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

Process Intensification for Odor Removal in Composting Facilities

Composting is a method of waste management using biological degradation at aerobic condition. Although the process is one of the efficient and least expensive waste management options, nuisance odors emanating from waste processing facilities degrade the air quality of neighborhood. Odor compounds vary significantly depending on the type of wastes, process conditions and include bioaerosols, biomolecules, volatile organics, ammonia, and organic sulphur compounds. Of all the mitigation technologies available for odor control, adsorption on activated carbon or other highly active surfaces, and biofilter are most efficient. In this work, a process intensification using two technologies, namely adsorption and chemical oxidation will be attempted in a single unit for the removal of model odor compounds. The two adsorbents are prepared from waste materials namely petroleum coke and biochar. This collaboration will help the partnering company, Renewi Canada, to mitigate odor problems by augmenting their existing scrubber and biofilter technologies.

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Faculty Supervisor:

Mita Ray

Student:

Banafsheh Khavaran

Partner:

Renewi Canada

Discipline:

Engineering

Sector:

Environmental industry

University:

Program:

Accelerate

Machine learning algorithms utilization for impairment screening using balance detection

In this project the human body movement and its balance will be studied, and artificial intelligence-based algorithms will be developed in order to detect the body movement and the posture in real-time. Specific camera technology will be utilized in order to gather required data of the human movement and the environment. The data will then be filtered and analyzed. The cleaned data will then be used in a artificial-intelligence-based system to detect the status of the movement. Finally, the result of the movement detection will be integrated with other indicators in order to detect the imbalances or visible impairments.

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Faculty Supervisor:

Jiannan Wang

Student:

Vishal Batvia

Partner:

CannSight Technologies Inc

Discipline:

Computer science

Sector:

Medical devices

University:

Program:

Accelerate

High-throughput phenotyping of plant health using machine learning and computer vision

Phenotyping is used to develop new strains of plants, understand plant-affecting diseases (phyto-pathology) and evaluate the effects of various substances on plants. A growing variety of sensors and sensor technology is used to gather data used for phenotyping, in a non-destructive manner, and this overall process of data acquisition and analysis is being automated, leading to high-throughput pheno-typing. These technological changes pose challenges both in terms of which models to apply to these heterogeneous data, as well as the scalability of the data and analytics pipeline. The proposed project aims to develop a deep learning model that would produce estimates of plant health based on imaging and other sensor data generated by Terramera, with high classification accuracy, according to threshold tolerances defined by Terramera plant physiologists. The project would also explore some of the data management challenges arising from the application of those deep learning models on automated phe-notyping data acquisition at scale.

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Faculty Supervisor:

Jiannan Wang

Student:

Fatemeh Renani

Partner:

Terramera Inc

Discipline:

Computer science

Sector:

Agriculture

University:

Program:

Accelerate

Global Dynamic Financial CGE Model

This project aims to develop a dynamic financial computable general equilibrium model (CGE) with interaction between real and financial side of the world economy. It seeks to understand how monetary policy changes such as interest rate changes, QE measures, and exchange rate changes affect the real economy by applying the financial dynamic CGE model. This project collaborates with the partner organization–the Infinite-Sum Modeling Inc.—to build a CGE-FDI database and to develop the financial CGE model. 

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Faculty Supervisor:

Jing Li

Student:

Qianyi Du

Partner:

Beijing Technology and Business University

Discipline:

Business

Sector:

Finance, insurance and business

University:

Simon Fraser University

Program:

Accelerate

Neutral and alkaline bio-heap oxidation of refractory gold ores with adaptive moderate-thermophilic and mesophilic microorganisms

The project has been defined to address the growing concerns of the mining industry towards sustainable copper production with low cost and environmentally friendly process option. The current processes for copper extraction are either expensive or have detrimental impact on the environment. This proposed project pertains to the development of a technology that applied green energy (electricity) as well as ultrasonic technology to recover copper from the main copper minerals (chalcopyrite and enargite) with minimum cost and highest efficiency.

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Faculty Supervisor:

Ahmad Ghahreman

Student:

James McNeice

Partner:

COREM

Discipline:

Visual arts

Sector:

Mining and quarrying

University:

Queen's University

Program:

Accelerate

Financial and Economic Analysis for the Integration of Wind Generation into Electricity Grids

This research effort will measure the impacts that the introduction of wind farms have had on the amount of electricity generated by natural gas fired thermal plants, hydro generation, nuclear generation or the quantities of electricity exported. For this analysis the historical operating information from the Province of Ontario’s electricity system will be used. An ex-post evaluation will be carried out for one or more wind farms operating in Ontario to identify the important parameters that determine the economic feasibility of such investments. A model will be developed for the appraisal of pumped storage facilities to identify the conditions when this technology is both an efficient method for energy storage and a cost effective way of stabilizing the electricity system for the impacts of variability of generation by non-dispatchable renewable technologies.

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Faculty Supervisor:

Frank Milne

Student:

Pejman Bahramian

Partner:

Cambridge Resources International Canada, Inc.

Discipline:

Economics

Sector:

Alternative energy

University:

Queen's University

Program:

Accelerate

The Value of Arts and Culture for Community Cohesion

Although the social, economic, and cultural importance of the arts is generally acknowledged, few studies have collected data on how community members (whether engaged in the arts or not) perceive the value of the arts within their community. This study examines public perceptions of the arts within Saskatchewan’s urban and rural communities. Using a mixed-methods research design that includes a random sample telephone survey and qualitative community-based consultations, the project examines the role of the arts in fostering community cohesion, revealing important insights on the social value and meaning of the arts. The study may also expose significant barriers and facilitators for the arts, and social interconnection more broadly, within rural communities, contributing important insights to the work of arts organizations and cultural policy development.

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Faculty Supervisor:

Amber Fletcher

Student:

Allison Patton

Partner:

Saskatchewan Arts Alliance

Discipline:

Sociology

Sector:

Management of companies and enterprises

University:

University of Regina

Program:

Accelerate

Transactive Electric Distribution System

Electric power distribution systems physically connect the newer active transactive energy (TE) elements such as energy storage, demand response, electric vehicles, and renewables to customer loads and electric supply from the transmission system. The proposal outlines a Transactive Electric Distribution System (TEDS) framework which enables the creation of a robust distribution system market in Canada and elsewhere. It encompasses building three sets of algorithms for optimal planning, optimal operation, and forecasting for the distribution system sector market, one set each for the Load Distribution Operator (LDO) market, aggregators, and prosumers. When implemented, the TEDS framework will unlock the economic potential of TE elements in the distribution sector and enable the flow of private capital into the distribution sector, minimizing the cost of electricity to customers while maximizing reliability.  The TEDS framework provides an informed path forward, advancing Canada’s leadership in smart grid technology and innovation.

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Faculty Supervisor:

Bala Venkatesh

Student:

Amr Mohamed

Partner:

Independent Electricity System Operator

Discipline:

Engineering - biomedical

Sector:

Energy

University:

Ryerson University

Program:

Accelerate

Development of a new compact configuration for enzyme-mediated carbon dioxide desorption unit based on detailed study of desorption kinetic mechanism and local-scale mass-transfer phenomena

The CO2 thermal desorption process in the stripper for the regeneration of solvents is central to the design of CO2 capture process from technical and operational standpoints, requiring huge amounts of energy and posing considerable challenges on plant operation. In order to offer an alternative environmentally-friendly and economical stripping unit, the present project aims to develop a new compact and efficient design for the stripper of CSI’s industrial lung technology based on a new methodology allowing fundamental understanding of CO2 desorption kinetics and predicting CO2 desorption efficiency during the regeneration process. Finally, it will enable CSI to offer a technically and economically viable CO2 capture technology to power generation plants and industrial sectors dealing with the reduction of CO2 emissions.

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Faculty Supervisor:

Faïçal Larachi

Student:

Amir Dashliborun

Partner:

CO2 Solutions Inc

Discipline:

Visual arts

Sector:

Alternative energy

University:

Université Laval

Program:

Accelerate

GIS-based Wildfire Catastrophic Risk Economic Capital Modelling

Models used for Wildfire catastrophe insurance as of today are not considering substantial information, such as geographic information and environmental constraints. The objective of the project is to establish a theoretical framework and an empirical process to enhance Aviva Canada’s current Wildfire Economic Capital (EC) model, to be able to determine the amount of capital needed to be allocated to ensure the company remains solvent, in case of occurrence of risks. The new model will incorporate spatial Geographic Information System (GIS)-based information and other non-spatial information and it will cater for the nature of the heavy-tailed data. It is expected that this approach can be adapted and extended to Aviva Canada’s other natural and man-made Catastrophe risk EC models with similar needs.

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Faculty Supervisor:

Melina Mailhot

Student:

Roba Bairakdar

Partner:

AVIVA Canada

Discipline:

Mathematics

Sector:

Finance, insurance and business

University:

Concordia University

Program:

Accelerate

Development of Persona Models for Banking Customers

In this research we will identify current types of customer, taking into account people who prefer to use a variety of platforms and different preferences in terms of how actively they manage their money. . We will carry out focus groups and interpret the results of a survey in terms of their implications for a set of factors that differentiate between banking customers. Using the factor scores obtained in a survey we will segment into meaningful groups (personas). A focus group will seek to validate the persona model inferred from the data analysis of the survey, and based on the focus groups and survey we will identify a revised set of key factors that underlie banking and investment preferences. The development of an up-to-date Persona model of customers will help TD target its offerings to different customer groups and will also assist it in designing user research activities.

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Faculty Supervisor:

Mark Chignell

Student:

Thanyathorn Thanapattheerakul

Partner:

Toronto-Dominion Bank

Discipline:

Engineering - mechanical

Sector:

Finance, insurance and business

University:

University of Toronto

Program:

Accelerate

Benchmarking Indigenous/Non-Indigenous Employment, Business and Social Development Partnership Capacities in Major Resource Projects

Indigenous communities continue to be excluded from the mainstream economy due to a lack of successful partnerships with non-Indigenous businesses. In this project, we will conduct ‘partnership benchmarking’ with resource companies and Indigenous communities establishing the organizational competencies and capacities needed to accelerate economic development. This project will conduct research resulting in Indigenous communities and mainstream companies to accelerate and grow their partnerships together and thereby build incremental Indigenous employment, business and social development.
We will also develop a learning program and certification system which will catalyze Indigenous/non-Indigenous partnerships. This project has the potential to be transformational by growing opportunities for Indigenous communities to participate more fully in the Canadian economy.

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Faculty Supervisor:

Ken Coates

Student:

Tanja Hoffman

Partner:

Indigenous Works Organization Inc

Discipline:

Public administration

Sector:

Aboriginal affairs

University:

Program:

Accelerate

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