In this project the intern will work with an expert team from the company Xanadu, to explore new computational methods and approaches which could be helpful for optimizing hybrid calculations involving both classical and quantum computing combined together.
For people with mobility impairments, such as spinal cord injury survivors, rehabilitation and at home care settings come with the possibility of costly, painful pressure ulcers and skin breakdown. Occurring at a high frequency, current practice requires constant vigilance by caretakers and individuals using self-management practices. This injury comes from a prolonged application of pressures, temperatures and humid environments causing the skin to die from a lack of blood flow, usually from situations that an able-bodied person can avoid, but those with mobility impairments cannot.
The Canadian healthcare system is not yet prepared to access and leverage IoT (Internet of Things) data to support clinical decision making outside of hospital settings (Nguyen et al., 2017). With advances in low-cost IoT technology, it is now possible to meaningfully incorporate a variety of sensors into our homes and communities, leading to the implementation of Smart Homes (Risteska Stojkoska & Trivodaliev, 2017) and Smart Communities to support healthy living (Bencardino & Greco, 2014; De Filippi et al., 2019).
Nondestructive evaluation (NDE) is frequently performed for various manufacturing sectors, but its current practices require human operators to be involved in all aspects of the data collection, transfer and analysis. With the advent of Industry 4.0, NDE technology needs to be upgraded to “NDE 4.0” comprising essential aspects such as automatic and autonomous NDE, interconnectivity for data communication, and real-time data analytics using AI, which cannot be achieved with current technology.
The notion of ownership is fundamental and essential in a number of settings, including the setting that is the focus of this proposal: information over the Internet. Ownership of some content, in turn, endows the owner with certain rights over the content.
In this proposal, we intend to answer how infrastructure sensors can be used for autonomous driving. Using infrastructure sensors make automated driving safer, more simplified, and cost effective especially for multiple autonomous vehicles operating in known environments such as large residential/commercial complexes and resorts. Infrastructure sensors replace the main onboard vehicle perception sensors with infrastructure sensors mounted on the side of the road, for example on light posts.
This project will look at improving the quality of software by using AI to determine if a defect / issue exists and if so where it exists for easier fixes. This research is innovative and this domain is not proven. The student will explore new techniques for a highly relevant issue in industry. The industry partner will gain insight and knowledge into how improvements can be made ultimately resulting in faster time to market and potential cost savings.
Willowbank Centre for Cultural Landscape will work with a University of Waterloo student to engage in an emerging process of building disassembly and material reuse. Demolishing a building and sending the debris to landfill sites is a huge loss of resources, energy, and historical value. This project becomes a prototype on how to reuse building materials in other contexts.
In Ontario, 95% of its paved roads in the province are paved with asphalt or asphalt surface treated. Due to severe weather conditions, the lifetime of asphalt roads is relatively short and regular maintenance is required. The annual cost of maintenance is estimated to be around 2.14 billion dollars. This project aims to explore nanotechnology to increase the lifetime of asphalt roads by exploring nanomaterials with anti-oxidation activities. Liposomes will be used as a model system for the initial studies and asphalt doped liposomes and finally asphalt will be tested.
The aim of this project is to allow for Deep Learning approaches utilized by Eye For Infrastructure to rely less heavily on labelled training data as well as to produce more human-understandable and actionable results. The improved system would allow for a seamless integration with municipalities for automated infrastructure assessment.