The electric power grid in Canada provides energy to the country. In order to provide more reliable power, to include more clean energy and to supply energy to remote Canadian communities, part of the power grid may be required to operate autonomously. At the distribution level, microgrids, which can be isolated from the main grid, are being deployed for this purpose. Protection schemes in microgrids are very different to those in conventional grids. This project deals with the design and deployment of microgrid protection schemes.

Tannins, natural renewable molecules, have exhibited excellent corrosion inhibition properties, comparable to those of non-renewable counterparts. TGWT Clean Technologies Inc. has a portfolio of tannin-based corrosion inhibitors, which are being used in industry to protect mild steel (MS) steam boilers, high efficiency condensing aluminium boilers, as well as multi-metal heating and cooling closed-loop systems. Copper equipment is ubiquitous in industry, e.g. heat exchangers.

Machine Vision (MV) is a technology that aims to translate visual data from images or videos into useful information for industrial processes. The use of MV in precision agriculture is currently expanding and has helped to accelerate and improve sorting, grading and yield estimation. The goal of this research project is to develop a MV yield monitor for the large scale industrial farm Delfland Inc. that will identify, sort and count vegetables according to their size.

When plants are stressed they produce "reactive oxygen species" (ROS). Plants manage ROS with specific enzymes, many of which require micronutrients for activity. In the case of herbicide tolerant crops, the application of herbicide kills weeds in the crop but also stresses the crop for a time. The proposed work will test the hypothesis that crop plants will be better able to deal with stress resulting from herbicide application, when they are given additional micronutrients, in the form of Axter products spray-applied to crop leaves. The crops used in this work will be soybean and corn.

This project aims at investigating productive uncertainty as a determinant factor in stimulating the exploration of innovation. Data will be collected through stakeholder interviews and observations of technological intelligence practices at Université de Bordeaux’s Via Inno lab. Via Inno engages with industrial partners to explore future development opportunities, which present an ideal case study to explore conditions of uncertainty.

Many problems which are best solved by neural networks are exhibiting rapid growth in nascent and existing fields, such as natural language processing, and image recognition for self-driving cars. Current limitations in manufacturing technologies impose limits that prevent these performance demands from being met through conventional methods. Neuromorphic computing has been proposed as a potential solution for problems best solved with artificial neural networks.