Projets novateurs réalisés

Développement stratégique de Mégaphone, pour un développement communautaire durable

MÉGAPHONE a pour mission de développer les compétences socioprofessionnelles des jeunes par la culture scientifique. Par le présent projet, Projet Mégaphone fait appel à une étudiante de maîtrise en gestion de l’innovation sociale pour lui confier un mandat de développement stratégique. Il comporte plusieurs éléments, notamment, l’élaboration d’un schéma de transformation sociale et une stratégie de financement, mettant en valeur l’originalité de l’initiative. Une stratégie associant subventions gouvernementales, autofinancement des activités et philanthropie.

Stability Modelling of a Five Axis CNC Machine

The Canadian tool, die and mold making industry had sales of $1.2 billion in 2002 that dropped by 40+% in the ensuing decade as manufacturing moved offshore in search for lower labor cost. Trade tensions, conflicts (Ukraine/Russia; Taiwan/China etc.), COVID pandemic and accompanying supply chain disruptions, increase in labour cost overseas, improved automation technology and rising transportation cost have eroded the advantage, and the Canadian market is once again on a growth trend predicted to reach $128 billion. The growth is fuelled by novel ways of machining to reduce production cost and increase productivity, greater employment, and higher wages (Cook, 2022) . Furthermore, transportation and labour accounts for 45% and 32% of the logistics cost and its reduction with reshoring is advantageous. A Canadian study, conducted by Deloitte Economic Advisory, identified Machinery manufacturing as a hotspot for reshoring. An estimated five to seven jobs are created in related industries for every job reshored in the manufacturing sector (Cook, 2022); an additional boost for Canadian employment. However, lack of skilled labor, manufacturing knowledge and lack of interest among youth in this domain is a challenge.

The focus of this, university/industry, partnership is on developing automation technology that assists operators during machine programming and by detecting and avoiding anomalies during machine setup and machine operation.

Big Data Research for Open Source Applications

Big data is a collection of data sets so large and complex that it becomes difficult to process using onhand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization. In this internship, we analyze a real-world big data set(s) to make sensible inferences by taking into account a selected range of criteria. A number of methods and algorithms are investigated, evaluated and evolved to advance the development of specialized tools and processes.

Evaluation and enhancement of the Craven SPORT services osteoarthritis program provision

For the past 5 years, Craven SPORT Services has been providing an osteoarthritis (OA) exercise intervention programs within their Saskatoon clinic. Demand for the OA program has grown considerably over the last two years with waitlists for each cycle of the program and increased client retention for consecutive program cycles (often several months and years). During this time there have been few avenues for a detailed assessment and evaluation of the OA program. The current metrics used to assess client engagement and objective progressions are time consuming. With the increase in program demand efforts need to be made to enhance the existing program for further expansion. A review of the existing practices and current time consuming metrics being used is needed. The current project is designed to analyze the current industry and research standards for objectively measuring the client outcomes when participating in an OA exercise intervention. Alongside a review of the existing measures being used by Craven SPORT services the implementation of new and efficient practices will be an objective of this project. The second half of the project will be to assess the impact and effectiveness of the implemented practices.

Monitoring Marsh Extent and Vegetation Composition in British Columbia’s South Coast using Remote Sensing and Machine/Deep Learning Models

Coastal salt marshes, such as those in southern British Columbia (BC), offer valuable ecosystem services, including providing habitats for various plant, fish, and bird species, protecting shorelines from storm surges and
erosion, and sequestering and storing carbon to mitigate climate change. However, this low-lying system is under threat due to rising sea levels and human disturbances, leading to significant marsh die-off and ecosystem
degradation in the past few decades. Therefore, it is critical to take action to restore disturbed marshes and conserve local ecosystems. This project was proposed to monitor marsh die-off and restoration using remote sensing (e.g., satellite imaging), which is effective for large-scale and repeated monitoring. Research results are expected to provide more insights into marsh die-off processes, reveal associated ecological and geomorphological mechanisms, and support local restoration efforts by partner organizations.

Data visualization and evidence synthesis to inform the Sensitive Measurement Project

To ensure that PPPH priority projects are developed using the most up-to-date evidence and to increase the likelihood of project success, evidence synthesis will be crucial in facilitating a deeper understanding of community health issues, the contributing factors, associated health inequities, and appropriate interventions to improve health outcomes. The objectives of this project are: 1) To develop effective evidence-based data visualization strategies for conveying sensitive measurement results for cervical and colorectal cancer screening participation; 2) To conduct evidence synthesis on country-wise incidence and prevalence of hysterectomy. Key findings from the evidence synthesis will be summarized into a comprehensive final report and a presentation. The evidence synthesis will contribute to a better understanding of important issues affecting the health of Albertans, as well as the contributing factors and interventions to improve health outcomes in the province.

Market Research

This project aims to thoroughly understand the diagnostic testing market in Canada, the US, and Globally. The project will task the intern to elucidate and report on the current global, North American, and Canadian landscape for Lateral Flow Assays (LFA’s), including identification of the current manufacturers, distributors and sellers, and test manufacturer and retail price points. The intern will discover and report on the current technologies in use and any new trends or technologies in colorimetric testing. This includes providing a comprehensive list of tests currently available and their pricing. Finally, the intern will be expected to produce a detailed report of a synthesis of their work with custom analysis, including charts and graphs, where helpful. There will also be a reference section capturing all the work referenced in their report.

The work performed by the intern will be invaluable to the Partner organization as a means of developing a strong understanding of the testing landscape that will include a go-to-market strategy.

Machine learning approach to monitoring and decarbonizing mineral processes

Within Canada’s commitment to the 2030 Agenda for Sustainable Development, a pivotal goal involves taking immediate action to combat climate change and its far-reaching effects. The specified target is a 40% to 45% reduction in the country’s total greenhouse gas (GHG) emissions below 2005 levels by 2030. To transition away from fossil fuels and embrace renewable energy sources, a strategic combination of solar and wind power,
coupled with energy storage solutions like lithium-ion batteries, emerges as a transformative approach.
While this renewable energy transition holds immense promise for long-term carbon emissions reduction, it is imperative to address and mitigate the environmental impacts associated with the production of these batteries. The proposed research seeks to refine mineral processing activities by leveraging machine learning, aiming to decrease carbon emissions significantly. The focus is on developing a versatile machine learning model designed to optimize energy consumption in processing plants, thereby bolstering the production of essential minerals for lithium-ion batteries in Canada. This innovative strategy not only aligns with the nation’s commitment to GHG reduction targets but also underscores a commitment to sustainable practices in resource extraction.

Accountium III – AI driven cash flow and budget prediction

Creative Emporium provides digital Accounting System Maintenance, minimizing human intervention. The current software does not have an intelligent engine to automate cash flow analysis and budget analysis. This process takes hours for an accountant to do manually and the results are not that accurate due to human errors.
The General objective of this proposal is to incorporate these analysis features into the current platform by building artificial intelligence tools, which will reduce manual work and increase productivity. These easy to use features will help businesses to plan their cash flow and budgets accordingly within minutes, and deliver reports via mobile devices anywhere anytime. The main activities of this project include:
1. Cash flow Analysis – automate cash flow prediction for different time intervals (monthly/quarterly/yearly)
2. Budget Analysis – automate budgets based on historic trends and relevant economic factors.

Coach MO: AI Coach for athletes engagement

MOTTIV Technologies and the University of Alberta team will create an “AI coach” which is a language based chatbot that will communicate to athletes, who use the MOTTIV app, with a defined vocabulary at the back-end effective for a coach-athlete relationship and training. The goal is to make the “Coach MO” chatbot proactive, engaging, motivating and the best 1-on-1 endurance coaches in the world.

Subsystem Optimization of Intelligent Automated Distribution Kiosk

This project is an R&D project intended to solve the problem relating to a piece of machinery, a retail kiosk for distribution of age-restricted beverages, that has overall reliability issues due to a compounding of sub-optimally performing devices and subsystems exacerbated by competing timeouts; and unpredictability of human users.

Nature-based solutions for health and economic-informed microclimate management

The research project promotes urban sustainability and the impact of preserving natural assets on health and the economy. It focuses on climate change adaptation and climate hazard mitigation, including, extreme heat, air quality, flooding, and high wind events. The research proposes a framework to predict and mitigate the impact of climate hazards on public health and wellbeing. The research uses multidisciplinary approaches to integrating data science and urban performance evaluation to predict the benefits of preserving natural assets (i.e., expanding greenery cover, employing cool surfaces, and green roofs) on reducing heatwave intensity, enhancing air quality, and mitigating stormwater runoff and exposure to high winds. It integrates community census and health data with weather measurements to predict public health outcomes including mortality, hospitalizations, ambulatory calls, and emergency department visits. It also quantifies the expected economic benefits of integrating the natural assets in terms of reduced mortality, avoided health system use, and increased worker productivity.

In collaboration with the Friends of Greenbelt Foundation, this research aims to develop a decision-making framework for municipalities and local governments to improve the urban environment and mitigate climate change impacts. The outputs of this research will support better health outcomes, environmental risk management, and building climatic-resilient communities.