This project aims to develop an AI-enhanced autonomous underwater vehicle (AUV) system designed to track Steel Catenary Risers (SCRs) in real time. Accurate tracking of SCRs is critical for maintaining the integrity of subsea infrastructure in the offshore oil and gas industry. The AUV will leverage advanced computer vision and machine learning techniques to continuously […]

Our project addresses a critical gap in maritime training, specifically the challenge of developing effective ice management skills in extreme environments. Traditional training methods rely heavily on human instructors, whose expertise is both scarce and costly, limiting the scalability and consistency of training programs. This issue is especially significant in industries like oil and gas, […]

AquaFishSense addresses the pressing issue of outdated and insufficient information available to fisheries, which impedes their ability to operate sustainably and efficiently. Fisheries face significant challenges due to the lack of real-time data on fish populations and aquatic habitats. This gap in information leads to overexploitation of marine resources, with approximately 34% of global fish […]

“THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW”

In partnership with NovaceneAI, computer science and journalism researchers from Toronto Metropolitan University will continue to develop an AI-powered product (Journalism Representation Index, or JeRI) that gives journalists and media consumers a tool with which to analyze the sources cited in journalism reports. The primary goal of the platform is to provide an evidenced-based structure […]

Le projet de recherche vise à améliorer la navigation des robots d’assistance en utilisant la cartographie sémantique de nuages de points 3D. Les robots mobiles autonomes sont essentiels pour les premiers intervenants, car ils offrent des informations précieuses sur une scène de catastrophe sans mettre de vies humaines en danger. Actuellement, ces robots nécessitent une […]

L’objectif de ce stage est de développer et d’optimiser des modèles avancés qui intègrent des données en temps réel sur les prix des engrais et des produits de récolte, afin d’ajuster dynamiquement les recommandations de fertilisation pour les agriculteurs. Ces modèles, basés sur des principes de microéconomie, s’appuieront sur des algorithmes d’intelligence artificielle pour analyser […]

Ocean industries, such as shipbuilding and offshore energy, face challenges in selecting materials that can endure corrosive environments, high pressures, and mechanical stresses. While materials like composites and aluminum offer promise, their adoption is slowed by their inherently complex and nonlinear mechanical behavior, which is sensitive to environmental conditions, as well as by the time-consuming, […]

The test-negative design (TND) is an observational study design that is currently and routinely being used globally to evaluate the effectiveness of vaccines against COVID-19 illness caused by emerging SARS-CoV-2 variants. Recently, more reliable statistical estimators were proposed to get better estimates of vaccine effectiveness. However, no one has yet investigated what statistical methods will […]

This project aims to improve the transparency and trustworthiness of AI systems in healthcare by using quantum-inspired agent-based modeling (ABM). By combining this with AI-based medical forecasting, the project will help create more reliable and ethical AI models that can handle complex medical data. The participating institutions will benefit by advancing their expertise in AI […]

Le projet de recherche explore l’intégration de l’intelligence artificielle (IA) dans le processus de revue de littérature systématique (RLS) afin d’optimiser l’efficacité, la rigueur et l’exhaustivité des analyses académiques. Traditionnellement, la RLS est une tâche chronophage nécessitant une collecte, un tri et une analyse manuelle de grandes quantités d’articles, souvent sujette à des biais humains […]

La prévision de la charge, ou de la demande électrique, est une activité fondamentale pour les utilités électriques et en particulier pour Hydro-Québec. Dans un contexte opérationnel, elle vise à prévoir sur un horizon de temps relativement court, typiquement 24 ou 48 heures la quantité d’électricité qui sera consommée par un ensemble de clients donnés. […]