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

Development of applications of the NanoCleanSQ surface coating in the fight against COVID-19

Envision SQ Inc. (EnvisionSQ), in a joint effort with the University of Guelph, is currently working on applications of their NanoCleanSQ disinfectant-sanitizer to help slow down the spread of the SARS-CoV-2 virus (the virus that causes COVID-19). NanoCleanSQ is a clear coating material and acts as a photocatalytic disinfectant that can be easily applied to virtually any hard surface to help prevent spread of viruses. While initial testing results indicate the coating kills bacteria and viruses, additional research is needed to understand how it can be deployed in various situations such as hospitals and long term care facilities. The results of the research undertaken by the interns is expected to lead to new product development and commercialization opportunities for EnvisionSQ.

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Faculty Supervisor:

Bill Van Heyst

Student:

Danika Ferguson;Jared Philpot

Partner:

Envision SQ Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Guelph

Program:

Accelerate

Novel service delivery models for children with neurodevelopmental disabilities and their families in light of the COVID-19 pandemic

COVID-19 has changed the way we access services in the community. Many services are now being offered online or over the phone instead of in a building. While this works for some families, families who are new to Canada, do not speak English, and don’t have access to technology may not be able to receive services during the pandemic. Children with brain-based disabilities may have difficulty with their behaviour, paying attention, and socializing with other children. This can add extra stress to parents during the COVID-19 pandemic. In this research project, we will speak with and ask questions of families, government representatives, and people who provide services to young children with brain-based disabilities. Results will be used to make recommendations as to how we can provide better service to families with young children with brain-based disorders during the COVID-19 pandemic.

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Faculty Supervisor:

Sarah Macoun

Student:

Buse Bedir

Partner:

Child Development Foundation of British Columbia

Discipline:

Psychology

Sector:

Health care and social assistance

University:

University of Victoria

Program:

Accelerate

Development of a rapid and sensitive test for food spoilage bacteria

Food waste is a multibillion-dollar problem in Canada and around the world. Some level of waste may be unavoidable, but large amounts of safe food are lost every year because of the arbitrary nature of measuring food spoilage. This is especially true at the wholesale and retail level for meat products. Food typically spoil in a highly predictable and reproducible way. Here, we will develop a device that will allow an untrained worker to quickly assess whether food is spoiled to allow a rational design about whether that product is fit for consumption or should be discarded.

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Faculty Supervisor:

Joseph McPhee

Student:

Raymond Huynh

Partner:

CleanForm Science CA Inc.

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

End-to-End Vulnerability Analysis of a No-Trust IoT Security Ecosystem

Cyber-Physical Systems (CPS) combine communication and information technology functions to the physical components of a system for purposes of monitoring, controlling, and automation. The power grid is becoming one of the largest CPS, where grid components are controlled based on the synergies in the cyberspace. CPS hold a great promise to improve the efficiency and productivity of numerous sectors in Canada and around the world. However, cyber-security is a major concern in CPS including the smart grid where an intrusion in one part of the system can cause a failure in the entire network if not detected and dealt with in a timely fashion. The main objective of this research project is to develop a realistic model to enable the implementation of machine learning-based algorithms to detect cyber-attacks in a smart grid environment.

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Faculty Supervisor:

Irfan Al-Anbagi

Student:

Brant Geddes

Partner:

Smart Talk Beacon

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Regina

Program:

Accelerate

Design Analytics and Design Reporting Tools

Design data is broadened beyond specifying built-environments to support evidence-based decision-making in the early phases of design. For using data, designers usually rely on specialized data visualizations. There is a need for interfaces specifically tailored for reporting designs with their form and performance data to and for seeking feedback from the other stakeholders who are not directly involved in design. Given their diversity and complexity of the design data, such interfaces are hard to develop. This project aims to identify, develop, and validate practical key features of data analytics interfaces for sharing design alternatives with the design stakeholders to support online group decision-making. These interfaces will become part of a platform for data-driven design exploration. This combines the fields of visual analytics and design, which we call design analytics. Using Design-through-Research with use-case driven software development methods, the project will demonstrate use of design analytics in group decision-making in design workflow.

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Faculty Supervisor:

Halil Erhan;Robert Woodbury

Student:

Osama Alsalman

Partner:

Stantec Consulting

Discipline:

Interactive arts and technology

Sector:

University:

Simon Fraser University

Program:

Accelerate

Respiratory Health System and Pandemic Early Warning System

The goal of this project is to develop a low-cost ventilation system which accurately detects and records both patient treatment data and environmental data is in great need. Further, such a system will allow to create a global health map. This research and resulting hardware and software will not only benefit the current research of COVID-19, but also assist in the long term identification and management of potential respiratory pandemics.

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Faculty Supervisor:

Fraaz Kamal;Yunwei Ryan Li;Marek Reformat

Student:

Mayara Nascimento de Oliveira;Owais Ahmed Amin;Marcelo Tabarelli

Partner:

Growing Greener Innovations

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

Program:

Accelerate

Modeling Aerosol Dispersion in Dental Offices

The Ontario Dental Association requires the time of three hours between two clients in a dental office to prevent the transmission of COVID-19; however, this strict guideline poses a great challenge to the economics of dental business and the recovery of Ontario economy. The results of this study will help understand the COVID-19 transmission in dental offices and help develop technologies for the proper control of aerosols and splatters generated during the dental procedures. Dispersion and removal of aerosols generated from a specific dental operation will be modelled to understand how aerosol disperses and transports in the facility. The partner organization provides consultancy and professional training in filtration and separation technologies, clean air technologies. The proposed CFD modeling work will provide relevant guidance on product development for occupational health protection during pandemics, and help the company sustain its technical consulting services to dental office industry, in and out of Ontario.

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Faculty Supervisor:

Fue-Sang Lien

Student:

Maryam Razavi

Partner:

Canapril Solutions Inc.

Discipline:

Engineering - mechanical

Sector:

Other

University:

University of Waterloo

Program:

Accelerate

Quantification of climate change impacts of selected construction material supply chains

Research the existing stock of Environmental Product Declarations and underlying Product Category Rules in selected material categories including wood, steel, and glass. Evaluate the accuracy and comparability of the population, identify top sources of embodied carbon impact variation in the supply chain, and provide estimates of the sensitivity of the embodied carbon impact of those supply chain factors. Document these differences in formats that can be published and, incorporated into BuildingTransparency.org’s free EC3 software service, for which C Change Labs is the primary developer. BuildingTransparency.org is a Washington State 501c(3) not-for-profit focused on climate change impacts in construction.

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Faculty Supervisor:

Qingshi Tu

Student:

Shiva Zargar Ershadi

Partner:

C Change Labs

Discipline:

Forestry

Sector:

Information and cultural industries

University:

University of British Columbia

Program:

Accelerate

Validation of Novel, Tumor Microenvironment-targetedImmunomodulatory Biological Therapeutic

ImmunoBiochem is developing novel anti-cancer therapeutics to address unmet need in intractable solid tumors. Because solid tumors are highly heterogeneous and evasive, recognizing cancerous cells, while avoiding damage to normal tissue, is a challenge. As a result, many targeted therapies quickly come up against resistance, resulting in patient relapses. ImmunoBiochem is solving the issue of tumor versus normal recognition by exploiting unique cancer targets in the tumor environment – a collection of features that are uniquely present in tumors and absent in the environment of normal cells. This provides for an ability for broader targeting and opportunity to avoid many common resistance mechanisms. The intern will help advance the validation of novel drug candidates in models of various cancer types and subtypes, to understand efficacy and how to ultimately translate the findings to initiate clinical trials in human patients.

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Faculty Supervisor:

Robert Rottapel

Student:

Tian Sun

Partner:

ImmunoBiochem Corporation

Discipline:

Medicine

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Efficient Screening Method for Novel Fluorescent Emitters

Canadian public and private researchers have taken an interest in a new class of light-emitting materials which can produce better colour in OLED smartphone and television screens. Currently, the only way to fully confirm that a specific material in this class has the desired properties is to build it into a prototype OLED pixel. This slows discovery, because researchers need to figure out how to make larger batches of a specific material just to confirm whether that material is useful. This project will create a testing method that only needs small quantities, which is based on a method that was proven to work for a similar kind of material. When complete, researchers will be able to test materials more quickly, which will speed up the process of creating materials for specific tasks.

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Faculty Supervisor:

Timothy Bender

Student:

Nina Francesca Farac

Partner:

Amber Molecular Inc.

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Machine-learning-based posture identification from dynamic seat sensors

Sitting for long periods of time has negative health effects that could be solved by changing posture throughout the day. The solution lies in the use of sit-stand desks, active seats, and automated reminders to change position. For this purpose, this project focuses on developing software that can intelligently determine a person’s posture using sensors located in a dynamic seat. Data will be collected from people using the Formid Dynamic Seat, which will then be used to develop and test machine learning algorithms. The results will benefit the industry partner in that they will be able to incorporate the resulting software into a mobile app that can let the person know that they need to move.

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Faculty Supervisor:

Ana Luisa Trejos

Student:

Ghazal Farhani

Partner:

Formid

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

Western University

Program:

Accelerate

Tightly coupled visual-inertial-LI DAR SLAM for real time application

Since Amazon robotics expanded the use of drones to package deliveries to customers, drone applications have been expanded to many industries along with its ability to perform various tasks autonomously. The fundamental technology of drones’ autonomy comes from perceiving its surrounding, creating its own map based on onboard sensors and estimate its location within the map. This technology, also known as Simultaneous Localization and Mapping (SLAM), has been on the rise especially in mining and construction industries for surveying and mapping the site more efficiently; thus, many research works have been performed to improve robot’s SLAM technology. Although various sensor suites have been researched to improve SLAM performance, this project focuses on the novel contribution of developing a robust and accurate 3D SLAM by jointly optimizing stereo cameras, IMU and LiDAR measurements. This project will not only advance the field of autonomous navigation but will also help ARA Robotique to be competitive in the UAV market.

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Faculty Supervisor:

James Richard Forbes

Student:

Kyungmin Jung;Mitchell Cohen

Partner:

ARA Robotique

Discipline:

Engineering - mechanical

Sector:

University:

McGill University

Program:

Accelerate

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