Sensor Technologies for Safety Monitoring in Mine Tailings Storage Facilities: Solutions in the Industry 4.0 Era

被引:2
作者
Cacciuttolo, Carlos [1 ,2 ]
Guzman, Valentina [1 ]
Catrinir, Patricio [1 ]
Atencio, Edison [2 ,3 ]
机构
[1] Catholic Univ Temuco, Dept Civil Works & Geol, Temuco 4780000, Chile
[2] Univ Castilla La Mancha, Dept Civil Engn, Av Camilo Jose Cela S-N, Ciudad Real 13071, Spain
[3] Pontificia Univ Catolica Valparaiso, Sch Civil Engn, Av Brasil 2147, Valparaiso 2340000, Chile
关键词
mine tailings; safety; risks; sensors; remote sensing; real-time monitoring; wireless; Internet of Things; Industry; 4.0; PRE-ALARM SYSTEM; MOISTURE-CONTENT; DAM; SUSTAINABILITY; INTERNET; IDENTIFICATION; MANAGEMENT; THINGS; IOT;
D O I
10.3390/min14050446
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The recent tailings storage facility (TSF) dam failures recorded around the world have concerned society in general, forcing the mining industry to improve its operating standards, invest greater economic resources, and implement the best available technologies (BATs) to control TSFs for safety purposes and avoid spills, accidents, and collapses. In this context, and as the era of digitalization and Industry 4.0 continues, monitoring technologies based on sensors have become increasingly common in the mining industry. This article studies the state of the art of implementing sensor technologies to monitor structural health and safety management issues in TSFs, highlighting advances and experiences through a review of the scientific literature on the topic. The methodology applied in this article adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and utilizes scientific maps for data visualization. To do so, three steps were implemented: (i) a quantitative bibliometric analysis, (ii) a qualitative systematic review of the literature, and (iii) a mixed review to integrate the findings from (i) and (ii). As a result, this article presents the main advances, gaps, and future trends regarding the main characteristics of the sensor technologies applied to monitor TSF structural health and safety management in the era of digitalization. According to the results, the existing research predominantly investigates certain TSF sensor technologies, such as wireless real-time monitoring, remote sensors (RS), unmanned aerial vehicles (UAVs), unmanned survey vessels (USVs), artificial intelligence (AI), cloud computing (CC), and Internet of Things (IoT) approaches, among others. These technologies stand out for their potential to improve the safety management monitoring of mine tailings, which is particularly significant in the context of climate change-related hazards, and to reduce the risk of TSF failures. They are recognized as emerging smart mining solutions with reliable, simple, scalable, secure, and competitive characteristics.
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页数:34
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共 127 条
  • [1] Synergising water and energy requirements to improve sustainability performance in mine tailings management
    Adiansyah, Joni Safaat
    Rosano, Michele
    Vink, Sue
    Keir, Greg
    Stokes, Jason R.
    [J]. JOURNAL OF CLEANER PRODUCTION, 2016, 133 : 5 - 17
  • [2] A framework for a sustainable approach to mine tailings management: disposal strategies
    Adiansyah, Joni Safaat
    Rosano, Michele
    Vink, Sue
    Keir, Greg
    [J]. JOURNAL OF CLEANER PRODUCTION, 2015, 108 : 1050 - 1062
  • [3] Global sustainability of electric vehicles minerals: A critical review of news media
    Agusdinata, Datu Buyung
    Liu, Wenjuan
    [J]. EXTRACTIVE INDUSTRIES AND SOCIETY, 2023, 13
  • [4] Recent advances in flotation froth image analysis
    Aldrich, Chris
    Avelar, Erica
    Liu, Xiu
    [J]. MINERALS ENGINEERING, 2022, 188
  • [5] Estimation of Moisture Content in Thickened Tailings Dams: Machine Learning Techniques Applied to Remote Sensing Images
    Arancibia, Gabriel Villavicencio
    Bustamante, Osvaldo Pina
    Vigneau, Gabriel Hermosilla
    Allende-Cid, Hector
    Fuentelaba, Gonzalo Suazo
    Nieto, Victor Araya
    [J]. IEEE ACCESS, 2021, 9 : 16988 - 16998
  • [6] Araya N., 2021, MAT PROC, V5, P82, DOI [10.3390/materproc2021005082, DOI 10.3390/MATERPROC2021005082]
  • [7] Why have so many tailings dams failed in recent years?
    Armstrong, Margaret
    Petter, Renato
    Petter, Carlos
    [J]. RESOURCES POLICY, 2019, 63
  • [8] Enterprise Architecture Approach for Project Management and Project-Based Organizations: A Review
    Atencio, Edison
    Bustos, Guillermo
    Mancini, Mauro
    [J]. SUSTAINABILITY, 2022, 14 (16)
  • [9] A Study on Industrial IoT for the Mining Industry: Synthesized Architecture and Open Research Directions
    Aziz, Abdullah
    Schelen, Olov
    Bodin, Ulf
    [J]. IOT, 2020, 1 (02): : 529 - 550
  • [10] Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning
    Balaniuk, Remis
    Isupova, Olga
    Reece, Steven
    [J]. SENSORS, 2020, 20 (23) : 1 - 26