Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

Predicting population level effects of microplastics ingestion on the behaviour of fishes

High numbers of microplastics are currently present in freshwater lakes, rivers and ponds. Fish are known to mistake microplastic particles for food, then behave differently after eating them. As changes in behaviour are often the first line of defense against human-induced rapid environmental changes, monitoring these behavioural changes can tell us how pollutants, like microplastics, are likely to affect populations. This research will model stream-dwelling salmonids consuming microplastic particles using agent-based models, to explore how microplastic ingestion will scale up to affect populations, and to identify the characteristics that will make a salmonid population the most and least resistant to the effects of microplastic pollution. This study will help inform effective conservation targets, to help mitigate harm caused by microplastics, and to reduce ecosystem-level effects caused by declines in salmonid populations. Educational materials targeting all ages will also inform the public on microplastics impacts in freshwater ecosystems.

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Faculty Supervisor:

Christina Semeniuk

Student:

Partner:

rare Charitable Research Reserve

Discipline:

Life Sciences

Sector:

Arts, entertainment and recreation; Other services (except public administration)

University:

University of Windsor

Program:

Accelerate

Assessment of neuromuscular, cardiorespiratory, and cognitive performance in running and hopping tasks using wearable sensors

The objectives of this research project are (a) to record neuromuscular, cardiorespiratory, and cognitive related data using wearable sensors during running and hopping as two basic activities of many sports; and (b) convert the data to medically meaningful indicators of athletic performance and risk of injury using signal processing and machine learning algorithms. The project outcomes will fuel iKinesia’s ongoing research to develop and enhance its solution for Canadian athletes and sports teams at both national level and private clubs. iKinesia’s solution will benefit athletes and coaches to improve and personalize assessment and training, augment game strategy, capture noteworthy players, reduce the risk of sports related injuries, and accurately determine the return to play time post injury.

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Faculty Supervisor:

David St-Onge;Rachid Aissaoui

Student:

Partner:

iKinesia Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

École de technologie supérieure

Program:

Accelerate

Cloud platform for machine learning

Surgical Safety Technologies aims to provide healthcare professionals with the opportunity to perform research in areas of surgical performance and education and implement evidence-based solutions to improve patient safety. Search on video content would an ideal functionality to assist with healthcare professionals’ research. This project uses computer vision model to rank the relevance of the surgical video. In addition, this project aims to improve the user experience of the product by analyzing the metadata generated by the cloud platform and developing an efficient data visualization technique.

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Faculty Supervisor:

Maryam Mehri Dehnavi

Student:

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Multi-Object Tracking in Production Environments

Multi-object tracking has many uses cases in autonomous driving, robotics and security. Tracking is important as it allows us reason about the dynamic world and make actionable decisions based-off predicted object trajectories. As an example, in autonomous driving, not only the location of objects is important but also their predicted future trajectories are needed in order to make informed decisions. It is important to understand the hardware constraints in order to develop trackers that work in real-time. Understanding the necessary camera frame rate needed to perform actionable real-time tracking is an example of such hardware constraint. For robotics, developing adequate tracking solutions that satisfy hardware constraint will allow the verification that objects are moving as they should.

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Faculty Supervisor:

Florian Shkurti

Student:

Partner:

Kindred AI

Discipline:

Computer science

Sector:

Artificial Intelligence

University:

University of Toronto

Program:

Accelerate

Numerical Assessment of Structural Behaviours of High-Performance Building Envelope Panels

The Nexii building system consists of a structural lightweight pre-cast sandwich panel system that attaches to an existing or new base building structure. In an effort to make the panels lighter and improve the building envelope performance, the new generation of Nexii panels use FRP instead of steel framing among several other modification to the panel assembly. This study aims at assessing structural performance of the panel under the gravity and wind loading through a comprehensive parametric study using numerical method and Finite Element (FE) simulations.

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Faculty Supervisor:

Min Sun

Student:

Partner:

Nexii Building Solutions

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Victoria

Program:

Accelerate

A Predictive Cluster-based Machine Learning Pricing Model

Dynamic pricing models create price by assessing total cost, demand, and timing to customize the price to the moment. The models enable both buyers and sellers to settle a price that is very custom to their specific needs. Bison Transport Inc. has a network model that monitors profit and a pricing engine that monitors margin. The network model needs to evolve in critical ways to facilitate dynamic pricing. The current model allows viewing of the network from a variety of vantage points- region, customer, driver, asset, service type and time (day of week, time of day, season of year). The pricing engine, however, is not flexible. The current direct programming-based solutions incorporated into the pricing engine for dynamic pricing cannot adapt to the changing and unpredictable market conditions. Deletion or addition of information are not possible unless the programming code is directly modified. This is tedious. The solution is, therefore, automating the software. We propose to use computer automating tools from machine learning, that will allow the computer to learn from the input data set and predict future prices without human intervention. These tools can perform real time data analysis and optimize prices to changing demand and market conditions.

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Faculty Supervisor:

Parimala Thulasiraman

Student:

Partner:

Bison Transport Inc

Discipline:

Computer science

Sector:

Transportation and warehousing

University:

University of Manitoba

Program:

Accelerate

Hypatia-Learn: State of the Art Mathematics Learning and Tutoring System

The project revolves around reading and understanding students solution to various mathematical problems. We wish to analyse the work done by students and the solution to these problems and provide math checking capabilities to various types of problems. Furthermore, this project looks to construct a virtual tutor that can analyse students work and provide feedback and hints to help the student arrive at the correct solution. We wish to achieve all of this while using a simple mathematical editor to allow students to type up mathematical solution cleanly and easily.

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Faculty Supervisor:

Fanny Chevalier

Student:

Partner:

Hypatia Systems Inc

Discipline:

Computer science

Sector:

Education

University:

University of Toronto

Program:

Accelerate

What athletic therapists need to know about pain and pain medication: an evidenced based approach

The Canadian Athletic Therapy association (CATA) is the governing board for athletic therapist, health care professionals who rehabilitate athletes who are injured or in pain. Over-the-counter and prescription medications are often used by athletes as a pain management strategy, although they can have negative impacts on their health if misused. Since Athletic therapists follow athletes on the field and in the clinic, they are likely their most available health care professional. They should therefore be able to accurately educate and answer questions regarding pain medication and management. The goal is to create a list of competencies regarding pain management and medication to be included in the curriculum of athletic therapy academic institutions, and a CEU course for those already certified. This will be derived through a focus group, a systematic review, a pain induction study, and a study applying psychological practice in addition to standard care in a clinical setting.

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Faculty Supervisor:

Geoffrey Dover

Student:

Partner:

Canadian Athletic Therapists Association

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

Concordia University

Program:

Accelerate

Stable Manipulation with Offline Model-based Reinforcement Learning

In this project, we would like to study the problem of object manipulation in a real-world scenario. We assume three major settings in the environment – the object is non-rigid, oniy offline dataset is available and the input is high-dimensional images which are hard to be handled by classical control models. Recent successes in deep learning and reinforcement learning have provided a promising approach to handle this problem. We would like to explore the possibility of using them to train an agent that can manipulate non-rigid objects stably under this scenario which is confronted by Kindred in day-to-day operations.

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Faculty Supervisor:

Animesh Garg

Student:

Partner:

Kindred AI

Discipline:

Computer science

Sector:

Other; Technology; Information and Communications Technology

University:

University of Toronto

Program:

Accelerate

Design and stress relaxation experimental characterization of thermal shims for space applications

MDA Montreal possesses a niche expertise on a wide variety of high-performance satellite telecommunication antennas. These antennas are exposed to extremely harsh environments. Some panels require a rigid mechanical assembly (i.e., nut and bolt fastening) but must preserve their thermal isolation for the proper operation of the antennas and to limit heat exchange towards the spacecraft. Relatively thick thermal shims or washers are currently inserted into these assemblies to almost completely block the heat flow between the two structures. The main problem is due to the viscoelastic behaviour of the current shim material used. Under a compressive initial load, the shims exhibit an important stress relaxation (i.e., softening of the material with respect to time) and the initial pre-load in the fastened assembly is significantly reduced over time.

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Faculty Supervisor:

Daniel Therriault

Student:

Partner:

MacDonald, Dettwiler, and Associates Ltd (Sainte-Anne-de-Bellevue, QC)

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

École Polytechnique de Montréal

Program:

Accelerate

Bone Quality and Nutrition Status of Elite Endurance Athletes

Relative Energy Deficiency in Sport (RED-S) is a devastating condition that affects an athlete’s short and long-term health and performance. The objective of this study is to investigate the relationships between bone density, microarchitecture, and strength with RED-S risk factors including inadequate nutrition, amenorrhea and stress fractures in elite endurance athletes. Athletes will be recruited from the Canadian Sport Institute Calgary from a variety of endurance sports, and their bone quality will be assessed at the Bone Imaging Laboratory, University of Calgary. The Canadian Sport Institute will benefit from participating in this research project as they will receive advanced skeletal imaging on their athletes. By combining detailed bone health assessments with nutrition, health and injury information, athlete integrated support teams may be better able to identify and monitor athletes at risk of RED-S.

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Faculty Supervisor:

Steven Boyd;Lauren Burt

Student:

Partner:

Canadian Sport Institute Alberta

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

University of Calgary

Program:

Accelerate

Twin-entry turbine modelling for high efficiency engines

A turbine is placed in an engine system to make use of energy contained in exhaust gases. It receives hot gases that are left over from the combustion process and converts them into useful shaft power that increases overall efficiency. The flow from each cylinder is highly dynamic since it is created by the exhaust valve opening and closing. An engine with more than four cylinders must separate the flows in order to prevent interaction that can lose some of the available energy. A twin-entry turbine is designed with two inlets and a divider to keep these flows separate until they reach the impeller. This research project will aim to simulate a twin-entry turbine by creating a new model that can predict its performance when exposed to realistic pulsating flow. This model needs to be fast-running in order to successfully integrate it into a larger engine system simulation.

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Faculty Supervisor:

Colin Copeland

Student:

Partner:

Cummins Canada

Discipline:

Engineering

Sector:

Manufacturing

University:

Simon Fraser University

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.