Projets novateurs réalisés

Development of Mobile and Fixed Models of Hybrid Energy Charging Station for Marine Applications and Waterfront Infrastructures

This project aims to develop two microgrid models based on hybrid energy resources for supplying clean energy to marine applications and waterfront infrastructure. The proposed Hybrid Energy Station (HES) has two models of HES microgrid. The first is a mobile HES (MHES) for supplying offshore power for charging boats and ships and auxiliary services integrated with fast charging technology and smart routing technique. The second is a fixed HES (FHES) for supplying the shore power for facilities for loading and unloading, commercial port facilities, supplying ancillary services, and charging ships and boats at the harbor. The two stations are integrated in the way the mobile station can work as a part of the fixed units or goes back and forth between the waterfront and the onshore area for doing charging and discharging missions. The two models combine many renewable energy sources to reduce greenhouse gas emission.

AI Algorithm Development and Refinement to Support the SR.ai Investment Research Platform

The field of responsible investing is rapidly expanding, with even greater attention on the importance of
responsible investment with each passing year, as seen most recently in the aftermath of the impactful 2021
COP26 summit, where responsible investment was key focal point. Directing our financial resources in a
sustainable direction has the potential to have a massive impact on helping us meet the Sustainable Development
Goals set forth by the UN. Though the importance of better alignment between finance and sustainability is clear,
a notion that now has very strong consensus built around it, investors still lack the right tools to support their
research process in terms of sustainability. They rely on high level data that is largely known not to be reliable,
which leads to massive misallocations of capital. The mission of SR.ai is to bring more rigour to the world of
responsible investment, using our technology backed by peer-reviewed research conducted within the University
of Toronto.

Newmont Nature-Based Decarbonization (scoping study)

Like many of the world’s largest mining companies, Newmont is voluntarily targeting net-zero carbon emissions by 2050. Recent research on technical feasibility of mining operation decarbonization has shown that mining companies may be able to achieve up to 70% carbon emissions reductions through internal initiatives, but may require options to capture and store carbon (either through purchasing offsets on the open market or capturing carbon) to drive net emissions all the way to zero. It is also predicted that the future cost of these offsets on the market will be multiples of what they are today. Nature-based solutions such as capturing carbon in forests, wetlands and soil will become an essential part of carbon capture portfolios for mining companies to stabilize and minimize the total cost of achieving decarbonization commitments. This study will model the different nature-based decarbonization opportunities available to Newmont mining operations in Canada.

Entraînement d’un agent conversationnel en assurance

Koïos Intelligence est à la source de l’agent conversationnel Olivo qui vise à offrir une expérience interactive, guidant l’utilisateur au travers des processus de prévente, de vente et d’après-vente pour tous les types d’assurances. Bien que l’outil soit dans un état avancé tant au niveau de la conversation écrite qu’orale, et ce aussi bien en français qu’en anglais, son amélioration se heurte aux exigences computationnelles lourdes pour l’entraînement des modèles d’apprentissage automatique sous-jacent. De plus, les outils de discussions inte-ractifs sont souvent imprécis dans leur développement et mise en œuvre dans le cadre d’un champ d’application particulier. C’est en particulier le cas en finance, pour les outils de conseils en matière bancaire et assurance. Il est nécessaire pour les rendre plus pertinents d’améliorer leur entraînement en utilisant des bases lexicales spécialisées, dont dispose en interne Koïos Intelligence.

Development of seedless triploid hemp varieties.

Hemp (Cannabis sativa L.) is an important natural source of cannabinoids for consumer products. Mainly grown outdoors, unintended cross-pollination can result in a significant loss of cannabinoid yield via seeding. To overcome this risk, the team intends to develop seedless, triploid varieties of hemp with high minor cannabinoid content, notably cannabigerol (CBG) O cannabichromene (CBC). The team will double the number of chromosomes in starting lines to make tetraploid (4n) hemp or hemp with 4 copies of each chromosome, Tetraploid flowers (4n) will be fertilized with pollen from normal diploid (2n) hemp of the same cultivar to produce 3n or triploid hemp seed. As seen for seedless bananas and watermelon, triploid hemp plants should be infertile when pollinated due to an uneven number of chromosomes. This process known as genome polyploidization has been successful in closely related crops to Cannabis such as hops, with benefits to product quality.

Intelligent recycled plastic boat, recycling plastics in the ocean

The ocean is receiving much of the plastic waste generated on land and it is calculated that yearly up to 12.7 million tons of them enters in our oceans bringing a drastic environmental problem. This project seeks to create an autonomous boat made with recycled plastics, to clean up plastic waste in the oceans.
The boat will be assisted by a drone, which will map the area in search of suspended debris, and then send their location to the boat for collection, achieving an integration of air and ground in an autonomous system. Part of the recycled plastics will be used later to 3D print new units allowing to clean more area, reducing costs and recycling waste.

Could Community-Based Sign Language Programs Serve as a Bridge for Deaf Adults to Post-Secondary?

The Sign Language Institute Canada (SLIC) is a community-based organization that aims to increase training and certification opportunities for teachers of American Sign Language (ASL) and la langue des signes Québécoise (LSQ) across Canada. SLIC has plans to implement a community-based sign language program, intended to provide deaf adults with pathways to employment, as sign language instructors, or continuing education, including college and university level education. The objective of this study is to explore the possibility of a community-based sign language program serving as a bridge for deaf adults to post-secondary. Through qualitative research with deaf adults who have participated in community-based adult education programs in the province of Ontario, as well as interviews with deaf adult education staff and teachers, this study aims to consider what a bridging program might look like, according to voices/signs of deaf adult learners, and move us in that direction.

Réseaux de Neurones, L’IA appliquée à l’imagerie médicale

Nous allons développer un outils d’aide à la décision pour les radiologues. À l’aide d’imagerie rayon X de la cage thoracique vue de face, il fournira une évaluation sur la probabilité que le patient soit atteint de 14 maladies communes (atélectasie, Cardiomégalie, épanchement, infiltration, Masse, nodule, pneumonie, pneumothorax, consodilation, oedeme, emphyseme, fibrose, épaississement pleural ,hernie). Cette liste précise vient du fait que nous nous basons sur une recherche nommé CheXNet qui a déjà de bon résultats. Nous voulons aggrandir le nombre de maladies détectées afin de couvrir celle au goût du jours comme la Covid par exemple.Cet outil mettra en évidence les régions à hauts potentiels en plus d’une suggestion de diagnostique (Maladie la plus probable) afin d’aider les radiologues dans leur décision.

Les avantages potentiels sont immense. Cet outils améliorera la qualité ainsi que la rapidité des diagnostiques. De plus, s’il y avait une liste d’attente pour les diagnostiques en radiologie, cet outil pourrait envoyer au radiologue en priorité les radiographies dans lesquelles il a détecté des maladies graves. Ainsi, le temps d’attente pour les cas urgent serait encore plus réduit permettant de sauver du temps très précieux dans ces cas.

Impacts of Diverse Cover Crop Mixtures on Soil Health and Soil GHGs

With losses of soil carbon constraining our ability to ensure regional food security, there is increased focus on using regenerative agricultural management to improve soil health and the sustainability of our agri-food system. Numerous knowledge gaps exist around how we can reliably increase soil carbon, and how regenerative principles may be applied to field conditions relevant to farmers in East Central Ontario, where a short growing season, variable topography, and shallow soils challenge farmers’ ability to adopt regenerative practices such as cover cropping. In this collaboration, Common Earth and Trent University researchers will establish a duplicated, controlled field trial to study soil carbon and nitrogen dynamics and greenhouse gas release as impacted by cover crop management, to better understand how we may best put and keep carbon in soil using regenerative practices.

UWB localization for Autonomous landing / Instrumentation landing of VTOL vehicles.

This project will focus on developing a system to find the precise location of a landing pad as seen from a drone / helicopter. The proposed system uses radio frequency ranging between the devices onboard and devices deployed at the landing pad. Together with accelerometer and compass data, the system can figure out the position and orientation of the drone / helicopter relative to the landing pad. This system will help to automate drone operations as well as will enable air ambulance services and offshore supply helicopters to be operated in poor visibility weather conditions.

Integrated Mobile Waste-to-Energy Process Technology for Marine Infrastructures

The field of plastic waste management is essential for a sustainable society that utilizes plastic waste for energy production and environmental safety. Plastic waste’s land filing and incineration have large environmental impacts due to greenhouse gas emissions. The mentioned challenges could be eliminated using a more reliable and controllable thermal source such as an inductively coupled thermal plasma torch, direct current plasma torch and microwave plasma torch. In this project, advanced torches will be simulated, designed and constructed to generate a thermal plasma jet and integrated into a processing tank on a lab-scale to enhance the chemical reactivity and produce clean gasoline and diesel fuels suitable for usage in ignition engines from plastic waste from marine vehicles. This integration shall improve the quality of end-products, eliminate tar and wax content, provide better temperature control in chemical reactors, as well as enhance the chemical reactivity and thermal cracking reaction parameters.

Sensor Fusion for Ocean Surface Wind, Wave and Current parameter Estimation and AIS Target Detection and Anti-Spoofing

High-frequency surface wave radar (HFSWR) is recognized as one of the essential tools for remote sensing of the ocean surface because it provides wide-area, all-weather, and near-real-time surveillance. It operates between 3 to 30 MHz and can detect a large area of thousands of square kilometers. Wind speed, wind direction, surface current, and significant wave height can be extracted from HFSWR Doppler spectra.
Although such methods can perform satisfactorily for ocean surface wave parameter estimation, there are other sensors that can provide better spatial resolution than HFSWR on its own. These sensors include Xband radar, which provides very good spatial resolution for parameter estimation, though usually with a reduced maximum range. Satellite imagery can provide parameter estimation over a very large area, however the spatial resolution is limited by the quality of the imagery and the temporal resolution may also be limited. By combining the data from all of these sensors, and possibly others, it is believed that estimates with high spatial and data resolutions for ocean surface wind, wave and current parameters may be extracted from the data from these various sources.