Design of a real-time on-site biosensor system to monitor harmful pathogens and protect canola production

Canada is one of the largest canola producing countries. The industry contributes about $20 billion revenue to the Canadian economy. Currently, canola farmers rely on the weather forecast (temperature, moisture, etc.) to decide whether to apply a fungicide. As the Internet-of-Things and sensor technologies get more advanced, farmers are deserved to have better technologies for intelligent farming. In this project, we propose the design of Internet-of-Things devices to monitor Sclerotinia sclerotiorum, a deadly airborne spore for canola.

Developing a virtual reality simulator and an algorithm to assess visual-vestibular interaction (VVI)

The effect of different factors in the field of view on the vestibular (balance) system including color, intensity, object motion, self-motion sensation, etc. are investigated in this study. Electrovestibulography (EVestG) is used to quantitatively measure vestibular responses from the ear canal, noninvasively. Currently, there is an ever- increasing interest among the health-related authorities to use visual stimulation to improve symptoms of vestibular and cognitive disorders.

Real-time Modeling of Virtual Synchronous Generator Type VSC Converters for Power Supply to Offshore Platforms

The voltage source converter VSC mimicking the behavior of a synchronous machine provides many advantages for grid operation. This “virtual synchronous generator (VSG)” will be implemented as a real-time simulator model on the RTDS simulator and used to investigate several operating scenarios.
The VS G behaves like a synchronous machine, which is one of the most widely used components of the legacy power system, and so it is well understood. The VSG can provide inertia and damping to the network.

Development of see-through near-eye display using embedded concave micromirror array for augmented reality applications

Near-eye displays (NEDs) are small displays that are positioned closed to the eye, which conveniently places visual information in the line of sight of a user. NEDs need to be compact and lightweight as they are typically worn on the head, taking the form of glasses or goggles. In this research, we design and build a thin and transparent NED. The proposed NED uses a high fill-factor embedded concave micromirror array (ECMMA), and light field principles for virtual image formation.

Private SQL interface for encrypted data

Querying databases without a layer of privacy protection might lead to serious privacy issues. Such issues include access patterns and communication volume patterns. By combining the state-of-the-art privacy standard (differential privacy) and encryption in provides resilience to a host of attacks on remote databases, including data reconstruction attacks. However, there is still research work needed in building a private access system on top of an encrypted database.

Temperature Prediction using Machine Learning

Synauta is a startup bringing the world's best Internet of Things solutions to water utilities. Our deep industry knowledge prepares utilities for true connectivity to realize energy savings. We provide cyber security, sensors and software. In this project we will create a temperature prediction algorithm to save energy for water treatment plants. More energy can be saved if operators can plan to make more treated water when temperatures are high and less treated water when temperatures are lower. Over a week, the amount of water produced would be the same, but less energy would be used.

Ultrafast laser nano-structuring in transparent glass: enabling 3D fibre-photonics packaging and assembly for high temperature sensing

This Mitacs project addresses a significant barrier the partner company (Fibos Inc.) is facing with their current customers in manufacturing of fibre optical sensors that can be robust and cost effective for the high temperature and pressure environments. The market is aimed at sensing of rotor assemblies in turbines where electrical and other means of measurement are not directly possible.

Feasibility of combining monolithically integrated silicon photonics with low cost, high performance, non-hermetic surface-mount technology (SMT) packaging

This project aims at experimentally validating the commercial viability of a new silicon photonics design which provides state of the art monolithic integration of various CMOS control electronics and BiCMOS high speed RF drive electronics which may be combined with high bandwidth non-hermetic SMT packages capable of withstanding standard high volume solder reflow processes.

Intelligent Chatbot Development for the Tourism Industry

This research helps to automate ontology development in order to support semi-supervised and active learning chatbot as much as possible, so that the overhead of chatbot training that requires human supervision is minimized, while relevant knowledge management activities become more efficient. The research objectives are both to refine the quality of the chatbot interactions and to automate its development and training as much as possible, to implement and test its practical and cost saving capabilities in tourism industry.

D2K+: Deep Learning of System Crash and Failure Reports for DevOps

The objective of this project is to develop techniques and tools that leverage artificial intelligence to automate the process of handling system crashes at Ericsson, one of the largest telecom and software companies in the world, and where the handling of crash reports (CRs) and continuous monitoring of key infrastructures tend to be particularly complex due to the large client base the company serves. In this project, we will explore the use of deep learning algorithms to classify CRs based on a variety of features including crash traces, CR descriptions, and a combination of both.