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

Prototyping and Industrial Testing of Novel Non-Consumable Thermocouples/Sensor Holders in Molten Steel

Secondary metallurgy is the most value adding step in the steelmaking process. As more sophisticated steel grades are developed, better process control is required to adjust and monitor properties of molten steel in secondary metallurgy. Improved process control also serves to increase productivity and profitability of steel mills. In steelmaking, process control is achieved through feedback from sensors. Unfortunately, existing state-of-the-art sensors for molten steel are consumable, unreliable, and provide limited measurements. This is a major barrier that must be overcome to improve secondary metallurgy processes, productivity, and profitability. This research project prototypes and industrially tests novel non-consumable thermocouple/sensor holders for use in molten steel. Prototyping follows from developments and testing of candidate materials on the laboratory scale. New design, joining, and manufacturing methods will be developed to utilize candidate materials on a larger scale. Experiments will be performed at a Canadian steel mill under steelmaking conditions. Scientific characterization, investigation, and data analysis follows from tested prototypes. The project aims to commercialize advanced materials, improve prosperity of the Canadian steel industry, and place Canada as a recognized innovator in advanced manufacturing.

View Full Project Description
Faculty Supervisor:

Gisele Azimi

Student:

William Judge

Partner:

Tenova Goodfellow Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Opportunities for and impacts of community-scale biomass and waste heat district energy systems in Canada

Solid biomass, of which Canada has plenty, is the lowest cost, and greatest employment generating, renewable heat source available but to date but is not often considered as a low carbon heating option for deployment on a large scale in Canadian cities. For solid biomass to reach a high market share, a key enabling infrastructure is required: district energy systems (DES). While there are existing DES in Canada, they provide less than 2% of all building heat in the country. There is a significant opportunity to develop biomass heating systems in Canadian communities as a low carbon heating solution, however the development of DES infrastructure in existing communities if often viewed as cost prohibitive, and biomass energy in general is not always viewed in a positive light by the public. To address these issues, this project will identify opportunities for biomass DES in Canadian communities and evaluate the economic feasibility as well as the regional social, economic and environmental impacts associated with the development of (community-wide) biomass DES in at least two urban Canadian communities (one using forest biomass, one using agricultural residues).

View Full Project Description
Faculty Supervisor:

Michelle Adams

Student:

Jean Blair

Partner:

TorchLight Bioresources

Discipline:

Environmental sciences

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Identifying and quantifying entrained larval fishes using eDNA and metabarcoding

Monitoring biodiversity using DNA-based approaches has many advantages for large-scale studies. DNA metabarcoding can assess the presence, absence, and abundance of species in a sample where individuals are not morphologically identifiable, such as bulk samples of larval fishes or from environmental DNA (eDNA) in water samples. We propose to develop a high-throughput metabarcoding-based approach that will quantify fishes entrained by the water-cooling system at Bruce Power. This approach will determine the presence or absence of species based on the DNA obtained from bulk larval tissue and eDNA samples. The abundance of each species will be estimated by the proportional representation of each DNA sequence in the sample or by assigning sequences to individuals using approaches similar to those in forensic investigations. These methods will provide a more efficient system for long-term entrainment monitoring and will improve estimates of species loss used to inform mitigation and offsetting practices.

View Full Project Description
Faculty Supervisor:

Nicholas Mandrak;Nathan Lovejoy

Student:

Alexander Van Nynatten

Partner:

Nuclear Innovation Institute

Discipline:

Biology

Sector:

Energy

University:

Program:

Liquid accelerated cold spray for copper deposition

The liquid accelerated cold spray (LACS) technology is an innovative process that uses a high-pressure liquid flow to accelerate metal and composite powders to very high velocities (above 500 m/s) so that, upon the impact on the substrate, they form a coating. Using a liquid instead of a gas as used in a traditional cold spray, makes it possible to spray particles with a larger size distribution owing to the high density of the liquid. The technology has the potential to reduce considerably the spraying costs (as compared to the current gas accelerated cold spray processes) and to deposit coatings on internal surfaces or surfaces difficult to access.

View Full Project Description
Faculty Supervisor:

Ali Dolatabadi;Christian Moreau

Student:

Ali Akbarnozari

Partner:

Polycontrols

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

Concordia University

Program:

Accelerate

Expanding chemical oxygen demand (COD) profiles to validate contaminant specific degradation in freshwater environments and indicators of ecosystem function

Environmental scientists examining large-scale ecosystem processes (e.g., climate change, contaminant effects) are increasingly charged with collecting high-quality data on a more rapid timeline and extending the application of that data spatially and temporally. IISD Experimental Lakes Area (IISD-ELA) is a field research station comprised of 58 pristine lakes and their watersheds. This area has been set aside exclusively for research to influence environmental policy and regulations in favour of protecting Canada’s freshwater resources. Current IISD-ELA projects include developing minimally invasive methods for oil spill cleanup, assessing the effects of pharmaceuticals, and determining the impacts of climate change on aquatic productivity. Each of these projects includes measurements that help us understand changes related to the stressor of interest, with some common measurements relevant to all stressors. Oxygen demand, related to the degradation of organic and inorganic constituents by aerobic respirators (biological oxygen demand – BOD) and chemical reactions (chemical oxygen demand – COD), is considered a fundamental measure of water quality. Mantech Inc. has developed a new robust and field ready instrument (the PeCOD) to allow rapid determinations of COD that can be used to inform IISD-ELA projects.

View Full Project Description
Faculty Supervisor:

Vince Palace;Mark Hanson

Student:

Blake Cooney

Partner:

Mantech Inc.

Discipline:

Environmental sciences

Sector:

Manufacturing

University:

University of Manitoba

Program:

Accelerate

An Environmental Management System for the Town of Georgina’s Wastewater Collection System

This study will identify a practical approach to bring a standard mid-size municipality into adherence with the ISO 14001, Environmental Management System standard, for its municipal wastewater system. This will increase the levels of government regulatory compliance, resilience on municipal infrastructure and reduction of risks for basement flooding, spills and overflows of raw sewage to the environment.

View Full Project Description
Faculty Supervisor:

Carolyn Johns

Student:

Andre Setoodeh

Partner:

Town of Georgina

Discipline:

Other

Sector:

Other

University:

Ryerson University

Program:

Accelerate

Reactive extrusion process development for silane modified EPDM

Most rubber products require curing that involves either sulfur or peroxide curing and other ingredients such as accelerators, antioxidants, antiozonants, and heavy metal oxides. Some of these ingredients, either individually or in combination, generate environmental pollutant and hazardous gases and fumes during rubber processing or storage. Thus, there is a continuous need by the rubber industry to develop benign curing processes involving environmental-friendly process and less hazardous ingredients. In this project, we aim to develop a scalable, robust, and waste-free process for the production of silane-modified EPDM elastomer with adaptable curing behavior. The modification process involve the chemical grafting of silanes onto elastomers in the presence of reaction initiators in a solvent-free melt process using an internal mixer and extruder.

View Full Project Description
Faculty Supervisor:

Tiz Mekonnen

Student:

Boon Peng Chang

Partner:

AirBoss of America

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of Waterloo

Program:

Accelerate

Low Latency Myoelectric Controlled Interface for Finger Click Detection

Myoelectric controlled interface (MCI) has been extensively investigated as an effective tool for the control of advanced prosthetics, exoskeleton, entertainment gadgets, etc. In these human-in-the-loop applications, the time delay through the loop: from the generation of human intentions, to action of the machines in response to human intention, to the feedback the machines provide to the human operator, is important and some times critical for a successful human-machine interaction. However, in most current MCI studies, typically hundreds of milliseconds data were required for making a prediction, introducing a significant long delay in the control process, and limiting the application of MCI in those time sensitive scenarios. This project investigated a low latency MCI for predicting the movement of finger click by employing only several milliseconds data. We propose to exploit spatial information, including increasing the number of electrodes, optimize the location of electrodes, and extracting spatial features, to compensate for the information reduction in time dimension. The investigation of low latency MCI would improve the efficiency of the human-machine interaction and expand the application of MCI in the real world.

View Full Project Description
Faculty Supervisor:

Ning Jiang;John Tze Wei Yeow

Student:

Jiayuan He

Partner:

Brink Bionics Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Waterloo

Program:

Effects of human and natural habitat factors on wolverine density and connectivity

In southern Canada, wolverines share their natural habitat with humans. Forestry, for example, alters local ecosystems and leaves behind road networks that give access to people, also including recreationalists. Finally, many valley bottoms contain human infrastructure. This research project examines if wolverine numbers are impacted more by human or natural factors, determines if population connectivity is interrupted by human infrastructure and asks if those patterns are different for reproductive females. Understanding the relationship between wolverines and human land uses will help wildlife managers and stakeholders make informed decisions to maintain sustainable populations of this species at risk, as well as other sensitive species with similar needs. The project partner, Yellowstone to Yukon Conservation Initiative (Y2Y), is dedicated to balancing the needs of people and wildlife. Y2Y often works with universities to provide science-based conservation recommendations, for example the manageable factors impacting wolverines that this project will determine.

View Full Project Description
Faculty Supervisor:

Marco Musiani

Student:

Mirjam Barrueto

Partner:

Yellowstone to Yukon Conservation Initiative

Discipline:

Biology

Sector:

Other services (except public administration)

University:

University of Calgary

Program:

Accelerate

Speeding up Federated Learning Convergence using Transfer Learning

The recent advances in machine learning based on deep neural networks, coupled with the availability of phenomenal storage capacity, are transforming the industrial landscape. However, these novel machine learning approaches are known to be data hungry, as they need to tune a huge number of parameters in order to perform well. As more and more AI based applications are being deployed to learn from personal data, privacy concerns are rising, and more specifically on sensible domains like medicine, finance or mobile related data. With the ubiquitous availability of cloud-based solutions at a very low price, privacy has now become even more sensitive.
To overcome these issues, collaborative frameworks such as Federated Learning (FL) recently emerged and are accepted as realistic and adoptable solutions by healthcare practitioners. In a FL setup, actors locally learn a model on their private data and share the model only to a server in charge of aggregating the extracted knowledge.
If the first proofs of concept show very promising results, some challenges still remain in the medical domain where population drift from one hospital to the other is an identified phenomenon, and where the data dimensionality makes local knowledge extraction difficult.

View Full Project Description
Faculty Supervisor:

Stan Matwin

Student:

Farshid Hajhashemi Varnosfaderani

Partner:

Imagia Cybernetics Inc

Discipline:

Computer science

Sector:

University:

Dalhousie University

Program:

Accelerate

Modelling the Non-Condensable Gas (NCG) in SAGD infill wells– Part 1

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.

View Full Project Description
Faculty Supervisor:

Hassan Hassanzadeh

Student:

Nasser Sabet

Partner:

Ashaw Energy

Discipline:

Engineering - chemical / biological

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

High-throughput linguistic content comparison and sentiment analysis

Scrawlr is a platform for unconstrained, global interaction with all internet content and users. Scrawlr allows for user evaluation and unconstrained classification of any Scrawlr-hosted or non-Scrawlr content. For non-Scrawlr content, this evaluation and classification allowance will be first at the URL level but will subsequently be provided at the individual content component level. Scrawlr will require the capacity to, in multiple languages, identify equivalent and similar content. This will enable a number of key internal functions, including rapid detection of spam, identification of trending topics in multiple languages, and the automatic identification of plagiarism in multiple languages. Scrawlr also intends to provide automated sentiment analysis of the contents. This requires expansion in capacity related to high-throughput multi-language sentiment analysis and classification. This will enable several key internal functions including determination of sentiment in multiple languages and comparison of this sentiment in relation to evaluation and classification metrics. This research project is a critical aspect for the company to ensure automated protection of unique content on its platform, and in particular content that is protected content, from duplication and reproduction.

View Full Project Description
Faculty Supervisor:

Fatemeh Hendijani Fard

Student:

Ramin Shahbazi

Partner:

Scrawlr Development Inc

Discipline:

Computer science

Sector:

University:

University of British Columbia Okanagan

Program:

Accelerate

Previous
1…349350351352353354355…1,106
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe