Innovative Projects Realized

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

30508 Completed Projects

2882
AB
5105
BC
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projects by Category

Machine learning algorithms utilization for impairment screening using balance detection

In this project the human body movement and its balance will be studied, and artificial intelligence-based algorithms will be developed in order to detect the body movement and the posture in real-time. Specific camera technology will be utilized in order to gather required data of the human movement and the environment. The data will then be filtered and analyzed. The cleaned data will then be used in a artificial-intelligence-based system to detect the status of the movement. Finally, the result of the movement detection will be integrated with other indicators in order to detect the imbalances or visible impairments.

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Faculty Supervisor:

Jiannan Wang

Student:

Partner:

Cannsight Technologies

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Technology; Information and Communications Technology

University:

Simon Fraser University

Program:

Accelerate

Application of Brain 23Na “Big Data” for Future Disease Classification

Sodium is a chemical ion which is essential for a healthy brain. The body naturally regulates its concentration inside and outside of cells through normal metabolism. Disruptions in this intricate balance can be caused by various neurological disorders, such as multiple sclerosis, concussion, or Alzheimer’s disease. In order to provide personalized medical care, a “big-data” approach is required whereby an individual’s brain can be compared to a standardized template or atlas – unfortunately, a sodium atlas, representing normal sodium concentrations, is not currently available. This project’s goal is to use Ceresensa’s expertise in coil design and manufacturing to create an atlas which can be used to further research into sodium’s role into brain illnesses.

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Faculty Supervisor:

Michael Noseworthy

Student:

Partner:

Ceresensa

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Improving 23Na – Magnetic Resonance Spectroscopic Imaging through RF Coil Development

Magnetic Resonance Imaging (MRI) machines use radiowaves and large magnets to safely produce pictures from the insides of the body. The radiowaves are emitted and detected by special antennas that surround the body. Most MRI scanning involves measuring of water in the body. But other atoms, like sodium, can also be seen too. This work described here involves designing new antennas to safely see sodium inside the body. More specifically these antennas will be designed based on novel geometric fractal shapes, which are regularly seen with cell phones. These shapes give a much better signal than traditional designs used currently with MRI.

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Faculty Supervisor:

Michael Noseworthy

Student:

Partner:

Ceresensa

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Productivity Tracking and Analysis of Earthmoving Operations

Monitoring and control earthmoving operations such as highways and dams construction; require the collection of large amounts of data. Collecting this data manually is time-consuming and it lacks accuracy, so there is a necessity for using automated data collection systems in such operations. Most of nowadays available data acquisition systems are costly back boxes, where the user can not use it based on his/her customised needs. The proposed model allows the customization of the data acquisition system using open source and low cost technologies, in which some sensors are selected to acquire data related to the different factors that could influence the productivity of earthmoving operations. The collected data will be transmitted to a server (cloud) instantly using communication protocols like WiFi. This data is usually collected in a raw format where it has no meaning, so should be processed to have meaningful information that helps in efficiently managing the projects. The proposed model process the collected data using cloud computing to allow higher security and flexibility. The results from data proccing could be retrieved using internet browsers by accessing a secure designated webpage using a user name and password. TBC

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Faculty Supervisor:

Osama Moselhi

Student:

Partner:

Pomerleau

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

Concordia University

Program:

Accelerate

Techno-Economic Feasibility of Wastewater Heat Recovery for Cold Climates like Canada

Wastewater is an abundant and severely underutilized energy source in North America. Sewers experience predictable flow profiles and nearly constant temperatures between 18 ?C and 20 ?C year-round. When wastewater is used in conjunction with heat pumps, it can serve as an energy source and sink to provide both heating and cooling to buildings. Therefore, there exists the potential to extract significant amounts of thermal energy from the wastewater using heat exchangers, resulting in substantial economic and environmental benefits. The proposed work is to investigate the techno-econo-environmental feasibility of sewage-based hybrid wastewater heat recovery energy systems suitable for North American residential, commercial, and institutional buildings via system modeling, simulation, and optimization of such hybrid systems to be validated with experimental results from a few pilot systems currently being developed.

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Faculty Supervisor:

Alan Fung

Student:

Partner:

Noventa

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

Toronto Metropolitan University

Program:

Accelerate

Pricing and Diversification of Flood Risk in Canada

Flood is the single most important natural hazard in Canada. Since 2015, private (overland) flood insurance coverage is gradually being offered to Canadian homeowners and demand for such protection is on the rise in Canada and elsewhere. For the product to be viable to the insurers and to the customers in the long term, flood insurance needs to be adequately priced and managed with a large and well diversified portfolio. Using a combination of climate and statistical models, the aim of this research project is to analyze pricing and especially spatial diversification of flood risk in Canada. The project will help insurance companies manage flood insurance in the short-term and determine whether such insurance will be viable in the long term as a result of climate change.

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Faculty Supervisor:

Mathieu Boudreault

Student:

Partner:

Co-operators (General Insurance);Canadian Institute of Actuaries

Discipline:

Mathematics

Sector:

Other services (except public administration)

University:

Université du Québec à Montréal

Program:

Accelerate

Embedding Techniques of Audio Segments Emphasizing Meaningful Semantic Characteristics

This project will develop artificial intelligence techniques to identify characteristics in audio samples that relate to real-world descriptions of sounds. When humans listen to various samples of sounds of a same category, they intuitively affix qualitative words to these sounds. The objective of the research is to find ways to let an AI algorithm find out these characteristics, and rank sounds based on them. For example, given a database of voice sound samples, the algorithm could automatically rank them in order of “kindness” in the voice, or “shyness”. The developed algorithms will help Ubisoft be more efficient and creative when designing the sound aspect of video games.

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Faculty Supervisor:

Ghyslain Gagnon

Student:

Partner:

Ubisoft Toronto

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing

University:

École de technologie supérieure

Program:

Accelerate

Development and experimental study of a vibration controller for a robotic system interfaced with machining operations.

Robotic arms are used extensively in machining applications due to a large working envelope and easy access to restricted areas. However, low stiffness of the robot arm caused by joint flexibility introduces additional degrees-of-freedom and vibration modes, which leads to the deterioration of positioning performance. To attenuate these induced motion tracking errors and vibrations, this research presents the development and experimental study of an adaptive control scheme, which combines a state feedback and an adaptive feedforward controller to shape robot dynamics into a desired dynamics that does not produce link oscillations. The proposed method is demonstrated on a six-joint robot manipulator, namely SCOMPI developing at Hydro-Québec’s research institute, performing machining tasks in situ maintenance of hydro turbine runners. Reliability and robustness of the proposed method allow the SCOMPI robot to maximize machining performance and to move SCOMPI technology forward over competitive products.

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Faculty Supervisor:

Zhaoheng Liu

Student:

Partner:

Institut de Recherche Hydro-Québec

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

École de technologie supérieure

Program:

Accelerate

Net Zero Energy Townhomes: Simulation Comparison between Software Platforms, Calibration Study and Uncertainty Quantification

Designing, building, and verifying highly energy efficient buildings presents complex challenges. Environmental factors such as the local weather, temperature swings, angle of the sun, etc. impose conditions on the building which itself has unique characteristics like its particular construction method, materials used, geometry and orientation, windows of specific properties, and so on. Then, there are active measures taken to make it livable, such as heating and cooling, lighting, using appliances, and such. The design team must take all of the factors and their complex interactions into account for the design, which compels them to use computer simulations. The problem in the industry, however, is that 1) various software tools produce different results, 2) adjusting the computer model to the actual building performance (model calibration) is often done non-systematically, and 3) associated model uncertainties are ignored. This study aims to help address the three issues with a real-life case study.

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Faculty Supervisor:

Scott Bucking

Student:

Partner:

S2E Technologies Developments Inc

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

Supporting Ontario EcoSchools: building capacity in schools and school boards to implement environmental initiatives

Environmental education is essential for young Canadians, yet educators have few resources to meet this rising demand. Ontario EcoSchools is addressing this disconnect by providing an environmental certification program and environmental education resources for Ontario elementary and secondary schools. Ontario EcoSchools certification program motivates students, teachers and staff members to implement initiatives to reduce waste, conserve energy, green the schoolyard and improve environmental literacy. Since 2002, Ontario EcoSchools has seen tremendous growth in the number of schools seeking certification, from just 13 schools in 2003 to 1518 schools in 2011. This project will allow Ontario EcoSchools to critically assess schools certification portfolios and onsite actions, determine the type of required environmental education resources and assist with their development of an online community resource database to help schools seeking certification.

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Faculty Supervisor:

Ian Colquhoun

Student:

Partner:

Ontario EcoSchools

Discipline:

Sociology

Sector:

Education

University:

Western University

Program:

Accelerate

Modeling DNA Adducts as Cancer Diagnostic and Therapeutic Markers: Computational Chemistry Studies of the Structure-Function Relationships of DG-C8-A?C Adducts

Recent nucleic acids research has focused on the formation of genotoxic DNA adducts as covalent modifications of DNA that often result from carcinogen exposure; human-made chemicals can also cause DNA damage through bulky DNA adduct formation. DNA adducts are not only markers of carcinogenic exposure but also alter the regulation of oncogene transcription and standard DNA replication. A potent DNA adduct of A?C, a carcinogenic heterocyclic aromatic amine produced in high quantities in tobacco smoke, has been identified (dG-C8-A?C), but the exact pathways and outcomes of its replication by different DNA translesion polymerases involved in DNA repair remain largely unknown. Accordingly, they will be investigated with standard computational chemistry, namely density-functional theory and molecular dynamics simulations, to shed light on the structure-function of these bulky DNA adducts and their mutational signature associated with several cancers, yielding crucial information to exploit them as diagnostic or therapeutic markers of cancer.

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Faculty Supervisor:

Gilles Peslherbe

Student:

Partner:

Henan University of Technology

Discipline:

Physics

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Synthesis an Characterization of luminescent Nanostructures

We use nanoscale gold particles to tune luminescence properties of light emitting lanthanide complexes. Metal nanoparticles, e.g. of gold and silver, absorb light in the visible region due to so-called plasmonic resonance. Thus, interaction between lanthanide luminescence and this resonance is expected. By varying the properties of the complex and the shape and surface of the nanoparticles the luminescence shall be tuned. The distance between the nanoparticle core and the emitting species is responsible for whether the luminescence is quenched or enhanced. In order to monitor this interaction lifetime measurement are necessary which will be carried out at Prof. Capobianco´s laboratory.

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Faculty Supervisor:

John Capobianco

Student:

Partner:

Universität zu Köln

Discipline:

Life Sciences

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

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