Session D, April 29, 2021, 10:00 a.m. to 12:30 a.m. ET
Innovation in Geoscience: Implications of Emerging Technologies and Their Applications
Session Chairs: Mark Priddle, P.Geo., McIntosh Perry and Tony Andrews, Professional Geoscientists Ontario
A moderated Q & A will follow after the panel presentations.
Presentation 1: The Bissett Creek Graphite Deposit and its Role in the Green Economy
Speaker: Gregory Bowes, P.Geo., Chief Executive Officer, Northern Graphite - SEE SPEAKER'S BIO
Greg will provide an introduction to “graphite” and its uses as well its role in the green economy. He will also provide an overview of Northern’s Bissett Creek graphite project and the Company’s experience permitting a mine in Ontario.
Presentation 2: Getting the Most Out of Your Data and Efforts: Application of Machine Learning to Geoscience
Speakers: Rebecca Montsion, P.Geo. PhD Candidate at Laurentian University’s Mineral Exploration Research Center (MERC) and the University of Western Australia’s Center for Exploration Targeting (CET) - SEE SPEAKER'S BIO
Rebecca Montsion1,2, Stéphane Perrouty1, Mark Lindsay2
1. Mineral Exploration Research Centre, Harquail School of Earth Sciences, Laurentian University, Sudbury, Ontario P3E 2C6,
2. Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Australia
Recent adoption of machine learning to daily usage has sparked a renaissance in geoscience as quantitative approaches provide fresh insight and support for qualitative or interpretation-based approaches. A wide range of tools under the machine learning umbrella are often used for prediction and classification while automation provides more rapid analysis of increasingly large and complex databases. The resulting applications provide a unique opportunity to challenge current understanding and generate new hypotheses. Despite growing popularity, these computer-based workflows are often perceived as inaccessibly complex and are poorly utilized. This presentation will cover broad terms, benefits, and cautions for applying machine learning to geoscience.
Presentation 3: Water Management and Big Data – Are We There Yet?
Speakers: Steve Holysh, P.Geo., Senior Hydrogeologist, Co-Program Manager, Oak Ridges Moraine Groundwater Program - SEE SPEAKER'S BIO
The idea of Big Data is compelling. As the term increasingly surfaces in mainstream media and on-line, water resources scientists, technicians and consultants wonder how day to day work might be altered and how water resource management will change as we move forward. Of course, to make use of any of the analytics and sophistication offered by new technology, there must be a repository of Big Data to begin with. In Ontario, outside of the municipal water utilities which certainly have tremendous amounts of water data tied to their water and wastewater distribution systems, the Oak Ridges Moraine Groundwater Program (ORMGP) ranks near the top of the list in terms of water related Big Data. Now approaching 90 gigabytes in size, the ORMGP database can certainly be considered Big Data, especially when taking into account that hydrogeologists work in four dimensions and therefore the database is also conceptualized, managed, and analysed in four dimensions. As more water related data is assembled and centralized in hubs similar to that of the ORMGP, it has been proposed that an entire sub-discipline of water resources is needed to curate and analyse such Big Data. This is reflected in recent data consolidation initiatives in the United States where two states (California and New Mexico) have already passed Water Data Act legislation and where initiatives such as the Water Quality Portal (https://www.waterqualitydata.us/) and The Internet of Water (https://internetofwater.org/), are gaining steam. By applying various modelling, statistical, and visualization techniques, ORMGP staff are moving to make sense of large environmental and operational datasets to generate actionable information for decision makers.
Presentation 4: Teaching, Learning and Research with Electronic Circuits: Measurement and Monitoring of Environmental Phenomena
Speaker: Nicholas Kinar, Centre for Hydrology of University of Saskatchewan, Global Institute for Water Security - SEE SPEAKER'S BIO
In the last quarter of the 20th century, microcontrollers and electronic circuits became part of the normative technology utilized for environmental monitoring. Initially developed by research groups associated with universities and government organizations, environmental monitoring systems gradually became a technology provided by commercial companies. However, recent developments related to IoT (Internet of Things) platforms, open-source electronics (i.e. Arduino), the need for FAIR (findable, accessible, interoperable, and reusable) datasets, the use of FOSS (free and open source) software, and the cultural trend of the maker movement indicates the start of a new renaissance in environmental monitoring where circuit development is decentralized and a mix of proprietary and new electronic platforms are used to measure environmental phenomena. To demonstrate these developments, this talk presents examples of how emerging technologies such as 3D printing and novel electronic circuits can be used to teach hydrology and environmental science at the postsecondary level. Moreover, 3D printing and new electronic circuits with IoT capabilities also have the potential to revolutionize environmental monitoring by allowing for the development of new electronic circuits that increase the accuracy and spatial density of measurements. Examples of recent research are presented. These developments are discussed in the context of IoT systems and emerging technologies that have the potential to influence the monitoring and measurement of environmental processes in an operational context.
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