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Area of Science:

  • Mining Engineering
  • Wireless Communication Technology
  • Industrial Internet of Things

Background:

  • Digitalization in mining requires robust data exchange for autonomous operations.
  • Underground environments pose significant challenges for wireless communication.
  • Manual data collection is inefficient and limits operational insights.

Purpose of the Study:

  • To present a Data Mule approach for digitalizing operations in active underground mining areas.
  • To demonstrate the feasibility of using LoRa technology for data collection in challenging subterranean environments.
  • To automate manual data collection processes, specifically at fuel gauges.

Main Methods:

  • Development and deployment of specialized LoRa Data Mule modules with mining-rated casings.
  • Implementation of a dynamic LoRa network for data transmission over large underground areas.
  • Utilizing custom communication protocols and commercial LoRa boards for connectivity.
  • Testing connectivity at operational speeds (20-40 km/h) and distances (180-770 m) with obstacles.

Main Results:

  • Successful data relay over distances of 180 to 770 meters, even with 90° turns and no line of sight.
  • Established reliable connectivity for LoRa Data Mule modules at travel speeds of 20 to 40 km/h.
  • Demonstrated the effectiveness of the Data Mule approach in a network of remote data generation points.
  • Validated LoRa's suitability for industrial applications and long-range underground communication.

Conclusions:

  • The LoRa Data Mule approach significantly advances digitalization in underground mining.
  • This technology enables automated data collection and improves operational flow management.
  • LoRa technology offers a viable solution for reliable wireless communication in challenging mining environments.