Projets novateurs réalisés

Stereo (Multi-view) DepthIQ and its Application in SLAM

Our partner organization has developed a new type of camera, one where depth information is part of a single lens/sensor construction, meaning that there are no occlusions or shadows which plague stereo cameras, there is no requirement to light the scene as well time-of-flight cameras, and the expense is low compared to light-field cameras. Currently these cameras are limited to a near-range depth field of around 2m, this project aims to improve through several methods. We shall work with our partner organization to develop a stereo setup (including a calibration process) that will greatly extend that range, and then incorporate a deep learning method that will be able to use the actual stereo method to infer the stereo back from a single camera. To validate this process we shall develop a Simultaneous Location and Mapping (SLAM) method using both cameras and determine the errors produced.

Design and development of machine learning and signal processing algorithms for a wearable device (Watch HOP) for critical care, surgery, and chronic disease monitoring

Diabetes is a chronic illness characterized by elevated levels of blood glucose, accompanied by disturbed metabolism of fats and proteins. In the present project, a non-invasive wrist-worn device (Watch HOP) will be designed and fabricated to obtain physiological data (digital biomarkers) from participants to enable the creation of an algorithm that will ultimately allow to monitor and predict HbA1c levels and assess the efficacy of the given treatment.
In many applications of the smartwatch, it is desirable to record data for long periods of time. As a result, the recoded data will have a large dimension. Therefore, compression of the signal is an important part of design process. Compression algorithms, represent the original signal with fewer information bits. It is important to preserve all the information in the original signal in the compression method. The candidate will work with the hardware and firmware team to design and implement a lossless compression algorithm to compress the recorded signals.

Développement et implantation de la technologie des fondations stabilisées comme solution de réhabilitation de chaussée environnementale et économique

Le retraitement en place de type 2 est une technique de réhabilitation des chaussées qui s’inscrit dans les principes du développement durable et de l’économie circulaire. Ce projet vise à développer des outils permettant de mieux encadrer cette technique de réhabilitation dans un contexte climatique propre au Canada. Les organismes partenaires pour ce projet représentent les différents types d’intervenants impliqués dans des projets typiques de réhabilitation de chaussée, soit un donneur d’ouvrage, un laboratoire génie-conseil, et un représentant des entrepreneurs.

Thermodynamic investigation into the recovery of rare earth elements

The proposed research aims to contribute to the development of a recycling process for waste magnets. The proposed method is based on slag treatment which is a high temperature process for separation of one element from another based on their difference in oxygen affinity. For example, the affinity of neodymium for oxygen is significantly higher than the affinity of Iron for oxygen. This will facilitate the separation of iron from neodymium in their oxide form.
Cyclic Materials is developing a recycling process for magnets. Considering the complexity of the chemistry of this mixture, it is necessary to perform a fundamental thermodynamic evaluation prior to high temperature experiments. This proposed project will examine the efficiency of slag treatment of magnets via thermodynamic modelling.

Facilitating the recycling process of catalytic converters using computer vision

Catalytic converters used in car exhausts are effective means of reducing pollutant emissions from internal combustion engines under normal operating conditions. They contain precious metals which makes them attractive for recycling due to their metal value and also the sustainability of the demand for these metals. The price of Catalytic converters can be determined based on their models and the amount of metal that exist in them. Currently, the price estimation requires human experts to identify the model of catalytic converters and then query a database to find the amount of precious metals in the catalytic converter and then estimate the recycling price of the catalytic converters based on the daily value of the PGM metals. The objective of this project is to build an application that can automate the price estimation of catalytic converters for recycling. We will train a machine learning classifier model using computer vision and integrate it in a cross-platform mobile application.

Specifications of a fuel cell hybrid powertrain for an agricultural machinery

Global warming and the atmospheric concentration raise of carbon dioxide (CO2) characterize the main
environmental problems nowadays. Forestry and agriculture sectors are among the chief contributors to the global
greenhouse gas (GHG) emissions. According to FAO reports, agricultural machinery is responsible for over 75%
of nitrogen oxides (NOx),42% of methane, and 20% of CO2. Canada generated 729 megatons of GHG emissions
in 2018 where almost 10% of that came from the agricultural sector. In the light of the discussed matters, it can
be stated that there has been an interesting momentum towards the electrification of agricultural machineries
while there is a lack of prototypes and specific driving cycle for further evaluations. this project aims at developing
a design specification for developing an electrified powertrain, composed of hydrogen fuel cell and battery, for an
agricultural machinery.

Investigating biological impacts of Ocean Alkalinity Enhancement using controlled mesocosm experiments

Ocean alkalinity enhancement (OAE) is rapidly emerging as a potential technique to mitigate against the worst impacts of climate change. However, little is known regarding the potential biological and ecological impacts of introducing alkaline base into the coastal ocean to capture CO2, reversing ocean acidification in the process. Specifically, it remains unclear whether the phytoplankton community are impacted by chemical changes induced by OAE. Recently, the National Research Council (NRC) in collaboration with Dalhousie University (Dr. MacIntyre) was funded externally to conduct a series of controlled experiments whereby natural phytoplankton communities are subjected to differing biological, chemical and physical conditions. This Dalhousie/NRC research team proposes to partner with Planetary Technologies to conduct a series of experiments at the NRC facility in Ketch Harbour whereby natural phytoplankton assemblages are subjected to increased alkalinity and closely monitored in state-of-the-art mesocosm tanks (~1000L). The Mitacs interns funded here will 1) assist in experimental design; 2) monitor changes in the seawater carbonate chemistry after alkalization; and 3) lead chemical data analysis and assist with interpretations alongside the larger project team.

Sliike Project – Mobile Apps/Website Design & Marketing Intern

Sliike Corporation is a startup B2B/B2C online marketplace and e-commerce company based in Quebec, Canada. We own a technology platform (App and website) that promote effortless transaction of beauty services, sales of beauty product and advertisement of global brands in cosmetics, fashion, lifestyle, home care and personal care.

Our platform also serves as a place of community and engagement for people of visible minority, particularly Afro-Caribbean.
Sliike connects beauticians to clients and CPG companies to consumers. We optimize the beauty services experience and grow the beauty trade of salon owners and independent beauticians.

Sliike is also established to promote all beauticians especially the beauticians of visible minority, their culture, values, products, lifestyle, and fashion.

Développement de nouveaux algorithmes de recherche et comparaison

3DPartFinder est un moteur de recherche commerciale révolutionnaire qui permet de trouver une pièce mécanique 3D parmi une banque de pièces existantes (déjà conçues et/ou fabriquées), un peu comme Google le fait pour chercher des mots. La grande différence est que l’on demande à 3DPartfinder de trouver une pièce similaire à celle dessinée avec un logiciel de CAO comme SolidWorks (ou avec un des cinq autres logiciels de dessin CAO supportés). Le résultat de la recherche est un ensemble des pièces classées par ordre de ressemblance. La recherche peut ensuite être affinée avec les pièces trouvées. 3DPartFinder est utilisé par des entreprises qui conçoivent des pièces d’aéronautique, d’automobile, d’appareils médicaux, d’horlogerie, etc. Le projet va permettre au logiciel de chercher plus facilement, plus précisément et dans une plus grande banque de pièces que présentement, et ce afin de demeurer les leaders dans ce domaine.

Thermo-responsive polymeric system for anti-inflammatory hydrophobic drug elution

Diseases, such as inflammatory bowel disease, rheumatoid arthritis, and osteoarthritis have been widely impacted by the pathogenesis of inflammation. After traditional therapy, most of the time dying cells stimulate inflammatory effects which results the reduction of therapeutic effect and enhances the drug resistance. That is why treatment often requires frequent or continuous high-dosage administration of anti-inflammatory drugs. Efficient delivery of anti-inflammatory drugs to the targeted sites can reduce medical dosage and improve therapeutic effect. In recent years, nanogels have emerged as promising vehicle for delivering and releasing medications to patients as one of the main dimensions of nanomedicine. Nanogel is a polymer-based gel network of a 20-200 nm scale range that allows a high-dosage loading of biological compound through different chemical/physical interactions. In this project a novel thermo responsive polymeric nanogel system has been designed using FDA approved zwitterionic and PEG derivative compounds to encapsulate anti-inflammatory drugs with controlled elution. The loaded medications can be released from the nanogels through changing the polymer network to swell or compress upon activation by microenvironment changes (temperature/pH of the inflammation sites).

Electrical performance of next generation single-photon detectors

Light detectors are a mature technology that we encounter on a day-to-day basis without even realizing it, such as in cameras for high resolution imaging and in satellites and dishes for communication. The ability to detect light at the fundamental limit (i.e., single photons) is critical for numerous applications in modern medicine, imaging and quantum information science. Examples include dose monitoring for cancer treatment through singlet oxygen detection, 3D imaging with high resolution over long distances, and in quantum communication for enhanced security to safeguard our sensitive data in banking transactions. Superconducting nanowire single-photon detectors (SNSPDs) are pushing the limits of single-photon detector performance, but their cost and need for cryogenic cooling systems are significant drawbacks for many applications. Comparatively, single-photon avalanche diode (SPAD) technologies can be made portable without cryogenics but falls significantly short of the SNSPD performance.

The aim of this project is to overcome these drawbacks through the development of novel semiconductor nanowire p-n junction array avalanche photodiode (SN-APD) designs for high-efficiency single-photon detection.

Enterprise Data Engine Development

Enterprise Data Engine Development