Leveraging Air Quality Sensing for Carbon Monoxide Transport Modeling in Underground Coal Mines

Kate Willa Brown Requist, Eric A Lutz, Moe Momayez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As air quality sensor networks become increasingly popular in underground coal mines, it is important to generate paradigms for the application of the collected data. To date, air quality sensing has been primarily used as an early warning system for hazardous air conditions. Using data collected from a network of sensors in a US underground coal mine, we have created multiple visualization methods to show the interactions of carbon monoxide evolution with ventilation airflow. These visualization methods can allow for further analysis of the source of contaminant, as well as better data resolution across the area of concern within the mine. By utilizing univariate spatial interpolations, we present methods for identifying the movement of carbon monoxide at one-minute intervals. The resulting visualizations display the evolution of carbon monoxide concentration across a sizeable study area over a period of 14 minutes.

Original languageEnglish (US)
Title of host publicationAPCOM 2023 Proceedings
Subtitle of host publicationIntelligent Mining: Innovation, Vision, and Value
PublisherSociety for Mining, Metallurgy and Exploration
ISBN (Electronic)9780873355216
StatePublished - 2023
EventAPCOM 2023 Conference: Intelligent Mining: Innovation, Vision, and Value - Rapid City, United States
Duration: Jun 25 2023Jun 28 2023

Publication series

NameAPCOM 2023 Proceedings: Intelligent Mining: Innovation, Vision, and Value

Conference

ConferenceAPCOM 2023 Conference: Intelligent Mining: Innovation, Vision, and Value
Country/TerritoryUnited States
CityRapid City
Period6/25/236/28/23

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Computer Science Applications

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