Integrity and Analytics of Energy Market Data

ReWatt Power facilitates transactions of green energy derivatives/green attributes such as Alberta Carbon Offsets. The company uses a blockchain technology to manage all transactions on their platform. This way, all parties have access to the transaction history in a database they own, and the transactions are immutable. The first objective of this project is to ensure that source energy measurements are accurate before the resulting green attributes are permanently recorded.

HI-DSR: Hyperspectral Images enhancement via Deep Sparse Representation model

The current non-destructive and fast method of hyperspectral imaging technology are used for different application from remote sensing to medical imaging and food processing. Due to the nature of acquired data which are massive as well as physical consideration depend on the type of application, the careful, fast and accurate data analysis is mandatory to accelerate the usage of HSI technology. To cope with the type of HSI data in which the sparsity assumption is applicable, this project aims to address the HSI data representation though the sparse problem under deep learning approach.

Pickup and Delivery with Smart Service Times

The research problem to be addressed is the pickup and delivery problem (last mile) with precedence constraints for the pickup/delivery operations, and time windows. The objective is: (i) the design of a new algorithm that will use the algorithm of Curtois et al.

Machine Learning for Modeling Soil-Tool Interactions

When construction equipment digs, this generates a complex set of physical interactions between the machine and the soil. Being able to accurately simulate such interactions in real-time opens the door to improved operator training and even adaptively-tuned digging operation that optimize the energy-efficiency of construction equipment. With recent advanced in artificial intelligence (AI), this is now within reach.

Scaling up CO2 electrocatalysis

CERT has developed a technology to convert carbon dioxide into chemicals using water and renewable electricity in a system called a CO2 electrolyzer. They are scaling up this technology as part of the Carbon XPRIZE competition, a global race to find new technologies to make valuable products from CO2.

Automatic matching of service offers to calls for tenders

The process for responding to tenders is very long, arduous and involves many repetitive tasks. Among these, it is necessary to read the invitation to tender in order to find the different requirements, important dates, legal obligations, constraints of presentation of the response, etc. All of these factors are used for the prequalification of a tender and for the drafting of the tender. These requirements are generally expressed in the form of free text.

Novelty Detection in Lunar Analogue Terrains

Lunar and planetary rovers are faced with a high volume of data from their sensors and cameras, and yet decisions must be made rapidly to prioritize to which crater it should drive up to and of which rock it should take a closer look. In Canada’s intended upcoming exploration of the Lunar surface aboard short-timescale commercial missions, these considerations are of utmost importance.

Enhancement of Virtual Synchronous Machine Algorithms with Energy Storage

Modern electric power systems are rapidly adopting renewable energy resources. This positive movement, however, does bring with it major challenges to the way we operate power systems. In particular we may face drastic frequency changes and far-reaching transient phenomena. One way to remedy these is to deploy energy storage systems, such a s batteries, to assist the power system in maintaining its frequency and in releasing and absorbing bursts of power that are required to do so.

Computer Vision Algorithms for USV mounted Real-Time Marine Vessel Detection Systems

This is a feasibility study for designing an automatic marine vessel detection system that can be used by an Unmanned Surface Vehicle. Following a thorough exploration of the challenges related to the video date acquired on the boat by our partner, we will come up with recommendations for the best camera hardware setup and preprocessing techniques that improve video quality. Next, state-of-art machine learning techniques for target detection will be applied to spot the marine vessels.

Machine-learning-based posture identification from dynamic seat sensors

Sitting for long periods of time has negative health effects that could be solved by changing posture throughout the day. The solution lies in the use of sit-stand desks, active seats, and automated reminders to change position. For this purpose, this project focuses on developing software that can intelligently determine a person’s posture using sensors located in a dynamic seat. Data will be collected from people using the Formid Dynamic Seat, which will then be used to develop and test machine learning algorithms.