Precision agriculture is one of the top revolutions in agriculture, which is the leading industry in food production for the entire human population. Fertilizers have been the key to boosting crop production and a major source of green gas emissions at the same time. The optimal and sustainable application of fertilizers is a significant challenge in precision agriculture that can save the farming cost for growers and reduce carbon emissions.

Manitoba has an opportunity to transform agriculture practices through advances in sensors, robotics, and machine learn-ing. Real-time, automated methods of in-field data collection are needed to increase productivity and sustainability in production agriculture, to expedite plant breeding and research, and to further the uptake of organic farming. To this end, we are developing a self-propelled, GPS-guided data rover for the rapid collection of plant images and environmental data in test plots, organic farms, and with partner EMILI, across a full-scale commercial farm.

A multi-party live video communication, such as live tutorials and fitness classes, are an emerging application which involves a large number of users from different places with heterogeneous network conditions like 3G/4G/5G or Wi-Fi networks. Video Content/Service providers usually deploy their Content Delivery Networks (CDNs) over the public Internet to avoid expenses of dedicated connectivity. Thus, they often seek solutions to provide seamless services over the changing conditions of Internet that can introduce packet error, packet loss, or out-of-order packets.

As vehicle systems become more advanced, accurate information about vehicle states, parameters, and surrounding operating conditions becomes paramount for vehicle health monitoring and driver control systems. This information is vital for the production, cost, and efficiency of the vehicles, as well as a key to improving passenger safety. In commercial vehicles, not all parameters of interest are directly measurable using sensors, because of sensor costs or design constraints.

COVID, remote work, remote learning and the accelerated adoption of technology globally has shifted the ways of how we live, learn, and our future lifestyles going forward. The 90% of society face challenges of how best to simplify their navigation and access to knowledge – those who may not have high value networks, and the means and resources to identify and access ways to upskill, reskill, or retrain to enter or re-enter the future workforce.

This goal of the project is compare tools that can be used to evaluate the job performance of paramedics in a fair, equitable and consistent way whether they live in Saskatchewan or somewhere else in the world. Individuals who have completed their paramedic training will be evaluated using a common real life situation that they will experience when working as a paramedic in our province. The situation will be experienced in an artificial environment or through the use of a mannequin doll.

The project aims to facilitate the research and development of new drugs by employing machine learning methods to generate new molecules. This includes understanding various properties about known molecules by training deep learning models for the purpose of molecular generation. The gained understanding of molecules will be used to improve existing models and generate novel molecules with high likelihood of satisfying given properties.

The attribution of textual sources remains a challenge in recommendation systems. The problem receives attention in academic circles. As part of this project, we will be developing an AI-powered recommender system to help users find out what to read next when it comes to technical documents like theses, manuscripts, and technical reports based on resources they have already read. Finding a good resource recommendation system can mitigate the time-consuming task of finding a valid reference for written paragraphs in a technical document.

The interns in this project will use their skills in researching parts and products that can be used to achieve the subprojects that we set out to create on the micro-mobility car. In some areas the students may use the machine shop and equipment found in the engineering building on York University campus to create parts. Lastly, the car will have to be tested for insurance and the received data collected to find an insurance suited for the car.

Creating an inclusive environment where different innovators can feel welcome and exploit their talents is an ethical imperative no company can ignore. The scientific literature also provides clear evidence that diverse teams are more creative and high-performing, and that the engineering industry has a diversity problem. The general objective of this proposal is to research methodologies, outcomes and best practices for STEM experiential-learning environments that engage student teams in community-driven projects that address societal-impactful, sustainability problems.