A multi-level IIOT platform for boosting mines digitalization
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Fecha
2025-02
Autores
Miñón Jiménez, Raúl
López de Armentia Mendizabal, Juan
Bonilla, Lander
Brazaola, Aitor
Laña Aurrecoechea, Ibai
Palacios Prados, María Carmen
Mueller, Szymon
Blaszczak, Michal
Zeiner, Herwig
Tschuden, Julia
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Elsevier B.V.
Resumen
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.
Palabras clave
Big data
Cloud continuum
Edge
Fog
Mine digitalization
Cloud continuum
Edge
Fog
Mine digitalization
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Miñón, R., López-de-Armentia, J., Bonilla, L., Brazaola, A., Laña, I., Palacios, M. C., Mueller, S., Blaszczak, M., Zeiner, H., Tschuden, J., Quadri, M. Y., Garcia-Milà, I., Bartoli, A., Gormolla, N., Fernández, A., Segarra, P., Sanchidrián, J. A., & Hartlieb, P. (2025). A multi-level IIOT platform for boosting mines digitalization. Future Generation Computer Systems, 163. https://doi.org/10.1016/J.FUTURE.2024.107501