toxic proteins that destroy bacteria derived from viruses that only infect and kill bacteria as a plausible alternative. The benefit of this research to Cytophage Technologies Inc. is the development of a procedure that can be used to test the ‘kill activity’ of future proteins against the growth of bacteria. In addition, if a protein is found that is of high interest (kills different types of bacteria), it can potentially be used to help fight off bacterial infections in livestock anima

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Faculty Supervisor:

Deborah Court

Student:

Klara Wang

Partner:

Cytophage Technologies

Discipline:

Biology

Sector:

Life sciences

University:

University of Manitoba

Program:

Accelerate

Light Weighting Structural Injection Molded Parts for the Automotive Industry

Light weighting in the automotive industry is ever becoming important. The overall objective of this research project with Axiom Group Inc. is to develop an innovative, cost-effective and industry-scale technology that can produce lightweight automotive products with good impact strengths. The project is aiming to achieve the cellular morphology to maximize weight reduction (20-30%) without sacrificing (or even while enhancing) impact properties of the product. This high-performance and more environmentally-friendly automotive product will be developed with zero ozone depletion potential blowing agents to further improve the sustainability of our environment. Various parameters such as material choices, filler/fiber contents, mold designs, processing conditions and others will be investigated in detail. The outcome of this project will offer Axiom a solution to produce lightweight structural injection molded automotive parts in its product lineup in response to the global trend.

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Faculty Supervisor:

Patrick C Lee

Student:

Nello Sansone

Partner:

Axiom Plastics Inc

Discipline:

Engineering - mechanical

Sector:

Automotive and transportation

University:

University of Toronto

Program:

Accelerate

An Integrated model of Geomechanics and a Multiporosity Reservoir Simulator to Investigate Improved Recovery Techniques in Shale Reservoirs-Part 2

Shale reservoirs have become a very important source of hydrocarbons, especially in North America. Shales are rocks with very low permeability and therefore, produce the hydrocarbons stored in them is difficult. In order to do it, oil companies have to inject high pressurized fluids to break the rock. But, by using this unique strategy, most hydrocarbons are being left in the subsurface. This work aims to use mathematical and numerical models to investigate different methods that can lead to recover a bigger portion of the hydrocarbons stored in shale reservoirs. In this study, the application of the developed models will be focused on a particular shale reservoir, but the methodology can be applied to other fields in Canada

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Faculty Supervisor:

Roberto Aguilera

Student:

Alfonso Fragoso

Partner:

CNOOC Petroleum North America ULC

Discipline:

Engineering - chemical / biological

Sector:

Mining and quarrying

University:

University of Calgary

Program:

Accelerate

Intelligent Chatbot Development for the Tourism Industry

This research helps to automate ontology development in order to support semi-supervised and active learning chatbot as much as possible, so that the overhead of chatbot training that requires human supervision is minimized, while relevant knowledge management activities become more efficient. The research objectives are both to refine the quality of the chatbot interactions and to automate its development and training as much as possible, to implement and test its practical and cost saving capabilities in tourism industry.

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Faculty Supervisor:

Diana Inkpen;Liam Peyton

Student:

Arya Rahgozar

Partner:

Spreedix

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Ottawa

Program:

Accelerate

Feasibility of combining monolithically integrated silicon photonics with low cost, high performance, non-hermetic surface-mount technology (SMT) packaging

This project aims at experimentally validating the commercial viability of a new silicon photonics design which provides state of the art monolithic integration of various CMOS control electronics and BiCMOS high speed RF drive electronics which may be combined with high bandwidth non-hermetic SMT packages capable of withstanding standard high volume solder reflow processes. Combining these technologies and their commercialization will have a huge impact on the size and cost of optical communications equipment and serve as a stepping stone in developing technologies for use in future board-to-board and chip-to-chip optical communications in a wide array of industries such as communications, military, and super-computing. The aforementioned research activities will help support ADVA’s plan in new products development by exploring their commercialization feasibility.

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Faculty Supervisor:

David Victor Plant

Student:

Heba Tamazin

Partner:

ADVA Optical Networking

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

McGill University

Program:

Accelerate

Ultrafast laser nano-structuring in transparent glass: enabling 3D fibre-photonics packaging and assembly for high temperature sensing

This Mitacs project addresses a significant barrier the partner company (Fibos Inc.) is facing with their current customers in manufacturing of fibre optical sensors that can be robust and cost effective for the high temperature and pressure environments. The market is aimed at sensing of rotor assemblies in turbines where electrical and other means of measurement are not directly possible. The proposed solution is an “all-glass” optical fibre transducer that eliminates low-temperature adhesives to improve mechanical strength, sensor response, amd product lifetime, while promising higher temperature application. This approach aims for a simple, all-in-one manufacturing procedure by applying a femtosecond laser to both fabricate the optical fibre sensor and to weld the optical fibre to glass substrate to form a robust optical fibre sensing transducer. Successful completion of this project will enable Fibos to establish ultrafast laser production of fibre transducer sensors for the first time in Canada that can work at extreme environment conditions.

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Faculty Supervisor:

Peter R Herman

Student:

Young Hwan Kim;Abdullah Rahnama

Partner:

FIBOS

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Finances of the Nation: Data-driven policy analysis for Canada

The project will foster high-quality analysis of taxation and other public policies in Canada. We will assemble data on public finances of governments in Canada and, to make them more useful for policy analysis, we will transform the data to make them consistent over time and across geographic units of Canada. We will make the data readily available to researchers, policymakers, journalists, and others through an online open data portal. Then, using the data, we will prepare short, focused, and accessible research papers analyzing the data to provide insights into and assessments of public policies in Canada. These research reports will be primarily non-technical in nature and will be published in a variety of outlets and available to all readers.

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Faculty Supervisor:

Michael Smart

Student:

Alexander Hempel

Partner:

Canadian Tax Foundation

Discipline:

Economics

Sector:

Education

University:

University of Toronto

Program:

Accelerate

Development of novel catalytic systems for green-house gas abatement

The use of fossil fuels for energy has led to the significant emission of greenhouse gases from the stationary and automobile sources. Methane (CH4) is an abundant source of fuel found in large quantities in natural gas reserves or produced synthetically is an alternative fuel for motor vehicles, large track transportation, marine application because of its low carbon emission per energy produced. However, methane is a potent green house gas and needs to be fully converted to CO2 to prevent its release into the atmosphere. The present project aims at the development of novel, efficient and cost-effective catalytic systems for elimination of exhaust methane in catalytic converter.

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Faculty Supervisor:

Elena Baranova

Student:

Najmeh Ahledel

Partner:

Besantek

Discipline:

Engineering - chemical / biological

Sector:

Oil and gas

University:

University of Ottawa

Program:

Accelerate

RALI-DX: Rapid Diagnostic Tools for Acute Lung Injury

Sepsis, severe pneumonia and respiratory viruses are key causes of Acute Respiratory Distress Syndrome (ARDS)—a detrimental lung condition that results in >3 million ICU admissions/year and can lead to organ failure and death. In Canada, ~18,000 patients with ARDS are admitted to hospital annually and those requiring critical care place an immense burden on hospital resources. Early detection of ARDS is vital for treatment to be effective. However, there remains a significant gap in precision diagnostics capable of recognizing early acute lung injury leading to ARDS that would enable the delivery of timely and cost-effective interventions. The proposed Mitacs project will focus on the validation of a recently discovered set of biomarkers and algorithms predictive of early acute lung injury, and will be performed on SQI Diagnostics’ novel platform that the team envisions will be integrated into emergency department hospitals worldwide.

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Faculty Supervisor:

Shaf Keshavjee

Student:

Bonnie Tso Yu Chao

Partner:

SQI Diagnostics Systems Inc

Discipline:

Engineering - biomedical

Sector:

Life sciences

University:

University of Toronto

Program:

Accelerate Masters Fellowship

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