Innovative Projects Realized

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

31620 Completed Projects

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Projects by Category

Advanced Analytics and Fault Detection of Industrial Steam Traps via Machine Learning

Steam is flexible and very cost-effective in terms of gases that can be used to transfer heat. All steam systems require that the steam arrives at the right quantity, temperature, and pressure for it to work efficiently. The presence of foreign materials such as air, condensate, and other gases can lead to a reduction in this efficiency. To that end, steam traps are used to remove condensate, debris, and other gases from the steam system to maintain operating efficiency and prevent system damage. Due to constant operation, steam traps have a high failure rate of about 20%, according to the US State Department of Energy. Pulse Industrial’s steam trap sensor provides monitoring capabilities and early detection of these steam trap failures. This leads to vast improvements in the operating performance of partner facilities and reduced operating costs. This research project will optimize the analytics and diagnostics performance of currently deployed steam trap monitors. This optimization will be done by developing the AI model using collected data from partner plants. This will allow for a holistic improvement of the overall system, which is expected to increase the accuracy performance of the steam trap sensors

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Faculty Supervisor:

Xianke Lin

Student:

Partner:

Pulse Industrial

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Ontario Institute of Technology

Program:

Accelerate

Improving the Efficiency in Customer Interactions and Investment Selection

The purpose of this research is to develop a solution that uses Artificial Intelligence and Predictive Analytics to Improving the Efficiency in Customer Interactions and Investment Selection.

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Faculty Supervisor:

Christian Jacob

Student:

Partner:

Boast Capital

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Émulation d’une plateforme transactionnelle dans un marché local de l’énergie

Dans ce projet, nous proposons l’émulation d’une plateforme transactionnelle dans un marché local de l’énergie pour apprendre et tester les différents algorithmes et approches d’optimisation et de contrôle décentralisés sur les échanges entre les agents, comprendre les contraintes techniques et les bloqueurs, et définir les enjeux d’intégration des RED dans le réseau électrique. Dans un premier temps, l’approche multi-agents au niveau du client sera analysée et des stratégies et algorithmes pour la gestion transactionnelle seront proposés. Ensuite, ces algorithmes et stratégies seront étendus aux différents niveaux hiérarchiques du réseau depuis le client au poste de distribution. Dans cette hiérarchie, les contrôleurs des charges domestiques et des systèmes de chauffage constituent des agents de base et les gestionnaires

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Faculty Supervisor:

Kodjo Agbossou

Student:

Partner:

Hydro-Quebec;Mitacs - Vancouver

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

Innovative tools to improve knee health and predict an athlete’s risk of anterior cruciate ligament (ACL) injury

Anterior cruciate ligament (ACL) injuries are one of the most frequent injuries among athletes. Currently, the only way to predict an individual’s risk of incurring an ACL injury is through prohibitively expensive motion analysis laboratories. There is a critical need to develop novel tools that improve knee-health and are well-received by the athletic community.
This proposal will develop (1) a Kinect-ACL Injury Prediction System (K-AIPS-pro) for sports-medicine and orthopaedic clinics to: (i) score the risk of ACL and secondary injury; (ii) an athlete’s ability to return to play; and (iii) identify biomechanical features to promote knee-health using a personalized exercise plan, and (2) a Smartphone-Knee Improvement Performance System (SKIPS) for athletes. Through the integration of exercise videos and knee health tutorials, SKIPS represents a tool enabling athletes to take preventative measures to reduce their risk of ACL injury.

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Faculty Supervisor:

Paul Martineau

Student:

Partner:

Emovi Inc

Discipline:

Life Sciences

Sector:

Manufacturing

University:

Research Institute of the McGill University Health Centre

Program:

Accelerate

Hydrologic regulating services of non-woody grassed and meadow urban landscapes

Due to urbanization in the GTA, many green areas are replaced by impervious infrastructure, preventing runoff infiltration and increasing flood risks. The Meadoway project proposed by the Toronto and Region Conservation Authority (TRCA) aims to restore meadow habitats with native plants along a hydro-corridor over 16 km across Scarborough, which can potentially improve the runoff retention and reduction capacity of the land due to the larger and longer roots, greater root density, and different evapotranspiration patterns of native plants compared with pre-restored turf and non-native cultural meadows. The proposed research will investigate the hydrologic response of meadows to storm events compared with turf lands, hardscaping, and potentially non- native cultural meadows. Laboratory rainfall simulation will be conducted upon intact soil columns collected from the field to mimic hydrologic process including rainfall, runoff, infiltration, and subsurface discharge. The results of the study can help TRCA develop plans for long-term assessment and aid the planning and management of future restoration project.

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Faculty Supervisor:

Jennifer Drake

Student:

Partner:

Toronto and Region Conservation Authority (Vaughan, ON)

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Public administration

University:

University of Toronto

Program:

Accelerate

Development and Control of Smart End effector for Robot assisted Epidural Needle insertion

Epidural injection is a medical intervention to inject therapeutics directly at the vicinity of the spinal cord and the nerves branching from it. This procedure may be performed for regional anesthesia, e.g., for painless labour, or pain management, e.g., for persistent low back pain. For epidural injection, a long thin needle is inserted into the patient’s spinal cavities through the skin and underlying soft tissues. Accurate insertion of the needle is a precise task that unless performed correctly may result in irreversible damage to the nerves or spinal cord. In this project, a remote-controlled robotic system is proposed, developed, and tested for precise and safe robot-assisted epidural injection. With this technology, the physician uses a haptic interface to control the robot remotely. The robot follows the physician’s lead on needle insertion while monitoring the needle pressure and insertion depth for safety purposes. The robotic system also uses artificial intelligence to detect if the needle’s tip is inside the target area.

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Faculty Supervisor:

Jake E Barralet

Student:

Partner:

Kinova Robotics

Discipline:

Engineering

Sector:

Manufacturing

University:

Research Institute of the McGill University Health Centre

Program:

Accelerate

Managing Shared State for Video Games in a Networked Multi-core Environment

Video Games require a vast array of different computations to present the desired experience. These computations must be completed consistently to make the software responsive to the user. The industry trend towards many separate processors (multi-core) in the same physical device and the emergence of network based ‘cloud’ computing have created many opportunities, but also many challenges for the game industry. The goal of this project is to create efficient techniques to organize and schedule the computations to take advantage of all the processors available. These techniques must ensure that the results produced correctly and are obtained quickly enough to satisfy responsiveness. Each of these techniques will have a corresponding aspect that allows them to be used by programmers who are not experts in utilizing multiple processors. While this project focuses on games, the benefits will be applicable to many domains, especially in the emerging field of mobile consumer-oriented applications.

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Faculty Supervisor:

Alexandra Fedorova

Student:

Partner:

Gaslamp Games

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Coveo : Algorithmes de recommandation

Ce projet s’inscrit dans la grande famille des projets de systèmes de recommandation, où un algorithme doit recommander aux utilisateurs des produits ou des documents qui seraient intéressants pour eux, basé sur ce que nous connaissons de l’utilisateur et sur sa session de recherche actuelle. Coveo a déjà des modèles de recommandation en place, dans le domaine du service et le domaine du commerce en ligne. Le stage a pour objectif de collaborer avec l’équipe de d’apprentissage automatique pour améliorer la qualité des modèles en place et explorer de nouvelles idées qui permettraient de résoudre de nouvelles problématiques provenant de nos clients. Durant ce projet, le commerce électronique sera le principal sujet, sans y être strictement limité.

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Faculty Supervisor:

Christian Gagné;Audrey Durand

Student:

Partner:

Coveo Solutions Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Paradocs : Recommandations pour la clientèle des stations de ski en temps réel

Dans un monde de plus en plus connecté, les stations de ski en Amérique du Nord et à travers le monde désirent s’impliquer davantage auprès de leur clientèle pendant qu’elle est sur les pentes où dans leurs infrastructures. Favoriser l’expérience de ski et améliorer les revenus connexes sont deux motivations importantes dans le contexte actuel de tourisme limité.
En partenariat avec plusieurs stations de ski, Paradocs développe et maintient le système de gestion des passes permettant l’usage des remontées mécaniques. Ainsi, à chaque fois qu’un skieur utilise une installation, un identifiant unique anonyme est journalisé pour permettre le suivi de celui-ci. Certains utilisateurs plus réguliers et détenteurs d’un compte ont leurs achats en boutique ou restaurants également journalisés.
Basé sur ces données d’achalandage et d’achat antérieurs, le but du projet est alors d’effectuer des recommandations en temps réel aux skieurs concernant les produits ou services qui seraient intéressants selon leur profil, et le contexte actuel (heure, météo, achalandage dans la station). Ces recommandations pourront par exemple contenir des promotions en boutique ou des réductions au restaurant en vue d’améliorer leur expérience en station. Ces recommandations seraient à terme transmises au visiteur via une application mobile utilisée par les skieurs.

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Faculty Supervisor:

Christian Gagné;Audrey Durand

Student:

Partner:

Paradocs Solutions Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Université Laval

Program:

Accelerate

LeddarTech: Détection et suivi d’objets pour la conduite autonome à partir de données Lidar et caméra fusionnées

LeddarTech, acteur de premier plan des solutions de détection environnementale pour les véhicules autonomes et les systèmes avancés d’aide à la conduite, propose l’utilisation d’un capteur Lidar (i.e., Pixell) conjointement avec d’autres capteurs (caméras optique, Radar, IMU, etc.). Le but de ce stage serait donc de vérifier (1) l’intérêt de l’utilisation du capteur Lidar pour prendre des décisions sur la conduite du véhicule (ex., la détection et le suivi des véhicules et des piétons), et (2) la synergie entre le capteur Lidar et les différents autres capteurs dans le cadre des véhicules autonomes. Dans le cadre du présent stage, un algorithme permettant la détection et le suivi des véhicules et des piétons, à partir de données capturées par des caméras optiques et d’un Lidar (i.e., Pixell) sera développé. De plus, une étude comparative sera effectuée pour déterminer une méthode de fusion efficace entre les données optiques et les données brutes Lidars.

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Faculty Supervisor:

Christian Gagné;Philippe Giguère

Student:

Partner:

LeddarTech Inc

Discipline:

Computer science

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

Circles Software and Mobile Application

The project focuses on developing a software program for creating audiovisual interactive digital art works able to blend and manipulate sound, text and images for the purposes of artistic installation, performance visuals, networked art, and creative sharing. While there are numerous companies who have developed creative software platforms, there is currently nothing available which minimizes the prerequisite of heavy technical knowledge necessary. By developing a user-friendly tool, which easily enables creative expression, we will attain a highly competitive edge in the industry

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Faculty Supervisor:

David Bogen

Student:

Partner:

Hybridity Media

Discipline:

Sociology

Sector:

Arts, entertainment and recreation

University:

Emily Carr University of Art + Design - Main Campus

Program:

Accelerate

Biochar as a Soil Amendment for Revitalizing Stockpiled Soils and Carbon Sequestration at an Oilsands Lease, Christina Lake, Alberta

Working in partnership with MEG Energy Ltd, the Applied Research Group in Natural Resource Technology at Saskatchewan Polytechnic will examine biochar’s role in revitalizing stockpiled soils by conducting a three-year assessment of black spruce growth and survival on a disturbed borrow pit site. Biochar is highly regarded for its ability to increase soil productivity due to high carbon content, organic matter volume, porosity, recalcitrance, and adsorptive characteristics. These qualities permit improved soil health through various pathways including the ability to selectively make-up for nutrient and microbial deficiencies through biochar inoculation. The research will assess twenty different control and experimental treatments involving various combinations of nutrient and microbe inoculants and microhabitat adjustments. Progress in soil revitalization research is likely to have significant bearing on the environmental sustainability of oilsands development in the western boreal forest.

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Faculty Supervisor:

David Halstead

Student:

Partner:

MEG Energy

Discipline:

Earth science

Sector:

Mining

University:

Saskatchewan Polytechnic

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.