Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

30508 Completed Projects

2882
AB
5105
BC
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projects by Category

Autonomous Mobile Energy System Modeling and Optimization

The proposed research project is targeted to develop an accurate mathematical description for control and optimization of the Autonomous Mobile Energy system (AMES) and its integration with potential applications in mining, water desalination and other areas. The system incorporates solar thermal system thermal energy storage and an auxiliary energy source and will provide uninterrupted clean energy with no fuel supply or power grid connection required. Ascent Systems Technologies will benefit by being able to realize a full-scale functional prototype of the module. With the eventual commercialization of the product, Canada will benefit because this technology supports transition to a low-carbon economy

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Faculty Supervisor:

Ryozo Nagamune

Student:

Partner:

Ascent Systems Technologies

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Extracting and Matching Keypoints using Deep Learning to Estimate Salmon Biomass

In land-based aquaculture being able to estimate the mass of a fish is critically important in monitoring their health as they move through their lifecycle as well as knowing when to harvest. Current methods are invasive to the fish in its environment and result in mortality during sampling. We aim to use two cameras placed closely together underwater to take simultaneous pictures of fish and enable the estimation of their biomass. This is a complicated process involving the use of AI and ML to automate the identification of a fish in the cameras’ field of view and then make specific measurements of the fish to determine its biomass. Working with land-based fish farms we will collect data that can be validated and use these examples to train our models.

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Faculty Supervisor:

Michael Bauer

Student:

Partner:

ReelData Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

The University of Western Ontario

Program:

Elevate

Self-learning Microgrids for Decarbonization of Industrial Applications

Industrial applications are among the heaviest producers of greenhouse gas emissions (GHGs) and require a large amount of energy to operate. Industrial applications have now begun to invest in “microgrids”, which are small-scale power systems that utilize clean energy sources, such as solar, batteries, and electric vehicles, to satisfy energy demand. This project will develop an artificially intelligent, learning based method to learn the individual patterns of the clean energy sources, and schedule them in a way to maximize the reduction of GHGs and energy cost. In addition, a special feature of electric vehicles will be involved, named “vehicle to grid”, where energy from the vehicle battery can be fed back to the grid as a clean energy source. The project will be demonstrated at a real-world demonstration site, and track the number of GHGs reduced over a minimum of 6 months. The outputs of this project will be used to publish and showcase innovative methods to reduce the devastating impacts of climate change by intelligently leveraging clean energy sources to lower energy costs and reduce GHG emissions.

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Faculty Supervisor:

Hany Farag

Student:

Partner:

TROES

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

York University

Program:

Elevate

BodySense: Updating, disseminating, and evaluating an e-learning body image program for athletes

The present research will focus on re-developing and evaluating an inclusive, and accessible gender-neutral program entitled “BodySense”, in collaboration with the Canadian Centre for Ethics in Sport (CCES), aimed at increasing awareness of body image concerns in sport and aiding athletes and key influencers (i.e., parents, coaches, sport organizations) in cultivating a more inclusive, equitable and diverse sporting environment. This resource tool will disseminate information on the complex factors that influence athletes’ body image, and include interactive virtual learning modules (i.e., positive approach to food, safe sport, self-esteem, mental health, role modelling etc.). This partnership will result in the rigorous re-development, implementation, and evaluation of a current CCES resources (i.e., Body Sense) which will help strengthen their mission to protecting the integrity of sport and helping to ensure sport is equitable and inclusive for Canadians.

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Faculty Supervisor:

Eva Pila

Student:

Partner:

Canadian Centre for Ethics in Sport

Discipline:

Sociology

Sector:

Administrative and support, waste management and remediation services; Arts, entertainment and recreation

University:

The University of Western Ontario

Program:

Accelerate

Advanced method development to convert pulp and paper waste into renewable natural gas

The project involves the conversion of pulp and paper waste into renewable natural gas (RNG) using anaerobic digestion. It is the process in which microorganism converts the organics content into methane, hydrogen gas and carbon dioxide in the absence of oxygen. However, these microorganism are highly sensitive to change in pH, sulphates, organic load and temperature. Hence, the optimization of operating conditions are the crucial aspect of RNG production and treating pulp and paper sludge. The project will be undertaken in collaboration with Gazifère, Canada, which involves the development of model to increase the biogas yield and decrease the toxicity of pulp and paper sludge using anaerobic digestion. The project will provide the cost benefit analysis as well as environmental impact analysis of the production process will allow the partner organization to set-up the production scale at industrial level. The present work’s implementation will augment the multiple sectors including pulp and paper industries, RNG production, and domestic sector. In addition, the amount of sludge as well as toxicity will be reduced, hence decreasing the impact on the environment.

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Faculty Supervisor:

Satinder Brar

Student:

Partner:

Gazifère

Discipline:

Life Sciences

Sector:

Utilities

University:

York University

Program:

Elevate

Development of novel adsorbent from foam glass for nutrient recovery from industrial and municipal wastewater effluents: steps towards commercialization.

Future scarcity of phosphorus supply, increasing cost and issues of eutrophication are potential drivers promoting nutrient recovery from wastewaters. The proposed project aims to develop cheap and environmentally friendly technology for the recovery of phosphorus and nitrogen from municipal, agricultural, dairy, food processing, petrochemicals, and biomass processing industries wastewaters. Successful completion of the project will benefit the partner organization by helping them solve the technical challenges associated with their patent-pending adsorbent. Also, the project will foster the commercialization of the Npower adsorbent. The Canadian community will benefit from the successful project because the technology could help produce safe and environmentally friendly drinking water. In addition, the biofertilizers could boost agricultural activities and reduce the cost of farming.

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Faculty Supervisor:

Hossein Kazemian

Student:

Partner:

NPower Clean Tech Corporation

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Northern British Columbia

Program:

Elevate

Development and production of a plant-based foam packaging material for Seafood Industry

The British Columbia aquaculture industry sends 3-4,000,000 Expanded Polystyrene (EPS Styrofoam) fish boxes to market annually. Globally, wild and farmed combined, circulate tens of millions annually. Food industry including Sea-food packaging is one of the largest producers of package waste in landfills, and this has driven the need for a recyclable/biodegradable packaging as a replacement for petrochemical-based polymers to reduce the damage to the environment.
As regulations banning single-use plastics and specifically EPS by counties, cities, states, provinces, and countries rise, the fresh fish industry will be left with no alternative option to transport the large quantities of the head of gutted fish (HOG). EPS is currently the only viable material packaging option to fulfill the needs of the entire fresh fish cold supply chain and finding a sustainable packaging solution is inevitable before the regulation is universal.
With a progressive incremental innovation plan, this project will introduce a new recyclable and biodegradable packaging substitute to replace EPS fish packaging. Environmental reciprocity and looming regulation will highlight the innovative opportunity to address this challenge that will persist beyond fresh fish packaging.

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Faculty Supervisor:

Hossein Kazemian

Student:

Partner:

Brown's Bay Packing Ltd.

Discipline:

Engineering

Sector:

Manufacturing; Wholesale trade

University:

University of Northern British Columbia

Program:

Elevate

Development of a pilot-scale system to demonstrate the feasibility of hydrogen production using a combined water electrolysis and wastewater treatment modular plant

This project aims to demonstrate the feasibility of a novel system for an efficient and environmentally friendly wastewater treatment plant to produce clean water and hydrogen production as a clean fuel. Hydrogen, as an important energy carrier, is a part of Canada’s energy transition towards net-zero emission and an important asset in Canada’s fight against climate change. In the framework of water-energy nexus, this project aims to produce clean water from wastewater where green hydrogen as a clean fuel is also produced within the process with low cost and low environmental impact, making it economically competitive with fossil fuel-based hydrogen production and accelerates carbon-free infrastructure development.

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Faculty Supervisor:

Hossein Kazemian

Student:

Partner:

Water Life Systems

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Northern British Columbia

Program:

Elevate

Real-time monitoring and leak detection in commercial refrigeration system

A refrigerant leak is one of the major contributors of commercial refrigeration unexpected breakdowns. Conventional methods of leak detection using physical sensors are expensive, have limited capability of square footage coverage, and incapable of detecting slow and progressive refrigerant leaks. Accordingly, the development of a smart leak detection system without the need to include additional physical sensors using AI models based on actual operating conditions could significantly reduce the overhead costs associated with system shutdowns and refrigerant fill-ups in grocery stores. The goal for this project is to analyze data collected from various systems, driving meaningful insights, and developing AI models for detecting refrigerant leaks in the form of anomalies. The outcome of achieving the project objectives would have a significant environmental impact, substantial cost-saving, and most importantly, reduce human efforts and erroneous leak maintenance and monitoring processes.

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Faculty Supervisor:

Ayan Sadhu

Student:

Partner:

Kalder at Neelands

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

The University of Western Ontario

Program:

Accelerate

A Feasibility Study on Appliance Load Monitoring Systems in Quebec Households

This project focuses on the development of a tool to monitor electricity use in Quebec households. This tool intends to assess in near real-time the energy use of each appliance (electric space heaters, electric water heaters, etc.) to identify and diagnose its energy usage for providing feedback to utility and customers. Accordingly, several developments and experimentations by using current technologies (smart appliances, edge devices, and AI-based algorithms) are carried out to design a prototype. The resulting system is beneficial to both Hydro-Québec and its customers. For Hydro-Québec, it will help to facilitate the implementation of demand-side management strategies in the residential sector. Besides, for customers, it brings about new opportunities that allow them to play a key role in power grid operation by optimizing their energy use. Although developing an efficient load monitoring system is a difficult task to perform in Quebec residences, its realization, aimed by this research work, can bring about many benefits to all power grid players.

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Faculty Supervisor:

Kodjo Agbossou

Student:

Partner:

Hydro-Quebec

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

Université du Québec à Trois-Rivières

Program:

Elevate

MEMA_CB_CHEM : Metabolic Engineering of MicroAlgae for CannaBinoids – Chemistry PDF

The Canadian company Algae-C is developing innovative platforms for the growth of different kinds of phototrophic algae around the world. The algal biomass from its modular units is used for the aquaculture, biofuel, nutraceutical, chemical, and personal care markets. Algae-C wants to expand the use of their technology in more areas such as the pharmaceutical field. In order to achieve their goal, the company wants to optimize its own microalgae strains. With this project, Algae-C wishes to optimize genetically engineered microalgae for the production of plant-based metabolites. In a previous project with our research team was able to have the complete metabolic pathway for the production of compounds belonging to the cannabinoid family. The promising results prompted the company to continue with the current challenge to improve (increase and optimize) the production of ?9-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA) from engineered microalgae.

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Faculty Supervisor:

Isabel Desgagné-Penix

Student:

Partner:

Algae-C

Discipline:

Life Sciences

Sector:

Manufacturing; Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Elevate

Identifying neural dynamics using fluid dynamics methods

Brain activity can be recorded by an electroencephalogram (EEG). When investigating the data, it is notoriously difficult to extract neural dynamics related directly to e.g., a visual stimulus in an experiment, from the ‘background’ brain activity. A similar problem arises in fluid dynamics, when ordered dynamics, so-called coherent structures, are extracted from measurement data. There, multiple coexisting dynamics which are superimposed in the data need to be separated for further analysis. In recent years a technique called ‘Spectral Proper Orthogonal Decomposition’ (SPOD) was developed at TU Berlin and proved very helpful in identifying and separating dynamic structures in flows. This method is now applied to EEG data that will be recorded during an experiment in which subjects must perform cognitively demanding tasks. The specific patterns in brain activity correlating to the subject’s performance are identified. To predict when an individual’s ability to reliably solve those tasks decreases, a method of monitoring the identified patterns in close to real-time needs to be developed.

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Faculty Supervisor:

Robert Martinuzzi

Student:

Partner:

Technische Universität Berlin

Discipline:

Engineering

Sector:

Technology; Information and Communications Technology; Health and Related Sciences & Technology

University:

University of Calgary

Program:

Globalink Research Award

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