A multi-level IIOT platform for boosting mines digitalization

Research output: Contribution to journalArticleResearchpeer-review

Authors

  • Raul Minon
  • Juan Lopez-de-Armentia
  • Lander Bonilla
  • Aitor Brazaola
  • Ibai Lana
  • M. Carmen Palacios
  • Szymon Mueller
  • Michal Blaszczak
  • Herwig Zeiner
  • Julia Tschuden
  • Mohmammad Jusuf Quadri
  • Ignasi Garcia-Mila
  • Andrea Bartoli
  • Norbert Gomolla
  • Alberto Fernandez
  • Pablo Segarra
  • José Angel Sanchidrián

External Organisational units

  • Tecnalia
  • DMT GmbH
  • Universidad Politécnica de Madrid
  • University of Deusto
  • Poznan Supercomputing and Networking Centre
  • Joanneum Research Forschungsgesellschaft mbH
  • WorldSensing SL

Abstract

This paper presents an innovative IIoT multi-level platform tailored to address the specific needs of the mining domain. The platform has been conceptualized and built in the context of the illuMINEation European project. For this purpose, mining specific use cases have been designed such as promoting underground safe areas, performing efficient mining operations or boosting predictive maintenance approaches. Then, specific requirements have been identified and, as a result, the platform has been developed. It consists of four-level layered platform: (1) edge devices layer to manage several sensors deployed in the mines; (2) edge box layer to provide in-mine operations such as filtering, streaming and processing; (3) fog layer which offers an overall perspective of each mine; and (4) cloud layer to centralize the data of all the mines and to provide powerful processing capabilities. In addition, the platform is robustly secured in terms of protecting communications confidentiality and access control and also provides a toolbox aimed at manipulating 3D complex images to obtain operable mine-domain novel user interfaces. Finally, a platform validation is proposed where three different use cases are explained to better show and demonstrate the capabilities of the platform.

Details

Original languageEnglish
Article number107501
Number of pages16
JournalFuture generation computer systems
Volume163.2025
Issue numberFebruary
DOIs
Publication statusPublished - 27 Aug 2024