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Internet of Things for Sustainable Mining

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Internet of Things for Sustainable Community Development

Part of the book series: Internet of Things ((ITTCC))

Abstract

The sustainable mining Internet of Things deals with the applications of IoT technology to the coupled needs of sustainable recovery of metals and a healthy environment for a thriving planet. In this chapter, the IoT architecture and technology is presented to support development of a digital mining platform emphasizing the exploration of rock–fluid–environment interactions to develop extraction methods with maximum economic benefit, while maintaining and preserving both water quantity and quality, soil, and, ultimately, human health. New perspectives are provided for IoT applications in developing new mineral resources, improved management of tailings, monitoring and mitigating contamination from mining. Moreover, tools to assess the environmental and social impacts of mining including the demands on dwindling freshwater resources. The cutting-edge technologies that could be leveraged to develop the state-of-the-art sustainable mining IoT paradigm are also discussed.

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References

  1. Assunção, T. W., & Gonçalves, L. M. B. (2017). Estimating volumes and tonnage using GPR data. In 2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR) (pp. 1–5). Piscataway: IEEE.

    Google Scholar 

  2. Aznar-Sánchez, J. A., Velasco-Muñoz, J. F., Belmonte-Ureña, L. J., & Manzano-Agugliaro, F. (2019). Innovation and technology for sustainable mining activity: A worldwide research assessment. Journal of Cleaner Production, 221, 38–54.

    Article  Google Scholar 

  3. Banerjee, B. P., Raval, S., Maslin, T. J., & Timms, W. (2018). Development of a UAV-mounted system for remotely collecting mine water samples. International Journal of Mining, Reclamation and Environment, 9, 1–12.

    Article  Google Scholar 

  4. Boullé, M. (2016). Predicting dangerous seismic events in coal mines under distribution drift. In 2016 Federated Conference on Computer Science and Information Systems (FedCSIS) (pp. 221–224). Piscataway: IEEE.

    Chapter  Google Scholar 

  5. Brusseau, M. (2019). Chapter 19 - Soil and groundwater remediation. In M. L. Brusseau, I. L. Pepper & C. P. Gerba (Eds.), Environmental and pollution science (3rd ed., pp. 329–354). Cambridge: Academic. https://doi.org/10.1016/B978-0-12-814719-1.00019-7. http://www.sciencedirect.com/science/article/pii/B9780128147191000197

    Chapter  Google Scholar 

  6. Chapter 9 - magnetometer technology. In Z. You (ed.), Space microsystems and micro/nano satellites, micro and nano technologies (pp. 341–360). Oxford: Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-812672-1.00009-6. http://www.sciencedirect.com/science/article/pii/B9780128126721000096

  7. Chung, C. C., Lin, C. P., Yang, S. H., Lin, J. Y., & Lin, C. H. (2019). Investigation of non-unique relationship between soil electrical conductivity and water content due to drying-wetting rate using TDR. Engineering Geology, 252, 54–64.

    Article  Google Scholar 

  8. Dalm, M. (2018). Sensor-based sorting opportunities for hydrothermal ore deposits: Raw material beneficiation in mining. Dissertation, Delft: Delft University of Technology. http://resolver.tudelft.nl/uuid:70a1e180-ef0c-4226-9af3-7e9dc3938c7f.

    Google Scholar 

  9. Dong, L., Shu, W., Sun, D., Li, X., & Zhang, L. (2017). Pre-alarm system based on real-time monitoring and numerical simulation using internet of things and cloud computing for tailings dam in mines. IEEE Access, 5, 21080–21089.

    Article  Google Scholar 

  10. Dubiński, J. (2013). Sustainable development of mining mineral resources. Journal of Sustainable Mining, 12(1), 1–6.

    Article  Google Scholar 

  11. Edwards, J. (2018). Signal processing opens the internet of things to a new world of possibilities: Research leads to new internet of things technologies and applications [special reports]. IEEE Signal Processing Magazine, 35(5), 9–12.

    Article  Google Scholar 

  12. Francke, J., & Utsi, V. (2009). Advances in long-range GPR systems and their applications to mineral exploration, geotechnical and static correction problems. First Break, 27(7), 85–93.

    Google Scholar 

  13. Gastauer, M., Silva, J. R., Junior, C. F. C., Ramos, S. J., Souza Filho, P. W. M., Neto, A. E. F., et al. (2018). Mine land rehabilitation: Modern ecological approaches for more sustainable mining. Journal of Cleaner Production, 172, 1409–1422.

    Article  Google Scholar 

  14. Ge, L., Chang, H. C., & Rizos, C. (2007). Mine subsidence monitoring using multi-source satellite SAR images. Photogrammetric Engineering & Remote Sensing, 73(3), 259–266.

    Article  Google Scholar 

  15. Ghosh, G., & Sivakumar, C. (2018). Application of underground microseismic monitoring for ground failure and secure longwall coal mining operation: A case study in an Indian mine. Journal of Applied Geophysics, 150, 21–39.

    Article  Google Scholar 

  16. Guo, J., Tong, J., Zhao, Q., Jiao, J., Huo, J., & Ma, C. (2019). An ultrawide band antipodal Vivaldi antenna for airborne GPR application. IEEE Geoscience and Remote Sensing Letters, 16, 1560–1564.

    Article  Google Scholar 

  17. Haldar, S. K. (2018). Mineral exploration: Principles and applications. Amsterdam: Elsevier.

    Google Scholar 

  18. Hyyppä, J., Jaakkola, A., Chen, Y., & Kukko, A. (2013). Unconventional LIDAR mapping from air, terrestrial and mobile. In Proceedings of the Photogrammetric Week (pp. 205–214). Germany: Wichmann/VDE Verlag Berlin.

    Google Scholar 

  19. Jiping, S. (2015). Accident analysis and big data and internet of things in coal mine. Industry and Mine Automation, 3, 1–5.

    Google Scholar 

  20. Jo, B., & Khan, R. (2018). An internet of things system for underground mine air quality pollutant prediction based on azure machine learning. Sensors, 18(4), 930.

    Article  Google Scholar 

  21. Jonathan, F. (1996). The role of remote sensing in finding hydrothermal mineral deposits on earth. Evolution of Hydrothermal, 21, 214.

    Google Scholar 

  22. Karthik, G., & Jayanthu, S. (2018). Review on low-cost wireless communication systems for slope stability monitoring in opencast mines. International Journal of Mining and Mineral Engineering, 9(1), 21–31.

    Article  Google Scholar 

  23. Kern, M., Tusa, L., Leißner, T., van den Boogaart, K. G., & Gutzmer, J. (2019). Optimal sensor selection for sensor-based sorting based on automated mineralogy data. Journal of Cleaner Production, 234, 1144–1152.

    Article  Google Scholar 

  24. Kiziroglou, M. E., Boyle, D. E., Yeatman, E. M., & Cilliers, J. J. (2016). Opportunities for sensing systems in mining. IEEE Transactions on Industrial Informatics, 13(1), 278–286.

    Article  Google Scholar 

  25. Klein, B., Wang, C., & Nadolski, S. (2018). Energy-efficient comminution: Best practices and future research needs. In Energy efficiency in the minerals industry (pp. 197–211). Berlin: Springer.

    Chapter  Google Scholar 

  26. Koch, P. H., Lund, C., & Rosenkranz, J. (2019). Automated drill core mineralogical characterization method for texture classification and modal mineralogy estimation for geometallurgy. Minerals Engineering, 136, 99–109.

    Article  Google Scholar 

  27. Kuhar, L. L., Bunney, K., Jackson, M., Austin, P., Li, J., Robinson, D. J., et al. (2018). Assessment of amenability of sandstone-hosted uranium deposit for in-situ recovery. Hydrometallurgy, 179, 157–166.

    Article  Google Scholar 

  28. Lawagon, C. P., Nisola, G. M., Mun, J., Tron, A., Torrejos, R. E. C., Seo, J. G., et al. (2016). Adsorptive Li+ mining from liquid resources by H2Tio3: Equilibrium, kinetics, thermodynamics, and mechanisms. Journal of Industrial and Engineering Chemistry, 35, 347–356.

    Article  Google Scholar 

  29. Lèbre, É., Corder, G. D., & Golev, A. (2017). Sustainable practices in the management of mining waste: A focus on the mineral resource. Minerals Engineering, 107, 34–42.

    Article  Google Scholar 

  30. Li, N., Yang, H., Li, T., Fan, Y., & Liu, Q. H. (2019). MIMO borehole radar imaging based on high degree of freedom for efficient subsurface sensing. IEEE Transactions on Geoscience and Remote Sensing, 57(6), 3380–3391. https://doi.org/10.1109/TGRS.2018.2884257

    Article  Google Scholar 

  31. Lishchuk, V., Lund, C., Lamberg, P., & Miroshnikova, E. (2018). Simulation of a mining value chain with a synthetic ore body model: Iron ore example. Minerals, 8(11), 536.

    Article  Google Scholar 

  32. Lööw, J., Abrahamsson, L., & Johansson, J. (2019). Mining 4.0—The impact of new technology from a work place perspective. Mining, Metallurgy & Exploration, 36(4), 701–707.

    Article  Google Scholar 

  33. McPhail, G., Ugaz, R., & Garcia, F. (2019). Practical tailings slurry dewatering and tailings management strategies for small and medium mines. In Proceedings of the 22nd International Conference on Paste, Thickened and Filtered Tailings. Crawley: Australian Centre for Geomechanics Perth.

    Google Scholar 

  34. Metternicht, G., Hurni, L., & Gogu, R. (2005). Remote sensing of landslides: An analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments. Remote Sensing of Environment, 98(2–3), 284–303.

    Article  Google Scholar 

  35. Meyers, J. M., Lampousis, A., & Vargas, O. (2018). Integration of near-surface geophysical measurements with data from aerial drones in a Hudson Valley vineyard. In SEG Technical Program Expanded Abstracts 2018 (pp. 2810–2812). Tulsa: Society of Exploration Geophysicists.

    Chapter  Google Scholar 

  36. Mi, J., Yang, Y., Zhang, S., An, S., Hou, H., Hua, Y., et al. (2019). Tracking the land use/land cover change in an area with underground mining and reforestation via continuous Landsat classification. Remote Sensing, 11(14), 1719.

    Article  Google Scholar 

  37. Mineral Resources for Future Generations. (2019). https://www.aims.rwth-aachen.de/

  38. Mishra, P., Kumar, S., Kumar, M., Kumar, J., et al. (2019). IoT based multimode sensing platform for underground coal mines. Wireless Personal Communications, 108(2), 1227–1242.

    Article  Google Scholar 

  39. Moomen, A., Bertolotto, M., Lacroix, P., & Jensen, D. (2019). Inadequate adaptation of geospatial information for sustainable mining towards agenda 2030 sustainable development goals. Journal of Cleaner Production, 238, 117954.

    Article  Google Scholar 

  40. Nordstrom, D. K., Blowes, D. W., & Ptacek, C. J. (2015). Hydrogeochemistry and microbiology of mine drainage: an update. Applied Geochemistry, 57, 3–16.

    Article  Google Scholar 

  41. Omotehinse, A., & De Tomi, G. (2019). Impact of mining activities on the achievement of sustainable development goals. In 9th International Conference on Sustainable Development in the Minerals Industry (SDIMI 2019).

    Google Scholar 

  42. Pai, S., Poedjono, B., & Hine, G. L. (2018). Earth surveying with aerial drones for improved drilling applications. US Patent Appilication No. 15/788,242.

    Google Scholar 

  43. Papachristos, C., Khattak, S., Mascarich, F., & Alexis, K. (2019). Autonomous navigation and mapping in underground mines using aerial robots. In 2019 IEEE Aerospace Conference (pp. 1–8). Piscataway: IEEE.

    Google Scholar 

  44. Qin, J., Cui, X., Yan, H., Lu, W., & Lin, C. (2019). Active treatment of acidic mine water to minimize environmental impacts in a densely populated downstream area. Journal of Cleaner Production, 210, 309–316. https://doi.org/10.1016/j.jclepro.2018.11.029. http://www.sciencedirect.com/science/article/pii/S0959652618334292

    Article  Google Scholar 

  45. Ranjan, A., Sahu, H., & Misra, P. (2019). Modeling and measurements for wireless communication networks in underground mine environments. Measurement, 149, 106980.

    Article  Google Scholar 

  46. Ranjan, A., Sahu, H., & Misra, P. (2019). Wireless robotics networks for search and rescue in underground mines: Taxonomy and open issues. In Exploring critical approaches of evolutionary computation (pp. 286–309). Pennsylvania: IGI Global.

    Chapter  Google Scholar 

  47. Salinas-Rodríguez, E., Hernández-Ávila, J., Cerecedo-Sáenz, E., Arenas-Flores, A., Reyes-Valderrama, M. I., Roldán-Contreras, E., et al. (2018). Leaching of silver contained in mining tailings: A comparative study of several leaching reagents. In Silver recovery from assorted spent sources: Toxicology of silver ions (p. 11). Singapore: World Scientific Publishing.

    Chapter  Google Scholar 

  48. Schoenberger, E. (2016). Environmentally sustainable mining: The case of tailings storage facilities. Resources Policy, 49, 119–128.

    Article  Google Scholar 

  49. Shustak*, M., Wechsler, N., Yurman, A., & Reshef, M. (2015). Comparison of surface vs. cross-hole seismic methods for void detection in the shallow sub-surface. In SEG Technical Program Expanded Abstracts 2015 (pp. 2286–2291). Tulsa: Society of Exploration Geophysicists.

    Google Scholar 

  50. Skousen, J., Zipper, C. E., McDonald, L. M., Hubbart, J. A., & Ziemkiewicz, P. F. (2019). Sustainable reclamation and water management practices. In Advances in productive, safe, and responsible coal mining (pp. 271–302). Amsterdam: Elsevier.

    Chapter  Google Scholar 

  51. Starke, L. (2002). Breaking new ground: Mining, minerals, and sustainable development: The report of the MMSD project, (Vol. 1). London: Earthscan.

    Google Scholar 

  52. Stewart, R., Chang, L., Sudarshan, S., Becker, A., & Huang, L. (2016). An unmanned aerial vehicle with vibration sensing ability (seismic drone). In SEG Technical Program Expanded Abstracts 2016 (pp. 225–229). Tulsa: Society of Exploration Geophysicists.

    Chapter  Google Scholar 

  53. Sun, E., Zhang, X., & Li, Z. (2012). The internet of things (IoT) and cloud computing (CC) based tailings dam monitoring and pre-alarm system in mines. Safety Science, 50(4), 811–815.

    Article  Google Scholar 

  54. Tadesse, B., Albijanic, B., Makuei, F., & Browner, R. (2019). Recovery of fine and ultrafine mineral particles by electroflotation–a review. Mineral Processing and Extractive Metallurgy Review, 40(2), 108–122.

    Article  Google Scholar 

  55. Terry, L. R., Kulp, T. R., Wiatrowski, H., Miller, L. G., & Oremland, R. S. (2015). Microbiological oxidation of antimony (III) with oxygen or nitrate by bacteria isolated from contaminated mine sediments. Applied and Environmental Microbiology, 81(24), 8478–8488.

    Article  Google Scholar 

  56. Unal, E. (1983). Development of design guidelines and roof-control standards for coal-mine roofs, Pennsylvania State University.

    Google Scholar 

  57. Wang, J., Guo, Y., Jia, Y., Zhang, Y., & Li, M. (2019). Modeling and application of the underground emergency hedging system based on internet of things technology. IEEE Access, 7, 63321–63335.

    Article  Google Scholar 

  58. West, G., & Macnae, J. (1991). Physics of the electromagnetic induction exploration method. In Electromagnetic methods in applied geophysics: Volume 2, application, parts A and B (pp. 5–46). Tulsa: Society of Exploration Geophysicists.

    Chapter  Google Scholar 

  59. Whitmore, A. (2006). The emperor’s new clothes: Sustainable mining? Journal of Cleaner Production, 14(3–4), 309–314.

    Article  Google Scholar 

  60. Xu, J., Gao, W., Xie, H., Dai, J., Lv, C., & Li, M. (2018). Integrated tech-paradigm based innovative approach towards ecological coal mining. Energy, 151, 297–308.

    Article  Google Scholar 

  61. Xu, J., Liu, C., Hsu, P. C., Zhao, J., Wu, T., Tang, J., et al. (2019). Remediation of heavy metal contaminated soil by asymmetrical alternating current electrochemistry. Nature Communications, 10(1), 2440.

    Article  Google Scholar 

  62. Yan, Z., Han, J., Yu, J., & Yang, Y. (2019). Water inrush sources monitoring and identification based on mine IoT. Concurrency and Computation: Practice and Experience, 31(10), e4843.

    Article  Google Scholar 

  63. Zeng, B., Zhang, Z., & Yang, M. (2018). Risk assessment of groundwater with multi-source pollution by a long-term monitoring programme for a large mining area. International Biodeterioration & Biodegradation, 128, 100–108.

    Article  Google Scholar 

  64. Zhou, J., Li, H., Zhao, L., & Chow, R. (2018). Role of mineral flotation technology in improving bitumen extraction from mined athabasca oil sands: I. flotation chemistry of water-based oil sand extraction. The Canadian Journal of Chemical Engineering, 96(9), 1986–1999.

    Article  Google Scholar 

  65. Zimroz, R., Hutter, M., Mistry, M., Stefaniak, P., Walas, K., & Wodecki, J. (2019). Why should inspection robots be used in deep underground mines? In Proceedings of the 27th International Symposium on Mine Planning and Equipment Selection-MPES 2018 (pp. 497–507). Berlin: Springer.

    Chapter  Google Scholar 

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Salam, A. (2020). Internet of Things for Sustainable Mining. In: Internet of Things for Sustainable Community Development. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-35291-2_8

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  • DOI: https://doi.org/10.1007/978-3-030-35291-2_8

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