Innovative Projects Realized

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

29670 Completed Projects

2811
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4990
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801
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663
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825
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8841
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9197
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95
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568
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1088
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Projects by Category

Cost-Effective Computer Simulation for the Offshore and Marine Industry

Computer simulations have been widely used by the offshore and marine industry, but they typically use different software to simulate different components of a single operational scenario. For example, the tool can be used for the analysis of wave loads of a moored structure in ice infested areas, eliminating the need for analyzing wave load, mooring tension, and ice loads, separately. This project looks to examine how multi-physics, multi-phase simulation software can improve the safety of personnel and assets by simulating complex marine scenarios in an integrated approach that is currently not available.

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Faculty Supervisor:

David Molyneux

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Clean Technology; Oil and Gas

University:

Memorial University of Newfoundland

Program:

Accelerate

Shipborne Sea Ice Classification Using Neural Networks

The purpose of this project is to take existing state-of-art machine learning techniques and implement them for ice classification in polar seas. Ice classification plays a critical role in any icebreaker voyage. An ice specialist onboard the icebreaker is required to classify all ice environments encountered. This process is tedious and time consuming. This project aims to automate this process. In using cutting edge neural networks, images taken from aboard icebreakers can be used to classify each pixel in an image giving overall context and information about the environment. These ice classifications would serve to generate important documentation for icebreakers as well as contribute to the formation of ice maps for the Canadian Ice Service.

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Faculty Supervisor:

Oscar de Silva;Weimin Huang

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Environmental Science and Technology

University:

Memorial University of Newfoundland

Program:

Accelerate

Fiber Optic Hydrophone Array

The proposed work targets the development of a fiber optic hydrophone array for underwater acoustics detection and recognition, with the potential for applications in national defense. We propose a new concept of using a small-size low-cost fiber optic hydrophone that are nearly undetectable and can be deployed in a dense array across a wide area and depths. The new hydrophone technology will offer a real-time capability and the required dynamic range to detect and track underwater as well as surface vessels. Working closely with the partner organization would help guide the development to meet requirements of real-life applications. Furthermore, the partner organization would participate in marketing research and steps towards commercialization.

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Faculty Supervisor:

Vlastimil Masek

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Technology; Other

University:

Memorial University of Newfoundland

Program:

Accelerate

Évaluation de différents protocoles de mise en diapause pour Trichogramma brassicae

Le projet vise à déterminer le meilleur protocole de mise en diapause de Trichogramma brassicae. Cet insecte est un parasitoïde s’attaquant aux oeufs de la pyrale du maïs et est utilisé depuis plusieurs années au Québec pour lutter contre cette pyrale réduisant par ce fait la quantité de pesticide utilisé par les agriculteurs. La diapause est un arrêt de l’activité ou du développement chez les insectes lors de conditions défavorables. Dans le cas des trichogrammes, ceux-ci entre en diapause afin de passer l’hiver. Nous cherchons donc à utiliser cette caractéristique biologique afin de pouvoir entreposer les pupes de T. brassicae au froid pour de longue période. L’acquisition par Anatis Bioportection d’un protocole permettant l’entrée en diapause des trichogrammes lui assurera une production durant toute l’année l’aidant à être plus compétitive.

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Faculty Supervisor:

Éric Lucas

Student:

Partner:

Anatis Bioprotection Inc.

Discipline:

Life Sciences

Sector:

University:

Université du Québec à Montréal

Program:

Accelerate

Examining the role for intimal cell communication in early atherosclerosis

Atherosclerosis is a disease defined by unresolved inflammation in the major arteries. High cholesterol is a major risk factor, resulting in fatty lesions developing silently for decades before causing heart attacks and strokes. Currently, no therapies exist that target the cells of the artery wall to suppress this disease. Myeloid cells (MCs) are white blood cells found in the inner artery wall, residing under a barrier of cells called endothelial cells (ECs). In the aorta, MCs are found only in areas where lesions grow. In mice with high cholesterol, arterial MCs engulf lipid and become “foam cells”. This is the first step in the formation of atherosclerosis. I believe that MCs and ECs communicate with each other within the artery wall and elevated cholesterol disrupts this communication. This work aims to target the cells within the artery, to restore proper cell communication, reduce inflammation, and ultimately decrease cardiovascular disease.

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Faculty Supervisor:

Myron I. Cybulsky

Student:

Partner:

Industrial Biodevelopmental Laboratory

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Ocean wind and wave parameter estimation using X-band marine radar images with rain mitigation

The real-time monitoring of sea surface wind and wave information are crucial to the safety, performance and efficiency of various weather-sensitive on- and offshore operations, such as oil & gas platform drilling, port operations and offshore wind farming. This project plans to propose an accurate and robust method to estimate sea surface wind and wave parameters (e.g., wind speed, wind direction, wave height, etc) using a type of sensor called X-band marine radar. Compared to other traditional sensors such as buoy, X-band marine radar is a “dry” sensor deployed above water, which is low on maintenance cost. Although various methods have been developed to wind and wave information using radar images generated by electromagnetic waves, the presence of rain will negatively affect the quality of the image, leading to low estimation accuracy. In order to solve this problem, this project aims to develop a novel method to mitigate the influence of rain on radar and further improve estimation accuracy based on machine learning techniques.

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Faculty Supervisor:

Weimin Huang

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Information and Communications Technology; Artificial Intelligence

University:

Memorial University of Newfoundland

Program:

Accelerate

Automated CT Data Analysis for Nuclear Reactor Maintenance

This project is aiming at the development of integrated computed tomography (CT) for automated integrity control of tools used in nuclear reactors during maintenance and inspection activities. Due to large number of complex tools, and the fact that the current process of tool integrity check is performed manually, the time required to finish the integrity check associated with each reactor maintenance and inspection task is extremely high. The current process is prone to human errors, where human inspectors might falsely assumes remaining parts are in the vault, with extended outage time that increases the costs of nuclear reactor repair and maintenance work in the order of millions of dollars. The proposed project is employing X-ray Computed Tomography (CT) technology to scan every tool before and after every vault work. Using advanced image processing, the pre-use scan before the vault work can be used to check every critical part of the tool. The automated pre-use scan process will verify if the tool is ready for vault use or not which will reduce time and cost.

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Faculty Supervisor:

Hossam Gaber;Jing Ren

Student:

Partner:

New Vision Systems

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Ontario Institute of Technology

Program:

Accelerate

Non-invasive automated assessment of tonic attention (vigilance) of commercial airline pilots during simulated flights – Part 2

With the goal of increasing the safety of civilian air flight, the detection of a decrease in pilot attention is becoming an important need in civilian aeronautics. Multiple models used for the detection of hypovigilant states have been developed over the years in experimental conditions, but barriers still exist limiting current use. First, some of these models require the execution of behavioral tasks that can disrupt pilot workflow. Second, other models relying on the use of physiological monitoring devices are still too cumbersome. The main objective of this project is to review all of the scientific publications about hypovigilance detection models so that future functional models can integrate the best evidence available. Although the main domain of application is aeronautics, other domains would also benefit from such technologies such as ground transportation and medical care.

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Faculty Supervisor:

Patrick Archambault

Student:

Partner:

Thales Canada Inc

Discipline:

Life Sciences

Sector:

Aerospace; Life Sciences (not health); Technology

University:

Université Laval

Program:

Accelerate

Real-time FPGA-based Architecture for Image andVideo Upscaling from Local Self-Examples

This project is about image upscaling which refers to the task of constructing a high
resolution image of a given lower resolution image, while preserving features of the original
image, such as sharpness and texture. One of the utmost difficulties that limit practical
application of state-of4he-art upscaling algorithms is their inherent computation demand, and
thus, conventional software implementations of upscaling algorithms are often unable to
deliver the required performance in many commercial applications such as mobile devices,
digital TVs, media players, and satellite imaging. In this project, we aim at a commercially
viable hardware (FPGA-based) implementation of an upscaling method that exploits local
self-similarities in the input image. We propose to desig a resources and power optimized
FPGA-based reconfigurable IP core that shall upscale HD1 D8Dp video streams in real-time
(30 frames/s). Our proposal outlines how we plan to achieve such a commerciallP core for a
robust image upscaling.

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Faculty Supervisor:

Aishy Amer

Student:

Partner:

TandemLaunch Inc

Discipline:

Engineering

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Development and Evaluation of Interventions for Farm Machinery Operators to Improve Musculoskeletal and Cognitive Health

Producers and farm workers are exposed to whole-body vibration (WBV) on a regular basis when operating farm machinery. The short-term effect of WBV include cognitive impairment and musculoskeletal disorders, such as low back pain. To aid in promoting worker cognitive and musculoskeletal health, rest and/or activity breaks may provide relief from these hazards and can be implemented immediately without cash investment. For these breaks to be appealing, they must be effective in reducing adverse health effects from WBV exposure, and must be feasible for field implementation. This multidisciplinary project will develop, test, and evaluate effective activity break interventions for agricultural equipment operators in order to mitigate adverse cognitive and musculoskeletal health effects during prolonged WBV. Worker participation and engagement will be incorporated throughout this project, to advise in developing best practices for field testing implementation. Outcomes of this work will include a set of guidelines and recommendations for field-test implementation.

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Faculty Supervisor:

Stephan Milosavljevic

Student:

Partner:

Agrivita Canada Inc.

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

University of Saskatchewan

Program:

Accelerate

Waterloo Affordable Housing Living Lab (WAHLL)

Waterloo Region is facing an acute housing crisis across the housing continuum. Waterloo Affordable Housing Living Lab (WAHLL) is an applied research collaborative aimed at understanding the local housing system to better enable investment in sustainable solutions. WAHLL is comprised of the Kitchener Waterloo Community Foundation (KWCF), Union: Sustainable Development Co-operative (Union Co-operative), and University of Waterloo’s ‘Waterloo Institution for Social Innovation and Resilience’ (WISIR). KWCF has convened a Housing Innovation Roundtable (HIR) which operates across sectors and will serve as the core stakeholder group for this collaborative. Union Co-operative seeks to leverage the growing social finance market to acquire properties in Waterloo Region, and the Co-operative is an HIR participant that will provide the perspective of a prototypical organization-level intervention. WISIR will undertake system mapping and modelling built on their Social Innovation Lab process and their work in community-based social finance.

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Faculty Supervisor:

Michele Mastroeni;Anthony Piscitelli;Sean Geobey;Sean Geobey;Anthony Piscitelli

Student:

Partner:

Union: Sustainable Development Co-operative;Kitchener Waterloo Community Foundation

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology; Real estate and rental and leasing

University:

Conestoga College Institute of Technology and Advanced Learning; Ontario College of Art & Design University; University of Waterloo

Program:

Accelerate

Energ-AI: Artificial Intelligence in Electrical Power Engineering

Classical engineering, referring to the three fields of civil, mechanical and electrical engineering, is currently based on traditional working methods. For example, the validation of plans is often done in paper version and the engineer must interpret photos and drawings manually, which introduces a risk of error due to the human factor. In addition, the shortage of labor in this area means that the economic potential of this industry in Canada cannot be exploited to its full value. In order to improve the efficiency, reliability, profitability and safety of the public and workers, the use of new digital technologies would allow engineering to migrate to the modern era.
To do this, the proposed project is to use artificial intelligence models to automatically interpret drawings and photos of electrical installations. This will allow the consulting engineering firm CIMA+ to stand out and offer these new services to its customers.

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Faculty Supervisor:

Martin Vallières;François Bouffard

Student:

Partner:

CIMA+ (Sherbrooke, QC)

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

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