This research project investigates the design of an all-digital transmitter that is suitable for low earth orbit satellite (LEO) networks. Important requirements for the satellite application include a transmit system that has a software reconfigurable hardware platform that is power efficient and can generate modulated output signals at the carrier frequency. The architecture also needs […]

The conventional approach of applying agro-chemicals uniformly to control pests in the potato field may not be the most efficient solution. The non-uniform distribution of pests and weeds necessitated site-specific management utilizing variable-rate and real-time spraying. To this end, a project is currently underway to implement of camera and detection pest algorithm as sensing system […]

The proposed research aims to use Machine Learning Methods to interpret data obtained during the Electrical Resistivity scans in the delineation of Fracking Sand deposits in Western Canada. Traditional exploration for sand deposits involves pricey and not always efficient auger and sonic drilling on the entire investigated Property. Currently, costs associated with those operations are […]

The primary objective of this project is to develop a comprehensive additive/subtractive manufacturing system encompassing hardware, sensors, and software for the automated production and repair of non-critical custom industrial equipment. This innovative system integrates AI and 3D computer vision to provide robust control, continuous monitoring, and effective failure identification. Featuring a groundbreaking PC/PLC-based communication architecture, […]

Our research addresses the challenges in solving large-scale parallel machine scheduling, an important combinatorial optimization problem in computer science and operations research. With applications ranging from manufacturing to healthcare and supercomputing, our goal is to provide a real-time solution for instances exceeding 1,000 jobs. In this research, we explore the application of parallel machine scheduling […]

The design and manufacturing of dies and molds represent a significant link in the entire production chain. It is on the critical path of development of many products, such as automobile and consumer electronics. The tooling development industries always meet three challenges: the demand for research and development speed, the high requirement for labor skill, […]

Cancer management continues to be a global problem (WHO report 2022) – mainly because cancerous solid tumors (found in more than 40% patients, and in all types of cancer) become metastatic, therapy resistant and poor-responding to conventional chemo-/radiotherapy due to a condition called hypoxia (tissue with low levels of oxygen). Due to poor tumor vasculature, […]

Psychological stress could be an important indicator of comfort with a task, particularly for training in safety-critical fields such as public safety. Continuous stress monitoring emerges as a valuable tool for improving and individualizing training, offering instructors a more comprehensive understanding of each student’s overall task comfort and enabling timely interventions based on stress levels […]

This project aims to enhance smart farming by improving the scalability and accuracy of two commercial products, SWAT CAM and SWAT MAPS, owned by Croptimistic Technologies Inc. These products are used for precision mapping on over three million acres of land across four countries. The project will utilize machine learning to identify crop parameters such […]

The construction industry heavily relies on mobile cranes for the off-site modular construction, emphasizing safety in operations. Despite standardized hand signals, inadequate and interrupted communications between mobile crane signalmen on the ground and crane operators pose significant risks of accidents, especially during blind lifts or lifts in severe weather. This research project aims to develop […]

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The main objective of this project is a comprehensive methodology that combines automated core characterization and AI methods to accurately forecast the geoenvironmental parameters of a deposit. By developing predictive models, this approach will enable the creation of a 3D geoenvironmental block model for the targeted deposit. This model will facilitate the prediction and optimization […]