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

Optimization and Development of Bombardier Data Based Engineering Design Tools

The proposed research will involve optimizing and improving engineering operations within Bombardier based on data collected from flight recorders and aircraft operators. This will involve developing new processes in maintenance tracking (i.e. tracking aftermarket spares sales, scheduled maintenance, accessing direct maintenance costs per component, etc.), and implementation of a stress tools suite for in-service structures evaluations. Currently, many internal processes within Bombardier are based on nonstandardized reporting and data collection methods. With the increasing influence of using data management and analytics in engineering, the challenge of the proposed research is incorporating these fields into the existing engineering simulation and design systems at Bombardier. To solve this issue, design platforms, linking to internal Bombardier databases, will be developed using tools such as MicroStrategy and Visual Basic to guide engineering decisions with respect to maintenance scheduling, structures evaluation, and aircraft efficiency.

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Faculty Supervisor:

Kamran Behdinan

Student:

John Paul Piazza;Daniel McCammon

Partner:

Bombardier Aerospace

Discipline:

Aerospace studies

Sector:

Manufacturing

University:

Program:

Accelerate

Dynamic Pricing for Optimizing Demand and Profitability

In this research project, a surcharge optimization algorithm will be developed to help the partner company to dynamically determine the premium charged for order pickup. The objective of the project is to smooth the demand curve for the order pickup timeslots: popular timeslots are congested, making it harder to deliver a positive experience, and other windows are idle, and overstaffed. In the project, large volumes of purchase history data including pickup and delivery “hot-spots”, historical pricing information, historical inventory, and shorts on pickup and delivery orders are to be utilized to determine the premium to be charged to improve both overall labor planning efficiency and customer experience.

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Faculty Supervisor:

Roger Grosse

Student:

Jing Li

Partner:

Loblaw Digital

Discipline:

Computer science

Sector:

Service industry

University:

Program:

Accelerate

Adaptive Artificial Agent for Smart Home Thermostat

How can we make the connected home smarter and more energy efficient? Ecobee’s research aims to address this question by making cutting-edge improvements to its smart home thermostat. There is huge potential to save energy in the residential heating and cooling space – homes with an ecobee smart thermostat can save up to 15% of their energy consumption. Ecobee’s aim is to make use of customer-volunteered usage data in the creation of an adaptive agent which can control the comfort level in the home autonomously. This agent will eliminate the need for close monitoring and adjusting of the thermostat by the user and use less energy than a house with a traditional thermostat, while still retaining maximal comfort for the residents. TO BE CONT’D

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Faculty Supervisor:

Maryam Mehri Dehnavi

Student:

Laura Walsh

Partner:

Ecobee Inc.

Discipline:

Computer science

Sector:

Manufacturing

University:

Program:

Accelerate

Evaluating the effectiveness of a multimodal intensive episodic treatment centre for youth Child Sexual Abuse (CSA) victims: The Be Brave Ranch

Child sexual abuse (CSA) is an all too prevalent form of childhood trauma worldwide. Nearly 1 in 5 women and 1 in 10 men experience some form of abuse in their childhood. CSA has been linked to numerous long-term effects: PTSD, depression, anxiety, substance abuse, eating disorders, sexual dysfunction, suicidal ideation, and cognitive impairment. Growing awareness of the problem has led more individuals to seek professional treatment. At present, there is no gold-standard for CSA treatment, particularly in youth. The Little Warriors Be Brave Ranch in Alberta, Canada is an innovative multimodal residential treatment program for children and adolescents with histories of CSA. We will gather mental health data from children and adolescents to measure symptom progression over time. We will also collect information from their caregivers, to gain better insight into the effects of treatment on them. Our goal is to develop a comprehensive framework for CSA treatment programs.

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Faculty Supervisor:

Peter Silverstone;Andrew Greenshaw

Student:

Matthew Reeson

Partner:

Little Warriors

Discipline:

Psychology

Sector:

Health care and social assistance

University:

Program:

Accelerate

Automated Retail Area Cluster Detection

The main objective of this project is to develop a retail cluster detection algorithm and improve the accuracy of the identification. The final deliverable will be an algorithm that runs through Google dataflow that will be able to ingest a month of users’ location breadcrumbs and output user-location clusters. The output of the algorithm will be a unique cluster identifier that will be used in the visit algorithm for visit identification. Besides latitude and longitude data, the project will have access to altitude information. This can be useful for determining clusters in multi-level locations (such as malls).This algorithm will help recognizing the customer visiting pattern observed based on user ID and allow accurate profiling for weather related content or advertisement targeting for enhanced user experience

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Faculty Supervisor:

Nick Koudas

Student:

Anxin Zhao

Partner:

Pelmorex Media Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Program:

Accelerate

Machine Learning Aided Detection of Brain Aneurysms

Intracranial aneurysms are relatively common, occurring in 2-5% of the general population. Rupture of the aneurysm can result in a stroke with a devastating 30-day mortality of 45%. Further, severe medical conditions are possible in which up to one third of patients may die before reaching the hospital and one third will become severely debilitated. Aneurysms are, however, difficult to find on magnetic resonance and computed tomography angiography scans (MRA and CTA scans) – especially when small or located close to the bone. Through the use of the existing knowledge and expertise of the neurovascular team at Toronto Western Hospital, as well as their database of CTA and MRA scans, the aim of this project is to improve on efforts in this field through the development of an artificial intelligence and machine learning method for the detection of intracranial aneurysms with a diagnostic accuracy approaching that of trained neuroradiologists. As unspecialized general radiologists read most neuroimaging exams due to a lack of specialized physicians in remote and rural areas, a long-term goal is to use results from this work to build a tool for the support of imaging review by non-specialists in emergency situations.

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Faculty Supervisor:

Marzyeh Ghassemi

Student:

Daniel Dastoor

Partner:

Education and Scientific Services of Toronto Neuroradiology

Discipline:

Computer science

Sector:

Health care and social assistance

University:

Program:

Accelerate

SSL Offloading Prototype

SOTI MoblControl is an enterprise mobllity management solution that secures and manages, mobile devices and the mobile data across all endpomts. To ensure end-to-end security, MobiControl encrypts all
communication between the MobiControl Manager and the Deployment Server uslng Secure Socket layer (SSL). The SSL Is a cryptographic protocol that is use widely for secure communication. The process of the encryption and the decryption In the SSL require considerable computation power. Specially in a situation of handling a large number of devices. This can put a significant stain on CPU resources and effect the performance of the system. By isolating SSL computation into a separate process and offloading process to specific hardware, and network components that are optimized specifically for this task, organizations gain grealtar control and ability to optimize the throughput of their system. The research will focus on creating a proof of concept that will potentially support SOTI’s customers in infrastructure saving.

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Faculty Supervisor:

David Lie

Student:

Or Aharoni

Partner:

SOTI Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and cultural industries

University:

Program:

Accelerate

Fast Implementation of Machine Learning Algorithms for Event Sequence Data in order to improve Customer Experience

Every day millions of customers move through the sales cycles of companies, this generates large sources of event data. This project aims to discover, understand and predict the journeys of their customers. On one hand, the project is interested in describing the data at a higher level. This means to apply machine learning techniques, namely clustering, and sequence embedding, in order to group similar behaviors together and allow the user to focus analysis on different aspects of the data, such as users of a specific age. On the other hand, this project focuses on dealing with real-time data, i.e. data that is coming into the system continuously. This platform could be applied to sales optimization, business process mining, churn analysis and so on.

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Faculty Supervisor:

Nathan Taback

Student:

Zhou Fang

Partner:

ODAIA Intelligence Inc.

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

Application of Real-time Axis-based SLAM in Geotechnical Engineering

Mining operations evaluate tunnel stability by looking at orientations of exposed rock faces and extrapolating the underlying rock formation. The most widespread and traditional method for determining these characteristics involve hand measurements with static tools. This process is both time intensive and prone to error. Additionally, it may be dangerous to measure rock faces that are hard to reach. The goal of this project is to implement a novel algorithm that can quickly and automatically determine sets of parallel rock faces and their orientations. This research will help successfully develop the RockMass Mapper which will be the company’s flagship product and is scheduled to launch in early 2020. The mining economy contributes to nearly 20% of Canada’s GDP and RockMass’s solution will improve the overall impact the mining industry will have on Canada’s economy while also improving the working conditions of those involved.

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Faculty Supervisor:

Alec Jacobson

Student:

John Xu

Partner:

RockMass Technologies Inc.

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

Investigation of Bicycle Traffic Flow Parameters

Bicycle and pedestrian counts are important data for the planning and design of safe roads. However, installing pedestrian and bicycle counters across an entire city road network is not financially viable. Therefore, a good option is to estimate counts at the network scale, using knowledge from a handful of pedestrian and bicycle counters (strategically placed) and trip data from users who willingly share their position from their smartphones.
Eco-Counter, the partner organization, is a world leader is the development of automated pedestrian and cyclist counting systems. The company is expanding into data services and requires additional tools and methods to help their clients (transportation agencies) manage and visualize their data. This project will help Eco-Counter achieve this objective.

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Faculty Supervisor:

Luis F. Miranda-Moreno;Kevin Manaugh

Student:

David Beitel;Lulu Tan

Partner:

Eco-Compteur

Discipline:

Engineering - civil

Sector:

Manufacturing

University:

Program:

Accelerate

Examining the barriers and facilitators to trauma registry sustainability in the Global South

Injury is a leading cause of death and disability world-wide, however rates are especially high for low- and middle-income countries (LMICs). Trauma registries— databases that document information on the injured patient related to the injury event, demographics, process of care, and outcome— are commonly used in high-income countries and have proven extremely effective in reducing rates of death and disability through informing injury prevention and quality improvement programs. Their use in LMICs is less common due to the financial and human resource constraints of hospitals in many of these settings. In recent years, innovative strategies have been used to overcome some of these constraints. The purpose of this project is to examine both the barriers and strategies that facilitate trauma registry sustainability—with a specific focus on the use of m-health technologies—to create a resource toolkit that can be used to improve how trauma registries are implemented and operated in the global south.

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Faculty Supervisor:

Nadine Schuurman

Student:

Leah Rosenkrantz

Partner:

T6 Health Systems

Discipline:

Geography / Geology / Earth science

Sector:

Information and cultural industries

University:

Program:

Accelerate

Hydraulic Vortex Optimization of a Recessed Impeller Pump

Toyo Pumps is performing research to upgrade their current line of recessed impeller or vortex pumps. Currently, these pumps can only operate in very limited and specific conditions. The goal is to redesign these pumps to allow them to operate in a wider variety of conditions and improve the efficiency, producing more work at a lower power cost. New designs will be made using advanced technology that makes it possible to virtually investigate hydraulic designs using software that simulates the flow through a pump. This allows for designs to be completed before ever constructing an actual pump. These advanced methods also make it possible to find and investigate designs that may be non-obvious and more complicated than if designed using traditional theoretical methods. These new and improved designs will give greater flexibility of use to the end user and save in power costs, reducing their footprint.

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Faculty Supervisor:

Siamak Arzanpour

Student:

Shahab Azimi

Partner:

Toyo Pumps

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

Program:

Accelerate

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