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On the Opportunities for Using Mobile Devices for Activity Monitoring and Understanding in Mining Applications

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Intelligent Data Engineering and Automated Learning – IDEAL 2018 (IDEAL 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11315))

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Abstract

Over the last decades, number of embedded and portable computer systems for monitoring of activities of miners and underground environmental conditions that have been developed has increased. However, their potential in terms of computing power and analytic capabilities is still underestimated. In this paper we elaborate on the recent examples of the use of wearable devices in mining industry. We identify challenges for high level monitoring of mining personnel with the use of mobile and wearable devices. To address some of them, we propose solutions based on our recent works, including context-aware data acquisition framework, physiological data acquisition from wearables, methods for incomplete and imprecise data handling, intelligent data processing and reasoning module, hybrid localization using semantic maps, and adaptive power management. We provide a basic use case to demonstrate the usefulness of this approach.

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Authors and Affiliations

  1. AGH University of Science and Technology, Cracow, Poland

    Grzegorz J. Nalepa, Edyta Brzychczy & Szymon Bobek

Authors
  1. Grzegorz J. Nalepa
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  2. Edyta Brzychczy
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  3. Szymon Bobek
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Corresponding author

Correspondence to Grzegorz J. Nalepa .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, UK

    Hujun Yin

  2. Rm 209, Building B, Autonomous University of Madrid, Madrid, Spain

    David Camacho

  3. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Seville, Seville, Spain

    Antonio J. Tallón-Ballesteros

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Nalepa, G.J., Brzychczy, E., Bobek, S. (2018). On the Opportunities for Using Mobile Devices for Activity Monitoring and Understanding in Mining Applications. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11315. Springer, Cham. https://doi.org/10.1007/978-3-030-03496-2_9

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  • DOI: https://doi.org/10.1007/978-3-030-03496-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03495-5

  • Online ISBN: 978-3-030-03496-2

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