Innovations 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

Geographic Risk Visualization for Unmanned Traffic Management

Risk evaluation is a crucial aspect of Unmanned Traffic Management (UTM) systems. Risk is calculated for missions involving unmanned systems and includes numerous factors from both ground and air risks. Currently, the risk evaluation and calculation for a mission is done by hand and based on estimations. Furthermore, the final calculated risk for a mission is difficult to conceptualize due to the high complexity of the UTM system and the method of risk calculation. This project aims to develop a system to aid in the conceptualization by providing aggregated data used for risk analysis and visualization techniques of the data and risks through software. Accomplishing this will involve collecting data used in risk analysis, analyzing the data for relevant information, and developing visualizations for the data. This project will benefit the partner organization in becoming an industry leader in Detect and Avoid and UTM systems.

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Faculty Supervisor:

Faramarz Samavati

Student:

Mohammad Hameed

Partner:

Canadian UAVs

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Support cases resolution retrieval

Coveo provides search and recommendation software for customer support systems in which customers can ask for help by entering a case description and, on the other side, support agents must find the solution. In this context, queries to Coveo are in the form of long texts describing a problem and potential solutions are knowledge articles or help documents.
Support cases resolution retrieval (SCRR), at its very core, requires a mapping of casual English text, possibly with grammatical mistakes, to well-formed formal English documents. This mapping problem closely resembles a well-studied problem in natural language processing (NLP) that is neural machine translation (NMT). However, unlike most publicly available datasets of NMT, SCRR aims to map a long query sequence (the support case) to an even longer target sequence (the resolution document). Although, recement language model based approaches such as GPT, BERT, XLNET etc. have provided means of overcoming this issue, practical uses are yet to be explored.

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Faculty Supervisor:

Leila Kosseim

Student:

Farhood Farahnak

Partner:

Coveo Solutions Inc

Discipline:

Engineering - computer / electrical

Sector:

University:

Concordia University

Program:

Accelerate

Relevance of security intelligence data for cyber insurance risk quantification

Cyber insurance is a relatively new and growing insurance product that provides companies with compensation following cybersecurity incidents involving data breaches, business interruption, digital asset loss and/or cyber extortion. The ever-changing nature of cyber technology combined with the lack of a large history of cyber insurance claims makes it challenging for insurance companies to rapidly assess risk and determine appropriate premiums for all of their cyber insurance clients, especially for small-to-medium sized enterprises. This project aims to investigate how security intelligence data products and security-related events at can be leveraged to help The Co-operators better quantify the relative cyber risks faced by its cyber insurance clients.

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Faculty Supervisor:

Hassan Khan

Student:

Anderson Ferneyhough

Partner:

Co-Operators General

Discipline:

Computer science

Sector:

Finance, insurance and business

University:

University of Guelph

Program:

Accelerate

Achieving energy efficiency and quality control during veneer drying with data-driven approaches

Minimizing energy consumption is essential to reduce greenhouse gas emissions. With that in mind, the industry partner wants to transition to a quantitative monitoring approach to simultaneously manage product quality and energy consumption. The intern will work to understand the relationship between raw material characteristics, process parameters, product quality indices, and energy consumption. They will use industrial data and various data-driven approaches to develop an energy consumption prediction model that could then be adapted into an online monitoring system. From the model, the intern will be able to recommend operational guidelines to the industry partner, who will benefit by increasing their understanding of the veneer drying process. This should result in a reduction in production costs and greenhouse gas emission.

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Faculty Supervisor:

Julie Cool;Stavros Avramidis

Student:

Qing Qiu

Partner:

Coastland Wood Industries Ltd

Discipline:

Forestry

Sector:

Manufacturing

University:

University of British Columbia

Program:

Accelerate

Additive manufacturing of high-performance polymer parts for aerospace application

Additive manufacturing (AM), 3D printing, offers flexibility in manufacturing and can process a wide range of materials. In this project, polymers and composites are investigated to increase mechanical performance, and to reduce weight, cost, and lead time of candidate parts. Pratt & Whitney Canada (P&WC) can greatly benefit from AM processes in aircraft engine components. In addition, AM can shorten the engine design cycle, and Research and Development (R&D) activities. This requires investigation of 3D printed parts and the impact of manufacturing parameters on final part properties, e.g. surface smoothness, tensile strength, etc. Available data from previous studies will be gathered and experimental testing on small-scale coupons will be used to fill gaps in data. In addition, large-scale parts will be prototyped, and their mechanical performance will be explored. Along with cost modeling, this project will help P&WC to make strategic decisions regarding the use of AM in its products.

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Faculty Supervisor:

Kazem Fayazbakhsh

Student:

Seyed Miri

Partner:

Pratt & Whitney Canada

Discipline:

Aerospace studies

Sector:

Manufacturing

University:

Ryerson University

Program:

Accelerate

Development of a Novel Flow Diverter Design for the Treatment of Cerebral Bifurcation Aneurysm

Cerebral aneurysm (CA) is an abnormal dilation of the cerebral arterial wall and accounts for more than half a million deaths worldwide annually. Flow diverters (FDs) are commonly used to treat CAs but have deficiencies in certain anatomies. In partnership with Evasc Medical System Inc., whose area of expertise is developing treatments for CA, we intend to develop a new design for the Evasc FD (eCLIPs) to address these shortcomings. Through a stepwise design modification process, we aim to improve the performance of eCLIPs in occluding flow into the aneurysm sac in complex anatomies. Results of this research project will serve as a guideline for Evasc to improve outcomes in a larger population of patients with CA. This project also hopes to establish an enduring partnership with Evasc for future collaborations and serve as a template for developing new technologies for cardiovascular medical devices.

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Faculty Supervisor:

Dana Grecov;York Hsiang;Abbas Sadeghzadeh Milani

Student:

Mehdi Jahandardoost

Partner:

eVasc Neurovascular

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Program:

Accelerate

Coupling the liquid pool and wellbore hydraulic module of the “Prediction andOptimization Software Package” – Part 4

In the last decade optimization is expanded in many applications from food production to sophisticated applications such as engine fuel efficiency. In the proposed package, it is tried to apply optimization techniques along with physics based analytical and semi-analytical methodologies to create a compelling framework which can help thermal-process based oil industry to reduce their GHG and also better evaluate their CAPEX. Many SAGD projects are overspent on their facilities due to under prediction or overprediction of their oil production expectations. this package will help operators to predict their expectations and improve their predictions as more inputs are provided such 4D seismic, temperature and pressure observation wells, production data, and geological characterization.

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Faculty Supervisor:

Apostolos Kantzas

Student:

Farzad Bashtani

Partner:

Ashaw Energy

Discipline:

Engineering - chemical / biological

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Effects of Coating Pre-treatment on the Filiform Corrosion of Aluminum Finishes

This project will evaluate the filiform corrosion (FFC) resistance of aluminum frame, aluminum panels and aluminum glazing bead (when used) via powder coating from Starline Windows Ltd. Currently before coating, aluminum substrates are pretreated with cleaning and etch processes, where an alkaline bath made of sodium hydroxide (NaOH) with drinking or reverse osmosis (RO) water is used. The cleaning process also prepare the surface for pre-enetrant etch (pre-pen etch), Pre-pen etch primarily removes smeared material to prepare a part for subsequent Fluorescent Penetrant Inspection (FPI) processing. The effects of various pre-treatment procedures, i.e., using RO water and subsequent pre-pen etch on the FFC of Aluminum Finishes will be clarified in this study. The overall outcome will help to advance the operations of aluminum cleaning and aluminum etch processing.

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Faculty Supervisor:

Jing Liu;Ahmed Qureshi

Student:

Daniela Arango Vásquez

Partner:

Starline Windows

Discipline:

Engineering - chemical / biological

Sector:

Other

University:

University of Alberta

Program:

Numerical modeling of a novel bucking coil for time-domain electromagnetic geophysics

Geophysical electromagnetic techniques are used to scan the Earth’s subsurface and can be used to help find buried materials of economic, environmental and societal importance. They are especially widely used in mineral exploration. DIAS Geophysical is developing a new geophysical electromagnetic system that will be flown under a helicopter that should be more effective than previous generations of systems. In order to make best use of the system, it is important to reduce the noise at the sensor as much as possible using specialized coils. The work described in this proposal will use computer simulations to characterize the performance of these coils which will allow us to optimize the coil design.

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Faculty Supervisor:

Sam Butler

Student:

Cory Ingram

Partner:

DIAS Geophysical

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Mass Timber Material Estimation Tool for Use in Early Stages of Project Design

A gap exists in the mass timber industry between modelled construction strategies and its corresponding material usage data. Using a tool that associates visualization and corresponding data, material take offs and costing can be better communicated to clients. With research that improves estimations and mass timber implementation in projects, the building industry will be more likely to readily adopt it as a material and its associated benefits including improved construction efficiency, carbon sequestration and construction waste reduction.
This project addresses the aforementioned gap by developing a parametric tool that produces material estimations for Spearhead, a multi-faceted, value-added manufacturing company with a specialization in mass timber solutions. The tool will strive to add value in the integrative design process by providing material usage estimations, potential waste reduction strategies and cost predictions in early stages of project design.

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Faculty Supervisor:

Joshua M Taron

Student:

Nicolas Hamel

Partner:

Spearhead Inc

Discipline:

Architecture and design

Sector:

Manufacturing

University:

University of Calgary

Program:

Accelerate

Oat Conversion to Milk and Nutrient Recovery Optimization

Plant-based beverages are inappropriate alternatives to bovine milk, due to lower protein content and not sufficient amount of essential amino acids. To produce nutritionally complete plant-based beverage with high overall acceptability, the technological interventions and fortification techniques need to be developed. Oat is one of the promising raw material for preparation of functional plant-based milk due to the presence of dietary fibres and good nutritional quality of oat proteins. Appropriate complementation of oat proteins with other high nutritious plant protein isolate will enable to produce plant-based beverage with all essential amino acids required for a complete source of protein in a single serving. The applied interventions may lead to process improvements for better quality and performance of plant-based beverages and further growth and global competitiveness of Canadian products in a global market.

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Faculty Supervisor:

Lingyun Chen

Student:

Zhenggang Wang

Partner:

Earth's Own Food Group

Discipline:

Food science

Sector:

Manufacturing

University:

University of Alberta

Program:

Accelerate

Developing a regional approach to modelling the co-benefits urban forest ecosystem services provide.

As the intensities of urbanization and climate change increase across the Toronto region, there are many benefits pointing to a need for increased investments in our regions urban forests. Urban forests provide co-benefits, services that benefit both humans and the environment, through heat mitigation and mitigation of the “urban heat island”, removing air pollution, sequestering carbon, managing storm water run-off and flood reduction, as well as benefits to both physical and mental human health. By using modelling software to project these co-benefits over the next 30+ years across climate change scenarios (low, medium, and high), the necessity of increased green infrastructure across the region will become apparent. It is the hope that the final report generated from these projections will assist in building a business model for investment in the Toronto region’s urban forests in the near future.

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Faculty Supervisor:

Sandy Smith

Student:

Alexandra Farkas

Partner:

Toronto and Region Conservation Authority

Discipline:

Forestry

Sector:

University:

University of Toronto

Program:

Accelerate

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