Innovative Projects Realized

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

30156 Completed Projects

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812
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673
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842
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8957
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9368
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96
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1120
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Projects by Category

Aerobic Granulation for the Treatment of Domestic Wastewater

Increasing pressure on India’s limited water resources due to population growth demands innovative and cost-effective methods of water management. One avenue of significant research is the treatment and recycling of municipal wastewater, where only about 31% of the domestic wastewater generated is treated using conventional methods. Aerobic granulation (AG) is a novel biotechnological wastewater treatment process that is increasingly drawing the interest of researchers worldwide. Aerobic granules are aggregates of microorganisms that form through microbe-to-microbe self-immobilization without reliance on biocarriers. The granules are packed with different microbial species and typically contain millions of organisms per gram of biomass. These microbes have the necessary physiological capabilities to degrade the pollutants in municipal and industrial wastewaters. The advantages of AG are its small space requirements, higher tolerance of toxicity and shock loads, and improvement in settling properties of biomass. The proposed project aims to develop and culture aerobic granules for the effective treatment of synthetic domestic wastewater in batch and continuous processes.

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Faculty Supervisor:

Andrew Tay

Student:

Partner:

Indian Institute of Technology Bombay

Discipline:

Engineering

Sector:

Education

University:

University of Calgary

Program:

Globalink Research Award

Temperature effects on geomaterials performance

The effects of temperature on the mechanical properties of geomaterials (e.g. soils, rocks) are important for the safety and life cycle of any infrastructures. The research activities in the field suggest that there is a lack of understanding due to limited experimental data. The seasonal climate change causes the variations in temperatures which may pose construction challenges. Extensive and systematic experimental studies will be conducted by the intern to address the stated temperature related problems. In this research, local geomaterials will be collected from various construction sites of Mumbai City. Thermal conductivity and strength properties of the materials will be determined under a range of temperatures. This data will be used to develop a regression model in future collaborations between these two research groups.

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Faculty Supervisor:

Sumi Siddiqua

Student:

Partner:

Indian Institute of Technology Bombay

Discipline:

Engineering

Sector:

Education

University:

University of British Columbia - Okanagan

Program:

Globalink Research Award

Controller Development and Validation for Extreme Maneuvering of Agile Fixed-Wing UAVs

Historically, unmanned aerial vehicles (UAVs) – also referred to as remotely piloted aircraft or drones – have most commonly been associated with military applications. In recent years, however, there has been a shift in interest towards civilian applications and a corresponding increase in research and development in this area. UAVs typically fall into two categories: fixedwing and rotorcraft. Fixed-wing aircraft – such as airplanes – generate lift by moving forward and creating airflow over their wings. Rotorcraft – such as helicopters – achieve their lift from rotating blades. Rotorcraft are usually used for tasks requiring superior handling and agility, however, they lack the endurance of fixed-wing aircraft. The proposed research aims to help bridge the gap between these two categories of UAVs by increasing the agility of fixed-wing aircraft, and thus broadening their suitability for missions requiring endurance and maneuverability. This will be accomplished by designing and testing onboard computer systems to automate extreme maneuvers with fixed-wing UAVs.

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Faculty Supervisor:

Meyer Nahon

Student:

Partner:

Indian Institute of Technology Bombay

Discipline:

Engineering

Sector:

Education

University:

McGill University

Program:

Globalink Research Award

Investigations in real-time spinal magnetometry using magnetoencephalography (MEG) for therapeutic biofeedback

Oscillatory neuronal activity can be quantified to help diagnose states of health and disease in the brain. These activities change on a fast time scale of milliseconds, which can only be captured by direct measurement of the brain’s electromagnetic activity. This is accomplished utilizing MEG and EEG technology, which can measure non-invasively these fast changes on the scalp surface. Moreover, using MEG, these signals can be observed within the brain volume through a localization process. The transition of MEG/EEG as a predominantly research tool to a modality used in a clinical setting has not been fully realized. In order for MEG/EEG to transition commercially to larger scale production, it is necessary to expand its relevance in a clinical setting. The proposed research will enable advancement into the clinical setting on two fronts: through development of real-time capabilities and by extending applications to the spine from predominantly brain based applications.

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Faculty Supervisor:

Teresa Cheung

Student:

Partner:

CTF MEG International Services Limited Partnership

Discipline:

Engineering

Sector:

Manufacturing

University:

Simon Fraser University

Program:

Accelerate

Deep Learning Analysis for Missing Tooth Detection in Mining Monitoring Systems

This project is aimed at using machine learning algorithms and techniques to enhance the current state of the art of missing tooth detection in mining monitoring systems. Unlike heuristic approaches that follow strictly static program instructions, machine learning techniques operate by building a model from example inputs in order to make data-driven predictions or decisions. We use machine learning techniques to identify the bucket and its teeth within the video frames taken by a camera located on the mining device. We keep track of the detected objects within the images to monitor the status of the teeth over time and detect a potentially missing tooth. We train our object recognition model based on a comprehensive database of over 200 hours of video footage, and evaluate our algorithm in the end by means of image benchmarks including various teeth locations/ scales and various weather conditions.

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Faculty Supervisor:

Guy Dumont

Student:

Partner:

Motion Metrics

Discipline:

Engineering

Sector:

Mining; Technology; Advanced Manufacturing

University:

The University of British Columbia

Program:

Accelerate

Giving Voice to Aboriginal Families

Experiences in early childhood are fundamental determinants of lifelong well-being. In this project, we will give voice to Aboriginal families and caregivers on what they believe is important to the well being of their young children. A methodology adopted from social psychology, called ‘echo’ enables the values and beliefs of the population of interest to be articulated. The population of interest is individuals working with or raising young Aboriginal children (ages 0-6 years) in the Greater Victoria Capital Region. The outcome is a unique and important perspective to inform early childhood services and practice. The intern will be involved in all aspects of this community-based research project. This research supports and informs the programs and services for Aboriginal children and families provided by the partner organization.

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Faculty Supervisor:

Beverly Smith

Student:

Partner:

Hulitan Family & Community Services Society;Success By 6;University of Victoria

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

University of Victoria

Program:

Accelerate

Aurora Lighting

The proposed project contributes to the development of a product for use in public spaces to provide LED lighting which is made interactive through sound responsiveness. This sound responsiveness is made possible through the use of modern micro-computers which can be programmed to use sounds in the environment to create different lighting effects. Unfortunately, this is a difficult task if the environments
are noisy. It’s a lot like trying to have a conversation during a loud party; a lot of information gets lost. This project is motivated by the desire to make the sound responsiveness more effective in noisy environment through the use of automatic sound analysis techniques. There are many techniques which have been created to help account for noise but none have been used for this specific reason. These different techniques will be investigated to see which can help sound responsive lighting in a noisy space. The partner organization is relatively young and this product will be their first to market. Through the funds made available through MITACS the partner organization will have more resources to ensure the success of this product. Furthermore, the technologies developed with this research will be integrated in future products.

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Faculty Supervisor:

George Tzanetakis

Student:

Partner:

Limbic Media Corporation

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

An Advanced Machine Vision-Based System for the Recognition and Counting of Indian Coins

Counting coins, with speed and accuracy, has been a challenging issue for banks and stores. People used to count coins manually before the arrival of coin counting machines. The process of counting coins manually is a very time consuming and tedious job. Moreover, mistakes are
likely to occur due to various reasons such as fatigue, eye tiredness and too many coins of nearly same shape and size cause confusion in sorting and counting. Coin sorters are common in North America and can be found in most commercial banks and even some grocery stores.
By contrast, they are not available in India, where the number and similarity of the coins make for a very challenging problem. The objective of this project is to determine whether advanced machine vision techniques are able to sort coins from India with acceptable speed and accuracy.
If the answer is yes, then the outcome will be used to develop a machine that can recognize and count Indian coins, with Indian banks as the initial market.

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Faculty Supervisor:

Brian Surgenor

Student:

Partner:

9293507 Canada Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

Queen's University

Program:

Accelerate

Microbial genomics for de-risking offshore oil and gas exploration in Nova Scotia

The proposed project fits within a broad initiative in offshore oil and gas exploration geoscience mapping led by the Nova Scotia Department of Energy (NSDoE), the project’s End User. The province has partnered with Dr. Casey Hubert (University of Calgary) to develop, validate, and deploy three new genomics-based bioassay tools for offshore prospecting on the Scotian Slope. Genomics results will be integrated into mapping petroleum potential with the overall aim to attract and maintain large-scale investments by the O&G industry, in Nova Scotia. Results will be integrated with other geoscience data in a broader work program at NSDoE. Atlas maps resulting from this work will be shared with prospective bidders to promote offshore leases and attendant spending commitments in the Province. By integrating genomics with extensive geoscience mapping approaches (seismic data, geophysical methods, geochemical tools, satellite oil slick data, etc) the new bioassays will be validated within a comprehensive effort comprising the NSDoE’s petroleum source rock program. The intern will enhance the capability of the Offshore Energy Research Association (OERA) to provide project management and scientific consulting for the project.

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Faculty Supervisor:

Todd Ventura

Student:

Partner:

Offshore Energy Research Association of Nova Scotia

Discipline:

Earth science

Sector:

Mining; Professional, scientific and technical services

University:

Saint Mary's University

Program:

Accelerate

Optimizing Forest Resource Management and Small Scale Wood Manufacturing – A case study with Chief Isaac Inc. business arm of the Tr’ondëk Hwëch’in First Nations, Yukon Territory

Traditionally, the forest management practice in the Dawson City area (YT) has been clear-cut management, in which all trees of a given area are harvested. As the local First Nation (the Tr’ondëk Hwëch’in Nation) seek to become more involved in the management of the local resources, the opportunity has arisen to transition to an alternative approach known as continuous cover forestry. This system is more conducive to their non-economic values, including wildlife, biodiversity and overall sustainability. In order for a successful transition to alternative approaches, an in-depth study of the forest attributes such as species composition and growth rate is required, in order to simulate potential management schemes. Additionally, in the absence of large influxes of timber from clear cutting, the existing mill in Dawson City is in need of optimization in order to continue operating. With an alternative approach to the current system, coupled with an optimized sawmill, this project will involve the community members on many levels, including employment opportunities, and the fulfillment of cultural needs.

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Faculty Supervisor:

Julie Cool;Verena Griess

Student:

Partner:

Chief Isaac Inc

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Embedding a Climate Change videogame in High Schools: Towards a Teacher’s Guide for Engaging Students with a Place-based Videogame – Future Delta 2.0

At the moment, BC has no comprehensive climate change curriculum in high schools, and educators lack coordinated materials to support its teaching. In an effort to narrow this gap, the Collaborative for Advanced Landscape Planning (CALP) at the Faculty of Forestry, UBC partnered with the Delta School District, to develop an educational and compelling videogame – Future Delta 2.0 (FD2), which brings together methods from commercial gaming a participatory research to address climate change science in an innovative place-based game environment. The game has been co-designed and evaluated with students & teachers from the Delta School District, as a proof-of-concept learning tool to explore how virtual future scenarios in the students’ own neighbourhoods may motivate interest, awareness, learning and in some cases behaviour change and civic engagement. CALP now proposes to turn the FD2 videogame, currently an experimental research product, into a comprehensive, stand-alone teaching and educational resource on climate change – Future Delta Teacher’s Guide. The Guide will provide a handbook on climate change education, for wider use in the Delta School District, using a community place-based videogame as an interdisciplinary resource to make climate change teaching/learning engaging and fun.

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Faculty Supervisor:

Stephen Sheppard

Student:

Partner:

TELUS (Vancouver, BC)

Discipline:

Sociology

Sector:

Information and cultural industries

University:

The University of British Columbia

Program:

Accelerate

Novel Approaches for Practical Machine Learning

Machine learning is a subfield of artificial intelligence that aims at producing computing models from observations (data), with no explicit coding made by humans. Recent advances have illustrated a strong potential of machine learning, with the potential of being a disruptive technology in many domains. For the current project, we are investigating techniques for making practical machine learning. Four main axes are considered: 1) to deal with big unstructured datasets, 2) to learn with a diverse set of representations of the data, 3) to learn from streams of data sensed or produced in real-time, and 4) to develop methods allowing fully automated machine learning with little or no insights from human experts. The internships will allow exploring key technologies that would support the development of applications such as smart cameras, wearable personal devices, and black-box machine learning software. It aims at exploring promising concepts with high commercialization potential.

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Faculty Supervisor:

Christian Gagné

Student:

Partner:

E Machine Learning Inc

Discipline:

Computer science

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

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