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

Deep Learning Method for Micromotion Detection and Mental Health Disease Diagnosis

Over the past few decades, mental disorders (e.g., depressive and anxiety) have become a significant medical burden for people of all ages. According to the survey performed by the World Health Organization (WHO), at least one out of ten people in the world suffers from mental health diseases (i.e., mental disorders, neurological disorders and addition). Many factors, such as heredity, work pressure and aging, can attribute to these disorders and degradations. However, some of these mental health diseases are preventable and treatable. In this project, we aim to develop a software system, especially a mobile app, for the detection of mental health diseases, in particular depression for now. This app uses facial and audio pattern recognition techniques, GPS and gait to assess mental health conditions for patients which will help with early diagnosis of depression symptom and trigger clinical intervention if necessary.

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Faculty Supervisor:

Jie Chen

Student:

Shiang Qi;Ben Flanders

Partner:

Hidaca Inc.

Discipline:

Engineering - computer / electrical

Sector:

Life sciences

University:

University of Alberta

Program:

Accelerate

High Performance Clustered Secure Storage Solution

45 Drives—a Nova Scotia based company—offers a high-density, low-cost data storage solution called the Storinator. While this product has been very successful, clients have indicated they would like a clustered solution which offers similar performance and redundancy, without sacrificing security or drastically increasing the cost. Researchers at the University of New Brunswick have been identified as a good fit for creating a clustered software-architecture in tandem with 45 Drives’ hardware-architecture. This software solution will be created from other software products which release their code for free called Free Open-Source software, or FOSS. The software-architecture must keep data secure, be resilient to failure and perform its tasks quickly. To the best of our knowledge, no one offers a storage solution with the properties described above.

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Faculty Supervisor:

Kenneth Kent

Student:

Fatemeh Khoda Parast

Partner:

45 Drives

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of New Brunswick

Program:

Accelerate

NOVEL IONIC LIQUIDS FOR HEAVY OIL ENHANCED RECOVERY

The use of ionic liquids (ILs) in enhanced oil recovery is considered a new and promising technology as it has never been tested in any pilot plant or reservoir field. ILs are very similar to surfactants as they help reduce the interfacial tension, change the wettability of the reservoir, and some have strong viscous effect, all essential factors in recovering more heavy oil. The technology can also be used for medium and light oil recoveries with other kinds of ionic liquids. After an initial screening, the best ionic liquid will be used in a chemical enhanced oil recovery application where an alkali and a polymer are added to increase the recovery factor. ILs have the potential to be the most promising Chemical enhanced oil recovery (EOR) technology in the history of heavy oil production. The economic benefits to Saskatchewan and Canada could be extraordinary.

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Faculty Supervisor:

Amr Henni

Student:

Ali Larbah

Partner:

Petroleum Technology Research Centre

Discipline:

Engineering - other

Sector:

Oil and gas

University:

University of Regina

Program:

Accelerate

Development of nano-colloid with gold nanoparticles to detect Legionella pneumophila using the principle of localized surface plasmon resonance

Legionnaires is a disease caused by the bacteria Legionella pneumophilia present mostly in aquatic environments. The first outbreak of this disease was recognized in 1976 in Philadelphia and the most recent one in July 2019 in Atlanta. Diagnosis of the disease isn’t early and thus need to be prevented by regular treatment. Treatment of water needs information about the water quality which needs on-site based sensors to detect the different pathogens present. At present, there is no viable solution to detect Legionella on site with confidence. This project focusses on developing hand-held optical sensors for rapid detection of Legionella. The completion of this project will address a real world problem and will allow the industry partner to create solutions for liquid borne bacteria. Municipalities, cooling towers, water treatment facilities, business users will be able to use this to assess water quality and make appropriate treatment procedures to avoid any outbreak.

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Faculty Supervisor:

Ishwar Puri;Fei Geng;Igor Zhitomirsky

Student:

Srivatsa Aithal;Aiswarya Mathai

Partner:

Genemis Laboratories

Discipline:

Engineering - biomedical

Sector:

Life sciences

University:

McMaster University

Program:

Accelerate

Printing of Collagen microgels

Developing technology capable of onsite medical diagnostics is crucial for health-care delivery in clinical and emergency settings. To perform on-site diagnostics, health-care practitioners need compact, inexpensive, and user-friendly equipment. Alentic Microscience has developed a system that uses small volumes of blood for cell counting and serum tests, occurring at the site of blood extraction. This system makes single molecular layers of reagents on the sensor surface, which when exposed to light allow the system to provide valuable diagnostics about the sample. The proposed project will increase the system’s range, by moving from the single monolayers to 3D gels. By using 3D gels, the increased volume will allow the addition of multiple molecular tags to the sample that can identify and quantify multiple components simultaneously. This work will increase the dynamic range of the current technology, allowing it to be useful for biological diagnostics in even more situations.

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Faculty Supervisor:

Laurent Kreplak

Student:

Gurkaran Chowdhry

Partner:

Alentic Microscience Inc

Discipline:

Geography / Geology / Earth science

Sector:

Medical devices

University:

Dalhousie University

Program:

Accelerate

Near-Infrared Dyes for Next-Generation Motion detection technology

Currently, the traditional use of the dye-sensitized solar cell (DSSC) is well-known in the science community as an effective photovoltaic technology, where it works best in diffuse lighting conditions. With the insights brought from this research project, the DSSC can also be transformed into an optically sensing motion sensor based on the dye utilized within it. This project will focus on synthesizing a family of organic dyes that absorb in the near-infrared region, optimal for detecting movement. The second half of the project will utilize those dyes in device fabrication. These cells will be re-envisioned into a coating that can be applied onto existing windows so that the DSSCs can dually function as light harvesting windows and safety features (eg. security cameras that pick up motion and send a signal to another device alerting the homeowner).

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Faculty Supervisor:

Bryan Koivisto

Student:

Tavneet Singh

Partner:

Science Discovery Zone

Discipline:

Biochemistry / Molecular biology

Sector:

Energy

University:

Ryerson University

Program:

Accelerate

Development of activated carbon from petroleum coke and electrolyte design for electrical double-layer supercapacitors – Part 3

Supercapacitors are electrochemical energy storage devices that promise fast charge-discharge rate, high power density, and long cycle life. However, low energy density, high cost, and safety risk of supercapacitors are yet to be addressed in order to deploy the technology into wholesale grid storage. This research project will design low-cost and high-performance electrode and electrolyte for supercapacitors. We will develop activated carbon from petroleum coke as the main component of electrode material, and design a novel high-voltage and safe electrolyte to improve the energy and power density and safety of supercapacitors. This project will help the industrial partner, Atlas Power Generation Inc., commercialize supercapacitor technology for grid scale applications.

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Faculty Supervisor:

Jian Liu

Student:

Behzad Gorji Pour Shafiee

Partner:

Atlas Power Generation

Discipline:

Engineering - other

Sector:

Energy

University:

Program:

Accelerate

Design of autonomous robotic system for removal of Porcupine Crab spine

Porcupine Crab (Neolithodes grimaldii) inhabits the seabed off the Coast of Newfoundland and Labrador and in the eastern Arctic as a by-catch in the turbot gillnet fishery. This research project focuses on developing automatic robotic technology for the removal of Porcupine Crab spines to ease the crab processing for potential future development of a Porcupine Crab fishery. Based on extensive research experience in robotic system design, the research team will propose a novel robotic mechanism, integrated with the state-of-the-art artificial intelligence method and sensing technology, to precisely and efficiently remove the sharp spines and thus significantly ease the danger and impracticability of processing of porcupine crab.

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Faculty Supervisor:

Ting Zou

Student:

Haodong Wu

Partner:

Nunavut Fisheries Association

Discipline:

Engineering - mechanical

Sector:

Fisheries and wildlife

University:

Memorial University of Newfoundland

Program:

Accelerate

Detecting Credit Transaction Fraudulent Behavior Using Recurrent Neural Networks

Fraudulent activities are hard to detect, but they cost financial institutions millions of dollars in monetary losses and legal costs every year. Millions of dollars are being lost in credit transactions as criminals are finding new, more sophisticated ways to conduct financial crime. This research project examines novel ways of detecting fraudulent behavior using powerful tools such as Recurrent Neural Networks, a type of machine learning model that is well suited for sequence or historical data.

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Faculty Supervisor:

Lourdes Peña-Castillo

Student:

Ruben Antonio Chevez Guardado

Partner:

Verafin Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Memorial University of Newfoundland

Program:

Accelerate

Sustainability Analysis of the VOCs Abatement Solution Proposed by SunHub Inc. for Small and Medium Enterprises in the Furniture Industry in China

Volatile Organic Compounds (VOCs) are major contributors to smog, causing harm to both the environment and human health. However, VOCs control faces tremendous challenges. The aggregation of low VOCs concentration emitted by small and medium-sized enterprises (SMEs) have significant environmental and social impacts. However, SMEs find the current “on the market” technologies impractical and too expensive in initial investments and operational maintenance costs. To help alleviate the problem, SunHub Inc. proposed a solution, including a R&D project of a hybrid of nonthermal plasma (NTP) and catalyst technology. The objective is to develop a safe, effective and economical solution for removing VOCs emitted by SMEs in the furniture industry. By examining whether this solution is sustainable through the case study research conducted by an accelerate entrepreneur, SunHub will gain valuable guidance and confidence in real-life problem-solving, making great contributions to sustainable future.

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Faculty Supervisor:

Will Low

Student:

Joan Zhao

Partner:

SunHub Inc

Discipline:

Environmental sciences

Sector:

Professional, scientific and technical services

University:

Royal Roads University

Program:

Accelerate

Synchronous Collaboration in Augmented Reality Utilizing Individual and Collaborative Views

The project investigates how collaborative tasks can be enhanced in AR environments. The intern will develop three approaches to present shared information in a co-located AR setting and conduct usability studies comparing these approaches. The first approach will present information in the same location and same orientation to the collaborators, the second will present the information in the same location but virtually oriented to both collaborators and the third approach will allow collaborators to place information in different locations while maintaining virtual ties between the displays for the two users. The most promising approach will be integrated in VizworX’ AR tools.

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Faculty Supervisor:

Frank Maurer;Cathy Ryan

Student:

Dianna Yim

Partner:

VizworX

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of Calgary

Program:

Accelerate

Stories Incarnate: Using Body-tracking/Body-Sensing Technology to Create Interactive Narrative Experiences for Audiences

Ryerson’s Synaesthetic Media Lab is working with Cirque du Soleil Entertainment Group’s creative design studio, 4U2C, to develop several ways for audiences to meaningfully interact with live performance. This project is looking at how tracking sensors, computer vision, and digital displays can be used to track audience movements and/or emotions for audiences to be able to participate in the storytelling of a live show. Through this research, 4U2C — and Cirque du Soleil Entertainment Group and its numerous ventures — will be equipped with new, immersive design concepts and technologies that will bring audiences more closely into the co-creation role, as they partake in determining how a live story will unfold.

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Faculty Supervisor:

Alexandra Mazalek;Louis-Etienne Dubois;Richard Lachman

Student:

Marisa Samek

Partner:

Cirque du Soleil

Discipline:

Journalism / Media studies and communication

Sector:

Arts, entertainment and recreation

University:

Ryerson University

Program:

Accelerate

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