Who could have foreseen that humanitarian activities during the 2010 earthquake in Haiti would, 10 years later, guide the way for researchers, entrepreneurs and Mitacs interns during the COVID-19 crisis?
During his deployment at a Red Cross field hospital after the earthquake, Dr. Abdo Shabah saw the potential for greater use of technology in emergency health interventions.
When Gurudeeban Selvaraj and Satyavani Kaliamurthi came to Canada in 2019, they had no idea they would be creating both a preventative vaccine and a curing drug to address the millennium’s biggest pandemic.
The forthcoming 5G networks will be much more complex than their predecessors. They are on the verge of a generational transformation driven by the coverage, connectivity, availability, speed and latency demands of 5G. 5G networks will use network slicing to open up the network “as a service” to various third parties and their diversified applications, e.g., from autonomous vehicle control to massive machine-type communication for IoT devices.
The research proposed in this document will build upon and extend the previously funded CRIAQ (AUT-1701) and MITACS (IT12130) projects on the development of a UAV platform for search and rescue activities in the ski facilities of Domain Saint Bernard in Mont Tremblant in collaboration with SII Canada. The goal of this research is to develop a synthesis methodology for a multivariable PID flight controller to steer a rescuing UAV to a person in danger using output feedback.
Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis.
As the 5G Network will be capable of being reconfigured and optimized on-the-fly, they will also be more automated, requiring less manual effort to provision resources and make the most efficient use of bandwidth. The Ciena Analytics as a Service is a suite of tools to assist network operator in pro-active discovery on their network operations. This project will look at integrating new advanced intrepretable Artificial Intelligence and Machine Learning techniques to tackle different challenging networking tasks (e.g. traffic prediction, anomaly detection, topology discovery, etc.).
Heart failure is a prevalent disease affecting 250,000 people in North America alone. This disease can be treated by the transplant of a donor organ, but insufficient donor organs have led to the development of mechanical circulatory support which now provide a reliable alternate treatment option for patients. Unfortunately, many patients that could be helped by a mechanical circulatory support are deemed ineligible due to the invasive, open- heart surgery that is required to install such devices. Puzzle Medical Inc.
The main goal of this project is to develop data-driven approaches to reduce energy consumption and cost when operating commercial building’s cooling systems. Indeed, according to recent studies the building sector is one of the largest energy-consuming entities (almost 40% of global energy consumption) and this consumption is predicted to increase by 50% by 2050. Thus, there is an urgent need to provide solutions to reduce energy consumption taking into account the importance to improve environmental sustainability and the increase of electricity prices.
A diversity of native bee species inhabit agricultural and urban landscapes and can be more effective pollinators than the widely employed European honey bee. However, honey and wild bee communities often overlap, which means these bees compete for the same floral resources. Studies of competition between wild and managed pollinators are limited due to methodological constraints. This restricts our ability to predict how pollination and bee diversity will be affected by changes in pollinator community composition.