The agricultural industry is adopting new technologies in many practices, including automation of routine practices such as milking in dairy or harvesting fruits. These innovations require the development of sophisticated machines and image processing algorithms associated with. This proposed project aims to develop the technology that allows design of a machine and associated algorithms to assess livestock for morphological traits. This innovation allows the farmers to evaluate their animals morphological traits more frequently and on their own.
A new atomizer for vaping devices will be studied experimentally and numerically. The visualization of the flow inside the atomizer microchannels and the liquid film formed over to the top surface of the atomizer (with and without surface heating) will be attempted. Aerosol characterization using Phase Doppler Anemometer (PDA) will be conducted. In addition, numerical studies using VOF (Volume of Fluid) will be performed and validated against the obtained experimental data.
Industrial workplaces can expose physical and chemical hazards to workers, which can lead to health complications in the short term and/or long term. The primary objective of this project is to develop a flexible industrial internet of things (IIoT) kit that is connected to the worker over work-shift to monitor various environmental factors in the workplace that could be potentially hazardous (such as noise, temperature, humidity, vibration, UV, H2S, VCM, VOC, benzene, acetone, ammonia, and etc.).
Remotely Piloted Aircraft (RPA) or drones have numerous applications in different industries. Data-based agriculture is an emerging field that can widely benefit from the drone technology through accurate data collection via drones. However, drones have limitations like short flight time, limited flight range, and they are prone to failure. To mitigate these limitations, we propose using a cooperative group of drones. The resulting parallel operation increases the efficiency and reduces required flight time.
The City of Victoria is working to implement infrastructure to support the adoptions of EVs. A key challenge are ‘garage orphans’, residents that live with multi-unit residential buildings (MURBs) without dedicated parking stalls per residence. Strata-governed residences also face various challenges in provisioning EV charging infrastructure. In order to support residents’ EV adoption, this project will help the City to develop planning methods and specific locations to incrementally install DC-fast chargers (DCFC).
Atmospheric corrosion, commonly known as weathering is among the leading causes of infrastructure degradation. The extent of atmospheric corrosion becomes more concerning when it triggers localized and non-linear metal loss rates. One such scenario is the localized corrosion at the flanged connections in piping, pipeline, and equipment for hydrocarbon industry and even utility sectors. As reported by transportation board Canada, flanges degradation is among the leading causes of leaks/ spills from pipeline.
Rappelon is robotic platform that works at heights on vertical surfaces. The robot can pass obstacles and working on facades with complicated geometries. With this robot, some dangerous and laborious tasks can be automated. They include highrise window cleaning, water tank painting and wind turbine blades maintenance. This project focuses on developing algorithms to keep the robot stable and make it move in different directions.To this end, analytic models as well as computer software will be developed to predict the position of each component, forces and loads on the building.
As the heat fluxes produced by modern high-performance microprocessors continue to rise, so too must the effectiveness of the removal of these fluxes. Accordingly, a large amount of research has focused on developing techniques to enhance cooling in computer systems. A novel method of doing so involves replacing the single-phase liquid or two phase-liquid vapor coolants typically employed in such systems with binary fluid mixtures.
Bio-materials can reduce our dependence on fossil fuels, greenhouse gas emissions and facilitate a rapid transition to a bio-basedleconomy. Thus, developing novel and innovative technologies and products related to bio-materials sectors is crucial. This has!resulted in extensive research into the development of biomaterials. Most research efforts have focused on materials selection,\'fabrication, and optimization of bio-materials\' performance through experimentation, trial-and-error, and microstructural analysis.
Reinforcement learning has caught significant attention in the past decade with landmark successes including deep Q-net applied to video games and AlphaGo for the game of go. However, the gap is still wide when it comes to application to real world problems mainly due to high training cost. We propose to develop a digital model of a physical system for the purpose of training an autonomous agent. This way, reinforcement algorithms can be trained on the digital model at a fraction of cost. This project will focus on a specific system: MyCobot 280 Pi from elephantRobotics.