Innovative Projects Realized

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

29670 Completed Projects

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801
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663
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825
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8841
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9197
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95
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568
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1088
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Projects by Category

Predicting noise impact on fish communities in the western Canadian Arctic using Passive Acoustic Monitoring – Year two

Several fish species produce species-specific sounds that can be identified in the wild using Passive Acoustic Monitoring (PAM) (i.e. dataloggers configured with underwater microphones). Our project will use existing and new PAM recordings to monitor the distribution of several fish species in the western Canadian Arctic, with particular focus on a keystone Arctic species, the Arctic cod (Boreogadus saida). Acoustic signal detection techniques will be implemented to identify fish sounds from large acoustic datasets. Predictive modelling will be used to predict the potential impacts of vessel noise and environmental changes on fish distribution. Timing is critical as the Arctic is undergoing increasingly rapid changes. Our investigation will be the first to investigate the ecoacoustics of Canadian Arctic fish and the potential impacts of anthropogenic noise. The automated signal processing and modeling will accelerate acoustic analyse and therefore benefiting the partner organisation and regulatory bodies alike.

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Faculty Supervisor:

Francis Juanes

Student:

Partner:

JASCO Applied Sciences (Canada) Ltd (Victoria)

Discipline:

Life Sciences

Sector:

Environmental Science and Technology; Sustainability & the Environment; Life Sciences (not health)

University:

University of Victoria

Program:

Elevate

Predicting noise impact on fish communities in the western Canadian Arctic using Passive Acoustic Monitoring

Several fish species produce species-specific sounds that can be identified in the wild using Passive Acoustic Monitoring (PAM) (i.e. dataloggers configured with underwater microphones). Our project will use existing and new PAM recordings to monitor the distribution of several fish species in the western Canadian Arctic, with particular focus on a keystone Arctic species, the Arctic cod (Boreogadus saida). Acoustic signal detection techniques will be implemented to identify different fish species from large acoustic datasets. Statistical modelling will be used to predict the potential impacts of anthropogenic noise and environmental changes on fish distribution. Timing is critical as the Arctic is undergoing increasingly rapid changes. Our investigation will be the first to investigate the ecoacoustics of Canadian Arctic fish and the potential impacts of anthropogenic noise. It will provide direct and indirect data relevant to indigenous food security and will provide long-term data and predictions needed to inform effective management.

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Faculty Supervisor:

Francis Juanes

Student:

Partner:

JASCO Applied Sciences (Canada) Ltd (Victoria)

Discipline:

Life Sciences

Sector:

Environmental Science and Technology; Sustainability & the Environment; Life Sciences (not health)

University:

University of Victoria

Program:

Elevate

Development of in operando characterization methods for lithium ion battery materials – Year two

The successful commercialization of new cathode materials for lithium ion batteries requires an improved and detailed understanding of the correlations between their structure, properties, and performance. Such a correlation will provide a foundation for better understanding the degradation mechanisms and optimized operating conditions for these cathode materials; pairing new battery materials with ideal applications and standardizing the methods by which these materials are evaluated. Lithium incorporated in the matrix of transition metal oxides, such as Ni, Co and/or Mn oxides, are materials of interest for improving capacity and/or power generation of recyclable batteries with applications in energy storage. To meet the cost targets and performance metrics for commercializing new types of cathode materials, we must be able to better understand the fit between cathode materials and operating conditions required by end applications. The proposed research will characterize cathode materials for lithium ion batteries using a variety of spectroscopic analytical techniques in real time with battery cycling to develop a better understanding of how these characteristics influence battery performance under different operating conditions and over time. This will also improve our ability to design cathode materials that meet the cost, durability, and power targets demanded from next generation lithium ion batteries.

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Faculty Supervisor:

Byron D Gates

Student:

Partner:

Nano One Materials Corp

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Simon Fraser University

Program:

Elevate

Development of in operando characterization methods for lithium ion battery materials

The successful commercialization of new cathode materials for lithium ion batteries requires an improved and detailed understanding of the correlations between their structure, properties, and performance. Such a correlation will provide a foundation for better understanding the degradation mechanisms and optimized operating conditions for these cathode materials; pairing new battery materials with ideal applications and standardizing the methods by which these materials are evaluated. Lithium incorporated in the matrix of transition metal oxides, such as Ni, Co and/or Mn oxides, are materials of interest for improving capacity and/or power generation of recyclable batteries with applications in energy storage. To meet the cost targets and performance metrics for commercializing new types of cathode materials, we must be able to better understand the fit between cathode materials and operating conditions required by end applications. The proposed research will characterize cathode materials for lithium ion batteries using a variety of spectroscopic analytical techniques in real time with battery cycling to develop a better understanding of how these characteristics influence battery performance under different operating conditions and over time. This will also improve our ability to design cathode materials that meet the cost, durability, and power targets demanded from next generation lithium ion batteries.

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Faculty Supervisor:

Byron D Gates

Student:

Partner:

Nano One Materials Corp

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Simon Fraser University

Program:

Elevate

Developing Tools to Track Vocalizing Marine Mammals with Long Baseline Hydrophone Arrays – Year two

My project aims to understand cetacean habitat use in remote areas along Canada’s coast. Using acoustic data from an array of permanently recording hydrophones, I am developing software to automatically detect, classify, and localize different species of whales that use the area .
The acoustic network is located deep in the Great Bear Rainforest in northern British Columbia in thus in important habitat for Northern Resident Killer Whales, humpback whales, and fin whales. At the same time, existing shipping and proposed tanker routes posing a challenge to the marine ecosystem.
The software I am developing within the Mitcas ELEVATE fellowship will provide unprecedented information about activity and behaviour of whales, and possible effects of shipping on their habitat use.My industry partner — WWF-Canada, the Gitga’at First Nation, and the North Coast Cetacean Society — will thus obtain urgently needed data for marine management.

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Faculty Supervisor:

Aaron Gulliver

Student:

Partner:

World Wildlife Fund Canada (Toronto, ON)

Discipline:

Engineering

Sector:

Environmental Science and Technology; Ocean Tech; Sustainability & the Environment

University:

University of Victoria

Program:

Elevate

Developing Tools to Track Vocalizing Marine Mammals with Long Baseline Hydrophone Arrays

The scope of this project is to use acoustic data from long-baseline arrays of hydrophones to detect, locate, and track marine mammals based on their vocalization. Specifically, the project aims to assess methods and develop automated tracking algorithms that provide accurate results for individual signals, and a maximum of flexibility regarding the channel, array, and signal characteristics. In cooperation with our industry partners — WWF-Canada, the Gitga’at First Nation, and the North Coast Cetacean Society — we will use the results to analyze the detailed movement pattern for a broad range of vocalizing marine mammals and their interdependency with human activities, such as ship traffic. The work will be conducted for the culturally, ecologically, and economically important marine environment around Gil Island in northern British Columbia and will make use of the sophisticated hydrophone array installed in Squally Channel. At this point, efficient, widely applicable tools for automated transient signal tracking do not exist for civilian long baseline hydrophone arrays, despite the high demand from industry, research, and government. The applications for such tracking tools range from facilitating port security to studies of marine habitat usage, or tracking species at risk.

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Faculty Supervisor:

Aaron Gulliver

Student:

Partner:

World Wildlife Fund Canada (Toronto, ON)

Discipline:

Engineering

Sector:

Environmental Science and Technology; Ocean Tech; Sustainability & the Environment

University:

University of Victoria

Program:

Elevate

Machine Learning for Improved Automated Valuation Model

According to “Standard on Automated Valuation Models (AVMs)”, an automated valuation model (AVM) is a mathematically based computer software program that produces an estimate of market value based on market analysis of location, market conditions, and real estate characteristics from information that was previously and separately collected. The purpose of an AVM is to provide a credible, reliable, and cost-effective estimate of market value as of a given point in time. Residential real estate market is geographically diverse and constantly changing. Traditional regression models require a long time to build and are rarely updated to reflect changes in the dynamic environment. Data Nerds at Kelowna initiated an internship project with UBCO to apply machine learning techniques for a more accurate and reliable valuation model. The outcome of the project will be integrated into Data Nerds’ AVM application platform.

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Faculty Supervisor:

Zheng Liu;Eric Li

Student:

Partner:

Data Nerds

Discipline:

Engineering

Sector:

Information and cultural industries

University:

University of British Columbia - Okanagan

Program:

Accelerate

Laser-based Metrology for Quantitative Inspection of Water Pipe

The PipeDiver is a free-swimming platform developed by Pure Technologies, which can carry sensors and devices for non-destructive inspection of in-service water pipelines. CCTV (closed-circuit television) inspection is a well-adopted method, which employs a CCTV camera on the platform. General, the CCTV inspection can only provide qualitative results about pipe condition. To achieve quantitative inspection, such as the measurement of pipe joint gap, precise laser-based measurement is preferred. This research is to integrate laser sensor with digital camera on the PipeDiver platform to implement the gap measurement. The principle is to use camera to capture the laser profile projected onto the gap and use image processing to calculate the width from the laser profile. The automatic processing algorithm will be developed as a software prototype by the intern for Pure Technologies.

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Faculty Supervisor:

Zheng Liu

Student:

Partner:

Pure Technologies Ltd

Discipline:

Engineering

Sector:

Utilities

University:

University of British Columbia - Okanagan

Program:

Accelerate

Developing Integrated Smart Home Controllers with Energy-Efficient HVAC Operation

AYO Smart Home is an integrator of new technologies to provide affordable and energy-efficient housing for First Nations communities across Canada. AYO manages the technology and supply chain to deliver Net-Zero houses consisting of efficient building envelopes, heat recovery systems, energy-efficient HVAC, LED lighting, mold-resistant materials, and smart home controllers. After developing an energy-efficient HVAC system under a previous Mitacs project and successfully testing it in a pilot construction, AYO intends to move to the next level.It is proposed in this project to develop a smart home control system integrated as an inherent component of AYO houses. The smart home controller will provide high-technology access to the variety of the home systems including HVAC, lighting, sensor data, and solar generation. The most important component of the smart home controller is the the energy-efficient operation of HVAC.The post-doctoral fellow has 5 years of expertise developing energy-efficient HVAC systems under supervision of his academic supervisor in Simon Fraser University. AYO recognizes the potential in the academic team to develop the smart home control system. In continuation of the previous year-long collaboration, AYO and SFU will develop and bring the next generation of the product to the market.

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Faculty Supervisor:

Majid Bahrami

Student:

Partner:

AYO Smart Home Ltd

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Elevate

A Survey Design and Analysis On Building Information Modeling (BIM) Implementation in Alberta

Public and private owners and stakeholders view Building Information Modeling (BIM) as a technology to assist in project delivery and to support the use of information integration for project design, construction and facility management. Owners will demand the use of evidence-focused BIM technology to eliminate inefficiencies, misinterpretations and unjustified over-budget and over-time project delivery that are common within the Architecture, Engineering and Construction (AEC) industry.

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Faculty Supervisor:

Ahmed Bouferguene

Student:

Partner:

Discipline:

Sociology

Sector:

University:

University of Alberta

Program:

Accelerate

Precious metal mineralization at submarine volcanic centres: insight from the felsic centres of the Abitibi greenstone belt, Quebec, Canada

The proposed study will examine the volcanological, mineralogical and geochemical evolution of the felsic volcanic complex hosting Horne deposit in a comparative study with the surrounding felsic volcanic centres in the Rouyn-Noranda region of Quebec. Volcanic and intrusive facies, alteration phases and mineralization styles will be described for each centre. Mineralization will be further examined by analyzing trace element concentrations in sulfide and oxide phases to identify similarities and differences between all complexes. Through the course of determining these concentrations, a separation and identification of components from magmatic and hydrothermal contributions will be attempted. Field samples and drill core from the Krafla volcanic complex will be examined to compare trace element concentrations in sulfide and oxide phases in a modern hydrothermal system and an evaluation of fractures and pore spaces will be conducted to assess how these fluids flow through these spaces.

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Faculty Supervisor:

John Stix

Student:

Partner:

Falco Resources Ltd

Discipline:

Earth science

Sector:

Mining

University:

McGill University

Program:

Accelerate

Portable diagnostic device for outpatient BNP detection – Year two

Heart Failure (HF) occurs when the heart becomes damaged or weakened. HF is an epidemic, with approximately 1 million Canadians affected. BNP is an effective diagnostic and prognostic marker for HF. There is a direct correlation between elevated concentrations of BNP in the blood and the severity of HF symptoms. The need for point-of-care monitoring of BNP levels in the outpatient setting is imperative. The main objective is to develop a portable immunoassay-based electrochemical sensor for rapid detection and monitoring of BNP levels in outpatient’s blood, for early detection of HF. The partner organization will gain intellectual properties and the rights to commercialize a home-use monitoring system for accurate detection of BNP in a drop of blood.

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Faculty Supervisor:

Juewen Liu

Student:

Partner:

LeNano Diagnostics Inc;University of Waterloo

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Elevate

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