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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825
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8841
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Projects by Category

Data-Driven Control of an Ultracompact Industrial Robot

In recent years, automation has become more accessible to small- and medium-sized businesses, leading to an increase in popularity of ultra-compact and easy-to-integrate industrial robot arms like Mecademic’s Meca500. However, because of their size constraints, it is harder for these robots to accurately follow a programmed path. This research project aims to improve the path-tracking performance of Mecademic’s Meca500 robot by fusing state-of-the-art machine learning techniques with modern control design techniques. Improving the path-accuracy of the Meca500 will strengthen Mecademic’s competitive advantage in the fast-paced industrial automation market.

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Faculty Supervisor:

James Richard Forbes

Student:

Partner:

Mecademic

Discipline:

Engineering

Sector:

Manufacturing

University:

McGill University

Program:

Accelerate

Enhancing visualization of manufacturing complexity highlights on CAD file

Currently, the service provided by GRAD4 has an interface for visualization of CAD models. However, there is still room for improvement in speed and comprehensibility for the users: both manufacturers and buyers. The main challenge of implementing the improvements is in relatively high computational cost of such visualizations: while a regular PC handles such task efficiently, web-based tools tend to have difficulties when modelling 3D object with similar performance. Based on this, it is proposed 1) to investigate ways of improving geometric representations of CAD models on a web-page; 2) to retrieve and analyze user feedback on the viewer and take according actions; and 3) to identify future venues for viewer development.

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Faculty Supervisor:

Yaoyao Fiona Zhao

Student:

Partner:

GRAD4 Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Performance map of effect of composition and heat treatment on the work output from shape memory alloys.

Shape memory alloys are materials which, when cooled are easily stretched, but when heated, return to its previously “remembered” shape with a high force. This allows for a simple heat engine to be made, which can use hot and cold sources to create motion and do work. The amount of work that can be done by a shape memory alloy is dependant on its composition, geometry and how the material is processed prior to use. To properly a design a shape memory alloy device, it is important to determine how it will perform, taking those previously mentioned factors into account, but also heating and cooling rates. The objective of this proposal is to develop a testing facility tailored to shape memory alloys, accounting for the factors which affect performance in application. This apparatus is unique in that it allows for a complete characterization of the performance of the material in a single step.

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Faculty Supervisor:

Chan Y. Ching

Student:

Partner:

Smarter Alloys Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Comparison of electronic cognitive behavioural therapy to other treatment modalities at a specialized mental health hospital

There is a need for research on electronic CBT (eCBT) in real-world settings, particularly during the COVID-19 pandemic as access to face-to-face treatment is limited. Understanding the challenges in delivering eCBT will be crucial for improving access to care during the current pandemic, and in preparing a response to future pandemics. The intern will lead an evaluation and continuous improvement of the eCBT program at Ontario Shores Centre for Mental Health Sciences. This project will involve three phases: (1) A comparison of client characteristics and outcomes in different modalities of CBT (individual face-to-face, group, eCBT, and mixed); (2) an analysis of client adherence to treatment; and (3) an economic evaluation of eCBT compared face-to-face treatment.

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Faculty Supervisor:

David Rudoler

Student:

Partner:

Ontario Shores Centre for Mental Health Sciences

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

University of Ontario Institute of Technology

Program:

Accelerate

Photonic Cognitive Processor for Next Generation Artificial Intelligence Hardware

Artificial Intelligence (AI) is transforming our lives in the same way as the advent of the Internet and cellular phones has done. However, it takes thousands of CPUs and GPUs, and many weeks to train the neural networks in AI hardware. Traditional CPUs, GPUs, and brain-inspired electronics will not be powerful enough to train the neural networks of the near future. To radically impact the next generation of AI hardware, I propose to develop a fundamental technology: a photonic cognitive processor that uses light (instead of electrons). By employing photonic networks, I will test my processor with standard benchmark tasks on pattern recognition such as MNIST. I propose to use a special purpose GEMM compiler that will efficiently perform small matrix multiplications on enormous matrices. Results will be compared to electronic counterparts in terms of speed, precision, and energy efficiency.

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Faculty Supervisor:

Bhavin J. Shastri

Student:

Partner:

Huawei Technologies Canada Co Ltd (Markham, ON)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Queen's University

Program:

Accelerate

Creating a Map of Adipose Tissue Distribution and Automated Analysis for Plastic Surgery

The surgical practices involving fat are constantly evolving at the cutting edge of technology. Procedures involving fat manipulation, such as liposuction, contain a degree of subjectivity which is mainly guided by the surgeon’s visual or tactile perception of the underlying fat. This lack of subjectivity raises an important issue regarding the surgeon’s ability to replicate his work and predict the final results of the procedures. Moreover, there is currently no absolute method to measure the volume of the fat in real time effectively. Current works will demonstrate that the thickness of fat can be automatically and objectively measured in real time in the operating room using ultrasound technology and an in-house software. The benefit to the partner organisation is the development of an optimized ultrasound assessment tool using artificial intelligence to provide surgeons and patients with a repeatable, predictable service and, ultimately, greater confidence in the planning and execution of invasive surgical procedures in plastic surgery.

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Faculty Supervisor:

Thomas Hemmerling

Student:

Partner:

9216-3922 QC Inc.

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

Research Institute of the McGill University Health Centre

Program:

Accelerate

Human Pose Estimation and Activity Monitoring in Hospital with Self-calibrating Cameras

The interns will work on improvements to algorithms using geometry and deep learning for estimating human pose of individuals and the distance between them. This is a difficult task to do from videos as it involves 1) the detection and 2) 3D metric reconstruction of persons in all kinds of poses and apparel. The interns will obtain hands-on experience in algorithmic development, programming, and running validation studies at UBC and HPC’s facilities.
The expected benefit to the partner organization are far-reaching. This work is laying the groundwork for Providence to establish a computer-vision based smart hospital where non-contact based detection models can benefit patient care in areas including but not limited to infection control and patient monitoring.

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Faculty Supervisor:

Helge Rhodin

Student:

Partner:

Providence Health Care

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

MATCHING VIDEO CONTENT TO THE DEVELOPMENTAL NEEDS OF PRESCHOOL CHILDREN

The proposed research will include an analysis of video content to determine its implicit learning content based on the social and emotional domains. Once the videos are analyzed, a parent profile will be used to determine what videos are most applicable to each individual child, based on their developmental profile. Further activities will be recommended to parents in addition to the video content. This project will aid the organization in becoming more individualized in terms of content and domain development, according to what the profile indicates for the child. This specificity will allow the organization to market their product as developmentally appropriate, and it will also promote the capabilities to foster particular developmental skills.

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Faculty Supervisor:

Elizabeth Nowicki

Student:

Partner:

Kidobi

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

Western University

Program:

Accelerate

Monitoring, Analyzing, and Mitigating Electrical Vehicle (EV) Anomalies and Failures

This project is designed to build a system and software that will monitor and analyze the Electrical Vehicle (EV) bearing anomalies and failures. We will develop a framework that will address the EV bearing failure modes, its effect, and the key features of each failure mode. Later, we will collect the bearing data at “Solution Serafin”, and ingest it in an AI tool for the diagnosis and prognosis of the EV bearing failure. This tool will provide the EV driver and our partner the remaining useful bearing life, and consequently an enhanced maintenance planning strategy. Moreover, we will define the suitable actions to be taken to avoid the EV bearing breakdowns, and we will extend its functionality to reach the nearest suitable replacement time. The proposed system will help our partner to be in control of the EV performance and to find enhanced maintenance actions.

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Faculty Supervisor:

Soumaya Yacout

Student:

Partner:

Solutions Serafin

Discipline:

Engineering

Sector:

Transportation and warehousing

University:

Polytechnique Montréal

Program:

Accelerate

Real-Time Control of Integrated Stormwater Systems using a Model Predictive Control Approach

Burdened by aging infrastructures, urbanisation and climate change, municipalities are seeking innovative solutions to address urban water management. To mitigate flooding, riverbank erosion as well as stormwater-caused pollution, many authorities are now relying on green infrastructures and intelligent flow control instead of the traditional grey infrastructures (e.g., basins and pipes). The objective of this research is to develop an innovative approach to dynamically control emptying flows from stormwater systems to eliminate or reduce flooding and to limit the pollutant loads discharged in the receiving waters. For this, we propose to use a Model Predictive Control (MPC) approach. Using rainfall predictions, measurements and models, the MPC will control gate openings to optimize the use of the stormwater systems’ conveyance and storage capacities in view of minimizing flood risk, erosion and pollution.

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Faculty Supervisor:

Peter Vanrolleghem;Dirk Muschalla

Student:

Partner:

Tetra Tech QI Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Using Machine Learning to Predict 30-Day Risk of Hospitalization, Emergency Visit or Death Among Albertans Who Received Opioid Prescriptions

When utilizing and implementing ML for prediction using administrative health data, two key issues are ML algorithm evaluation and generalizability21. Current approaches evaluate model performance by quantifying how closely the prediction made by the model matches known health outcomes. Evaluation metrics include sensitivity, specificity, and positive predictive value, as well as measures such as the area under the receiver operating characteristic (ROC) curve, the area under the precision-recall curve, and calibration. Because no single measurement reflects all of the desirable properties of a model, several measurements typically are reported to summarize the performance of the model16. Furthermore, model performance ultimately comes down to discrimination and calibration22. Discrimination is usually quantified using a concordance statistic (area under ROC) while calibration is graphically represented as observed to expected ratios.
Generalizability is also an issue that must be acknowledged in ML prediction settings21. ML models trained in one setting may not be valid in another. The same is true for populations. Furthermore, even ML algorithms that are considered generalizable may quickly become outdated as treatment guidelines or the population changes thus requiring model updating and re-evaluation 21.

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Faculty Supervisor:

Irene Cheng

Student:

Partner:

OKAKI

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

Integration of Simultaneous Localization And Mapping (SLAM) to improve workflow of reconstruction projects and space utilization

The focus of this project will be how modern technologies, specifically static and mobile laser scanners, drone photogrammetry, and Virtual Reality (VR) can be applied to solve issues related to renovating and utilizing (repurposing) old buildings. This is a multi-disciplinary approach with college interns from Geomatics Engineering and Architecture Engineering programs.

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Faculty Supervisor:

Blair Bridger;Deirdre Snook

Student:

Partner:

People of the Dawn Indigenous Friendship Centre

Discipline:

Engineering

Sector:

Public administration

University:

College of the North Atlantic

Program:

Accelerate

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