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

Effectiveness of vegetation and habitat characteristics as predictors of insect parasitoid populations – Year two

Climate change, land development, invasive species, and other disturbances can alter the composition, structure, and functions of native vegetation across landscapes. These disturbances also impact insect parasitoids, which are a key, and often overlooked, component of biodiversity. By their ability to control other insect populations, they are integral for fostering resilient and functional forests. Understanding and monitoring vegetation structure and composition and how it relates to parasitoid populations will help to quickly detect, measure, and forecast negative changes to forest ecosystems. This research will explore the link between plant and parasitoid populations across forests of different successional stages and disturbance regimes to provide (1) a strong basis on which to create and improve ecological restoration and rehabilitation programs and (2) data on the relationship between vegetation and parasitoids to identify and detect the effects of future disturbances and cascade effects on animal species as part of regular, long-term management of forests. This is especially relevant in Ontario as invasive species, such as the emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), continue to spread rapidly throughout the province having detrimental impacts on forests across the landscape.

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Faculty Supervisor:

Stephen Murphy

Student:

Justin Gaudon

Partner:

rare Charitable Research Reserve

Discipline:

Environmental sciences

Sector:

Fisheries and wildlife

University:

University of Waterloo

Program:

Elevate

Development of a novel IPM strategy for brown marmorated stink bugs (Halyomorpha halys) using RNA interference (RNAi) technology – Year two

Brown marmorated stink bug (BMSB) (Halyomorpha halys (Stål)) is an invasive pest with a large host range that includes many economically important fruits, vegetables, and row crops. Native to Asia, BMSB was first detected in North America in 1998 and since has become established in British Columbia, Quebec, and Ontario; and 44 American states. In order to develop efficient BMSB focused integrated pest management program (IPM), it is critical that novel alternative control tactics are investigated primarily because there are no effective insecticides available. RNA interference (RNAi) is a form of genetic control that has shown promise as a management tactic for BMSB. In this context, we aim to investigate RNAi for BMSB management. We will use genetic and proteomic tools to design new dsRNA (n = 10) in order to affect all BMSB life stages. We will test the effects of dsRNA, first independently then in multiple combinations, on BMSB populations raised in the laboratory. The most efficient combinations (n = 3) will finally be tested in the field to assess their efficiency under natural conditions. Our project will be the first step in the development and potential commercialization of a control of BMSB, efficient in the long term.

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Faculty Supervisor:

Cynthia Scott-Dupree

Student:

Alexandra SEBASTIEN

Partner:

Bayer CropScience Canada

Discipline:

Environmental sciences

Sector:

Life sciences

University:

University of Guelph

Program:

Elevate

Towards Clinical Use of Whole Genome Sequencing based Tests in a Clinical Setting – Year two

Using genomics in clinical care has the potential to treat patients more efficiently. There have been a number of recent discoveries of genomic assays that can guide treatment. However, most genomic data is generated in a research setting and useful health data only in a clinical setting. Translating potential genomic research into a clinical setting as well as bringing clinical data into a research setting faces significant challenges. One challenge is technical: genomic tests often take days to run and are thus not efficient enough for a clinical use. Another challenge is the public perception: because genomic data is very private, the patient’s privacy needs to be ensured and the public opinion about this has to be respected. A final challenge is logistic: how can genomic data be linked into clinical records when the data is generated at different sites and different organizations have to be involved.
We propose to address these challenges. We will gather best practices and key characteristics of already successfully established genomic projects that cooperate with clinical sites. We will identify one or two clinical sites within Ontario that are positioned to implement genomic tests and start to integrate them. TO BE CONT’D

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Faculty Supervisor:

Quaid Morris

Student:

Linda Sundermann

Partner:

Vector Institute

Discipline:

Biochemistry / Molecular biology

Sector:

Life sciences

University:

University of Toronto

Program:

Elevate

Designing Soft+Stiff Haptic Interactions with Opensource Authoring Toolkits – Year two

Our sense of touch is vital to most daily activities we engage in, but is underused by most existing computing devices. Though haptics is an active research field, the main outcomes of three decades of research are limited to cost-effective vibrotactile feedback (as in mobile phones) or expensive force-feedback devices (mainly for surgical operation simulation). Software frameworks for haptics offer comprehensive haptics and physics simulation capabilities, however require expert engineering and software development skills. Haply Robotics offers a cost-effective force-feedback hardware toolkit. The Haply development environment targets designers and students, however its expressivity in haptics and physics simulations is more limited. There is still a huge potential for haptic applications to unleash creativity and expressivity: improving communication (as in information visualization) and interpretation (as in digital musical instrument design). Recent advances in soft robotics offer opportunities to develop soft haptics applications with greater degrees of freedom.
We will create a second generation Haply toolkit for soft haptics building upon the recent advances in soft robotics. We will create an authoring tool that support novices and experts (in design, development and engineering) compatible with both toolkit generations. TO BE CONT’D

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Faculty Supervisor:

Marcelo Wanderley

Student:

Christian Frisson

Partner:

Haply

Discipline:

Music

Sector:

Information and communications technologies

University:

McGill University

Program:

Elevate

Development of climate sensitive growth functions for western North America’s boreal tree species – Year two

The Mixedwood Growth Model (MGM) is used by forest managers in estimating growth and yield outcomes for common boreal tree species in North America. MGM has been shown to effectively model both managed and unmanaged stands in Alberta and surrounding regions. Currently, climate effects are not accounted for in growth functions used in MGM. Recent work for black spruce has shown that there is need to understand and model the effect of climate for other boreal tree species including white spruce, aspen, balsam poplar, lodgepole pine and jack pine. This study is designed to examine the effect of climate, competition, site quality, and their interactions with climate on the growth of the aforementioned tree species. Long term measurement data with at least 11,673 Permanent Sample Plots (PSP) established and measured between 1931 and 2015 across western Canada and Alaska will be analysed for this project. This will include evaluating a wide variety of climate variables, competition indices and tree and site variables as potential predictors of growth . The addition of climate to growth functions in MGM would improve its ability to represent effects of climatic variation in the western boreal and support modeling of climate change impacts.

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Faculty Supervisor:

Phil Comeau

Student:

Felix Oboite

Partner:

Weyerhaeuser (Canada)

Discipline:

Resources and environmental management

Sector:

Forestry

University:

University of Alberta

Program:

Elevate

Developing measuring techniques for online monitoring of ex-vivo organ support system (EVOSS)

The ex-vivo organ support system (EVOSS) being developed by Tevosol, Inc.
Organ transplantation remains the standard therapy for treatment of end-stage heart and lung failure. Tevosol Inc., a Canadian organ transport device company in the market, is developing an ex-vivo organ support system (EVOSS). The EVOSS is a system that is used to preserve donor organs in a working state at body temperature during the time between donation and transplantation into a patient. The development, optimization and proving of this device is a collaboration between academics in Medicine and Engineering with the support of Tevosol company aimed at commercializing the device. This development includes sensor developments for measuring the flow rate in a pulsatile regime, and organs weigh and volume online measurement. All aspects of the sensor development including mechanical design, instrumentation, testing, validation, response, and feedback during online monitoring of system conditions will be investigated in this research project.

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Faculty Supervisor:

David Nobes;Reza Sabbagh

Student:

Bryce Palichuk;Jason Der

Partner:

Tevosol

Discipline:

Engineering - mechanical

Sector:

Life sciences

University:

University of Alberta

Program:

Accelerate

Analysis and Design of Fast Charging System with Flywheel Energy Storage Platform

This project is aiming at the design and analysis of high-performance fast charging system (FCS) to decrease charging time and reduce the high demand effect in the power grid. Besides, the target fast charging system will support transportation electrification infrastructures, maximize customer satisfaction, reduced operational costs and CO2 emissions. The analysis of the FCS system will provide resilient features to ensure minimum operation interruptions. Also, the system maximizes the charging time by protecting battery life. The design of the system can use energy storage system (battery-flywheel) to reduce the adverse effects of the high demand in the power grid. Also, the analysis includes the sizing of the system for different type of environment and weather conditions.The project will give an advance technology advantages to the partner organization members and will contribute to help grow the low-carbon and “smart” technology eco-system in the country, leading to job growth and economic development over the long-term.

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Faculty Supervisor:

Hossam Gaber

Student:

Onur Elma;Sherif Dabour

Partner:

Canadian Urban Transit Research and Innovation Consortium

Discipline:

Physics / Astronomy

Sector:

Automotive and transportation

University:

Ontario Tech University

Program:

Accelerate

Computational Chemistry And Structural Biology Approaches To Tackle Huntington’s Disease

Huntington’s Disease (HD) is a fatal hereditary neurodegenerative disease caused by expansion of the CAG repeat tract at the 5’ of the huntingtin (htt) gene resulting in polyglutamine expansion of the HTT protein (polyQ-HTT) of aberrant function. HD symptoms include loss of motor coordination, cognitive and speech impairment, and psychiatric disorders. HD affects approximately 1 in 7000 people in Canada, and there are no cures or disease-modifying therapies to date. This project aims to identify heterobifunctional small molecules (PROTACs) meant to revert or halt HD progression by binding E3 ubiquitin ligases and recruiting these to polyQ-HTT species, promoting their ubiquitin-mediated degradation. Atomic structures of polyQ-HTT-proximal E3 ligases will serve as a basis for computer-aided ligand design. Cocrystal structures of in vitro-positive hits, complexed with the E3 ligases, will guide ligand optimization. The project will broaden the applicant’s expertise in structural biology, computational chemistry, and will expand his knowledge in the fields of protein aggregation diseases and protein degradation as a therapeutic strategy; it will also expand SGC’s track record on E3 ligases and polyQ-HTT targeting. The chemical handles for E3 ligases generated will serve the global community working on PROTACs as a novel therapeutic modality.

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Faculty Supervisor:

Matthieu Schapira

Student:

Luca Signorile

Partner:

Structural Genomics Consortium

Discipline:

Pharmacy / Pharmacology

Sector:

Life sciences

University:

University of Toronto

Program:

Elevate

Smart Work Zone Management

Construction zones are one of the leading contributors to Toronto’s ever-growing congestion. The aim of this study is to develop an integrated construction zone traffic management framework to minimize disruption of the traffic and reduce the effect in terms of congestion. This study leverages historical and real data collected from on-board construction trucks provided by the partner organization to find an insight as to how far upstream and downstream of the work zone congestion propagates. Using such information, it is then possible to develop novel prediction models determining the impact zone for future construction zones and selecting optimal work zone size and staging of vehicles and equipment. In addition to the prediction model as part of this collaboration, an innovative anticipatory vehicle routing algorithm will be developed that not only help motorist to avoid construction zones but also guides them to their destination while minimizing travel time and utilizing road network more efficiently.

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Faculty Supervisor:

Bilal Farooq

Student:

Melvin Wong

Partner:

Lazaret Capital

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Ryerson University

Program:

Elevate

Simeio: Anomaly Detection for Building Automation System

Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis. Real-time monitoring and analysis of data can reveal insights about the performance of the building helping to reduce operating costs, lower utility bills, increase equipment life, improve tenant comfort, retention, and leasing rates; all while lowering carbon emissions. Simeio (A Cloud based software application developed by UCtriX team) is leveraging powerful artificial intelligence (AI) analytics to automatically detect anomalies and faults in the HVAC system and pinpoint any abnormalities or failures in a building. Simeio is a platform used by building owners, building managers, or higher authorities to ensure the sustainability and efficient operation of buildings.

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Faculty Supervisor:

Fariborz Haghighat

Student:

Milad Ashouri

Partner:

EnerZam

Discipline:

Engineering - civil

Sector:

Construction and infrastructure

University:

Concordia University

Program:

Elevate

Computer-vision Powered Smart Production Assistant

Over 70% of tasks in manufacturing are still manual; therefore, over 75% of variation in manufacturing comes from human beings. Human errors were the major driver behind $22.1 billion in vehicle recalls in 2016. Currently, when plant operators want to gain an understanding of their manual processes, they send out their highly-paid industrial engineers to run time studies. These studies produce highly biased and inaccurate data that provides minimal value to manufacturing teams. This project aims to create a smart production assistant that helps manufacturing plant operators gain unprecedented visibility into their manual production operations, allowing them to optimize their worker efficiency while maximizing productivity. This will be done by automated data generation using computer vision, conversion of raw data into useable information, visualization of information using common Business Intelligence methodologies and lastly, prediction of future plant performance based on historical information, as well as information about other market drivers.

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Faculty Supervisor:

Afshin Rahimi

Student:

Hamidreza Setare Kokab

Partner:

i-50

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Windsor

Program:

Accelerate

Wireless Network Testbed for Network Slicing and Data-driven System Parameter Optimization

The goal of this project is to design and develop a wireless network testbed at the University of British Columbia (UBC) for Rogers Communications Canada Inc. to support different use cases for the fifth generation (5G) wireless networks. We will study the concept of self-organizing network (SON) and design a deep learning-based algorithm for our testbed to determine the optimal network parameters based on network traffic data and key performance indicator (KPI) statistics. We will also design a network traffic forecasting algorithm by capturing the mobility patterns of users. We will employ the proposed forecasting method to equip our testbed with mobility management algorithms for frequent handover operations. We will leverage SDN and network functions virtualization (NFV) to enable our testbed to support network slicing. We will design algorithms for dynamic radio resource allocation within each slice to satisfy the service requirements in each use case.

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Faculty Supervisor:

Vincent Wong

Student:

Manyou Ma;Shahab Bahrami

Partner:

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of British Columbia

Program:

Accelerate

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