Projets novateurs réalisés

Simulation and Design of Next Generation Single Photon Sensors

Photons are particles of light. While countless numbers are emitted from a light source to illuminate a room, sensitive electronics can detect light down to the level of a single photon. These electronic devices, known as single photon avalanche diodes (SPADs), use a process that triggers an avalanche of electrical charges, which can be measured as an electrical current. SPADs have applications in next generation camera systems, autonomous vehicles, and even quantum information processing. In this project, student interns will work in partnership with Ansys to investigate the challenges of combining many SPADs into a sensor array. This research may lead to improved behavioural models that can be incorporated into advanced simulation tools, accelerating the next generation of device designs.

An integrated monitoring, statistical analysis and First Nations community engagement approach for water quality assessment in Necoslie River Watershed

The community of Nak’azdli Whut’en has been highly impacted by the watershed deterioration, as they currently have no access to clean water. The physicochemical and biological water quality parameters will be monitored for one-year. In addition, through the collaboration with the Nak’azdli band council and School District 91, a local team of high school students will be trained to help with water sampling and some on-site analysis of water quality parameters and the installation and maintenance of water quality monitoring data loggers. Multivariate statistical techniques, including principal component analysis (PCA), will be used for data analysis to evaluate the contribution of various sources to the river water quality and the application of the water quality index method. The results obtained from this project will provide valuable information for understanding the Necoslie river environment and its causes of pollution so that improved and sustainable watershed planning can be developed in the future.

EmersonGrow “Sun Box”

The objective of this project is to create a prototype of a portable External Universal Digital control device using existing technology from EmersonGrow EGX7, the first fully digital LED Grow light. This smart device enables users to control any compatible grow light digitally, including colour, intensity, create stages and light recipe, users can also upload, download and share with other growers worldwide. With the increased popularity and demand, we foresee that we will have increase in revenue and international growth with foreign purchases. We hope to set up manufacturing facility in Canada to fulfill the need and demand, we will be creating job and contribute to economic prosperity. The project will add to the number of Highly Qualified Personnel (HQP) in Canada and will establish Canada as a leader in the technology.

Robot Localization using Single-Point LiDAR Array

The primary objective of this project is to develop a way for low-cost service robots to navigate indoors in a more accurate way. To keep costs down, such robots rely on relatively inexpensive encoders and gyroscopes to determine their positions and orientation. However, this leads to the problem of accumulated error while the robot attempts to follow paths from room to room, which gets progressively worse over time. To overcome this problem, the robot must somehow ‘know’ its true location at any moment. In this project, the team will attempt to do this without resorting to expensive sensors or high-powered computers. If successful, it will be possible for low-cost robots to navigate from room to room while deviating from its desired path by only a few centimeters.

Assessment of air quality using remote sensing technology for Alberta’s oil sands region

The objectives of this study are:

• To assess the feasibility of using satellite remote sensing technology to measure trace gases and aerosols over northern Alberta and to study the transport of biomass burning emissions and its impact on air quality over northern Alberta.

Methodology:

Data from several satellite sensors will be used in this study coupled with AErosol RObotic NETwork (AERONET) ground measurement data, In-service Aircraft for a Global Observing System data (IAGOS), meteorological data and Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) Model.

Satellite data sets:

This study will use data from numerous satellite instruments, which are: MODIS (Moderate Resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging Spectroradiometer), CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation), OMI (The Ozone Monitoring Instrument), MOPITT (Measurements of Pollution in the Troposphere), and TES (Tropospheric Emission Spectrometer). Data are in HDF standardized format and we will use IDL programming language for data analysis.

The degradation of battery negative electrode materials in protic ionic liquids

The battery is an electrochemical device that people use every day. The industry is always interested in improving different characteristics of batteries such as less cost, increasing power, safety, and eco-friendliness. Nickel metal hydride (NiMH) batteries are widely used rechargeable power sources. We work on the replacement of aggressive electrolyte used in this technology by a more ecofriendly ionic liquid (IL). The proposed project is focused on the study of the negative electrode materials degradation in a new electrolyte. It is important for the good long time performance of the battery. Using different techniques we will study the degradation of materials during the charge/discharge cycling of the electrode materials. Also, this project is planned to study calendar corrosion. It is necessary to study the degradation of materials at storage mode because for example more than 90% of a car’s lifetime is spent parked and unused. This project will help us to choose good candidates for a new electrolyte.

Automating various land resources development and planning services using MapAki platform offered by CES

Services provided by CES move the traditional paradigm away from static paper maps and data management. Instead, they offer MapAki to create and deliver unique interactive web maps. This research project will attempt to associate multi-layered artificial intelligence empowered services to redesign and rebrand MapAki. Firstly, this project will use up-to-date visuals collected from the drones to generate 3D models for informed land use planning and development of a community for resource optimization, maintenance work, and capacity building. Furthermore, this project will focus on community-centric data analysis supporting tools (e.g., multi-layer data searches, generating personalised reports, heatmaps, and proximity analysis) that can facilitate the already existing services to a great extent by attracting a wide range of clients and increasing sales. Finally, the project will support next-generation 911 emergency responders by automating the identification and prediction of fire, flood, and evacuation routes through drone-based real-time visuals.

Optimiser la quantité d’hydrosemis utilisée pour la réhabilitation écologique des talus de sites miniers nordiques en fonction de l’exposition et du matériau

Les empilements de rejets miniers solides et de sol excavé doivent être végétalisés à la fin de la vie de la mine. La technique d’hydrosemis, qui consiste à pulvériser un mélange de graines et de fertilisant dans de l’eau, est souvent utilisée pour végétaliser les zones en pente. L’entreprise de végétalisation Irrigation NORCO veut optimiser la quantité d’hydrosemis à appliquer (nombre de couches) sur ces zones en pente pour s’assurer d’un résultat satisfaisant selon l’exposition et la nature des matériaux constituant les pentes. Cet ajustement est important dans le contexte des mines de fer en région nordique où les conditions climatiques extrêmes s’ajoutent aux contraintes d’établissement de la végétation sur rejets miniers. Ce projet de deux ans permettra la formation d’un ou d’un(e) étudiant(e) à la maitrise. Ces travaux contribueront à préciser les indicateurs de suivi du succès de la végétalisation pour le contexte des mines de fer nordiques.

Effective Recruitment and Retention of Underrepresented Demographics in Nova Scotia’s Automotive Sector

Currently in Nova Scotia there is under-representation of diverse individuals employed in the automotive sector and a growing job vacancy rate. The Nova Scotia Automotive Sector Council seeks to understand the current employment and recruitment rates, barriers and opportunities for improvement in collaboration with our partner organizations from under-presented groups. In order to create inclusive recruitment and retention strategies, safe work-spaces, mentorship culture and cultural safety in the future, we need to understand what currently works, what doesn’t and how we can improve as an Industry.

Advanced Solar Photovoltaic (PV) Data Analysis and Performance Predictor using Edge Computing

This project focuses on giving the commercial or industrial property (i.e. non-solar professional) owners and facilities managers the ability to accurately calculate the predicted output of a small to medium-size solar plant and compare that value to what it is producing. This comparison is helpful to the facilities manager as it gives a way to monitor for, pick up on and rectify issues with their solar plant, thereby ensuring their return on their investment. These predictive comparative outputs will be created via external sensors placed within the Solar plant communicating with a mini-computer to process the data. Finally, the information will be sent to a cloud service for data storage and display.

Manipulating Diet Content and Context to Improve Edible Insect Farming Yield

Food security is a major global concern and Canada’s current agricultural model is not adequately positioned to support our growing needs. Insects may solve this problem as they are nutritious and their production requires less resources than vertebrate protein sources. A primary goal of this project is to increase cricket yield. Together with Entomo Farms, we have identified key concerns surrounding increasing yield that cannot be addressed without academic support. We will determine how to best manipulate diet content (Goal 1) and context (Goal 2) to improve rearing facilities and practices and will test diet formulations and rearing practices at Entomo Farms (Goal 3). We will identify the protein:carbohydrate and ipid:phosphorus:vitamin C, along with the ideal plant-based protein and the optimal particle size required to maximize yield. Insect growth is also heavily influenced by abiotic temperature. Because different physiological processes have different optimal temperatures, insect growth’s temperature sensitivity is also dependent on diet. We will determine how diet and thermal environments interact to impact yield. Further, we will also determine the effect of rearing density and diet on growth and survival.

Evaluation of ML-based Intrusion Detection algorithms

This research will determine which combinations of metrics sets and machine learning algorithms
provide the most accurate outcomes when analyzing the data produced in the CSE-IDC-IDS2018 dataset.