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Minerals
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Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in...
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Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".

Deadline for manuscript submissions: closed (18 January 2022) | Viewed by 58349

Special Issue Editor

Prof. Dr. Yosoon Choi

E-Mail Website
Guest Editor
Department of Energy Resources Engineering, Pukyong National University, Busan 48513, Korea
Interests: smart mining; renewables in mining; space mining; AICBM (AI, IoT, Cloud, Big Data, Mobile) convergence; unmanned aerial vehicle; mine planning and design; open-pit mining operation; mine safety; geographic information systems; 3d geo-modeling and geostatistics; hydrological analysis; energy analysis and simulation; design of solar energy conversion systems; renewable energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, much attention has focused on unmanned aerial vehicle (UAV) technology, to the extent that the term “drone industry” has been created. UAV technology is now widely used in many industries for purposes such as investigation of agricultural crops, observation of weather, relay broadcasting and communication, investigation of the extent of damage during disasters, recognition of traffic flow, and unmanned security. Artificial intelligence (AI) technology is also spreading across all industries so that innovative changes are taking place in the industrial field through the combination of AI and domain knowledge.

UAV and AI technologies have a significant impact on the mining industry. Applications of UAV and AI technologies have been reported in the mining industry for mineral exploration, mine planning and design, mine operation, mineral/metallurgical processing, mine health and safety management, and mine reclamation. This Special Issue (SI) encourages engineers, geologists, metallurgists, educators, students, and researchers to address recent applications of UAV and AI technologies in mining from exploration to reclamation. Original research contributions and reviews providing examples of the improvements brought by UAV and AI technologies in all areas of the mineral sector can be included in this SI.

Prof. Dr. Yosoon Choi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Unmanned aerial vehicles in mining
  • Unmanned aerial systems in mining
  • Drone in mining
  • Photogrammetry in mining
  • 3D modeling in mining
  • Digital surface model in mining
  • Artificial intelligence in mining
  • Machine learning in mining
  • Deep learning in mining
  • Soft computing in mining

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Related Special Issue

Published Papers (8 papers)

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Editorial

Jump to: Research, Review

3 pages, 174 KiB  
Editorial
Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation
by Yosoon Choi
Minerals 2023, 13(3), 382; https://doi.org/10.3390/min13030382 - 9 Mar 2023
Cited by 5 | Viewed by 2169
Abstract
Mining has been an essential aspect of human civilization, providing the raw materials necessary for the development of industries and infrastructure [...] Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)

Research

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43 pages, 16477 KiB  
Article
Design and Computational Analyses of Nature Inspired Unmanned Amphibious Vehicle for Deep Sea Mining
by Vijayanandh Raja, Senthil Kumar Solaiappan, Lokeshkumar Kumar, Arishwaran Marimuthu, Raj Kumar Gnanasekaran and Yosoon Choi
Minerals 2022, 12(3), 342; https://doi.org/10.3390/min12030342 - 10 Mar 2022
Cited by 17 | Viewed by 3920
Abstract
This paper presents the design calculations, implementations, and multi-engineering based computational constructions of an unmanned amphibious vehicle (UAmV) which efficiently travels underwater to detect and collect deep-sea minerals for investigations, as well as creative usage purposes. The UAmV is expected to operate at [...] Read more.
This paper presents the design calculations, implementations, and multi-engineering based computational constructions of an unmanned amphibious vehicle (UAmV) which efficiently travels underwater to detect and collect deep-sea minerals for investigations, as well as creative usage purposes. The UAmV is expected to operate at a 300 m depth from the water surface. The UAmV is deployed above the water surface near to the approximate target location and swims underwater, checking the presence of various mining, then extracts them using a unique mechanism and stores them in an inimitable fuselage location. Since this proposed UAmV survives in deep-sea regions, the design construction of this UAmV is inspired by hydrodynamic efficient design-based fish, i.e., Rhinaancylostoma. Additionally, standard analytical approaches are followed and, subsequently, the inimitable components such as wing, stabilizers, propellers, and mining storage focused fuselage are calculated. The computational analyses such as hydrodynamic investigations and vibrational investigations were carried out with the help of ANSYS Workbench. The hydrodynamic pressures at various deployment regions were estimated and thereafter the vibrational outcomes of UAmVs were captured for various lightweight materials. The computed outcomes were imposed in the analytical approach and thereby the electrical energy generations by the UAmV’s components were calculated. Finally, the hydrodynamic efficient design and best material were picked, which provided a path to further works on the execution of the focused mission. Based on the low drag generating design profile and high electrical energy induction factors, the optimizations were executed on this work, and thus the needful, as well as suitable UAmV, was finalized for targeted real-time applications. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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16 pages, 8862 KiB  
Article
Airborne/UAV Multisensor Surveys Enhance the Geological Mapping and 3D Model of a Pseudo-Skarn Deposit in Ploumanac’h, French Brittany
by Guillaume Martelet, Eric Gloaguen, Arne Døssing, Eduardo Lima Simoes da Silva, Johannes Linde and Thorkild M. Rasmussen
Minerals 2021, 11(11), 1259; https://doi.org/10.3390/min11111259 - 12 Nov 2021
Cited by 13 | Viewed by 2581
Abstract
Taking advantage of a multi-sensor (multispectral and magnetic) drone survey, we address the detailed geological mapping and modeling of a mineralization in its geological environment. We stress that these high-resolution data allow us to bridge the gap between field observations and a regional [...] Read more.
Taking advantage of a multi-sensor (multispectral and magnetic) drone survey, we address the detailed geological mapping and modeling of a mineralization in its geological environment. We stress that these high-resolution data allow us to bridge the gap between field observations and a regional aeromagnetic survey. On the one hand, the combination of multispectral imagery with field geological observations enhances detailed geological mapping. On the other hand, the combination of field magnetic susceptibility measurement and their use in detailed to regional magnetic modeling, constrained respectively by UAV-borne and airborne magnetic surveys, allows deriving a model of the mineralization consistent across the scales. This is demonstrated in a case study in a complex polyphased magmatic-metamorphic environment on the coast of French Brittany. The target area hosts a pseudo-skarn mineralization, exhibiting an outstanding magnetic anomaly. The combination of remotely sensed and field data allows deriving a realistic conceptual and geometrical model of the magnetic mineralization in its geological environment, tightly constrained by field observations and measurements. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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13 pages, 13737 KiB  
Article
Procedures of Detecting Damage to a Conveyor Belt with Use of an Inspection Legged Robot for Deep Mine Infrastructure
by Maria Stachowiak, Wioletta Koperska, Paweł Stefaniak, Artur Skoczylas and Sergii Anufriiev
Minerals 2021, 11(10), 1040; https://doi.org/10.3390/min11101040 - 25 Sep 2021
Cited by 14 | Viewed by 3926
Abstract
Conveying systems are responsible for a large part of continuous horizontal transportation in underground mines. The total length of a conveyor network can reach hundreds of kilometers, while a single conveyor usually has a route length of about 0.5–2 km. The belt is [...] Read more.
Conveying systems are responsible for a large part of continuous horizontal transportation in underground mines. The total length of a conveyor network can reach hundreds of kilometers, while a single conveyor usually has a route length of about 0.5–2 km. The belt is a critical and one of the most costly components of the conveyor, and damage to it can result in long unexpected stoppages of production. This is why proper monitoring of conveyor belts is crucial for continuous operation. In this article, algorithms for the detection of potential damage to a conveyor belt are described. The algorithms for analysis used video recordings of a moving belt conveyor, which, in case the of hazardous conditions of deep mines, can be collected, for example, by a legged autonomous inspection robot. The video was then analyzed frame by frame. In this article, algorithms for edge damage detection, belt deviation, and conveyor load estimation are described. The main goal of the research was to find a potential application for image recognition to detect damage to conveyor belts in mines. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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13 pages, 7589 KiB  
Article
Geological Mapping Using Drone-Based Photogrammetry: An Application for Exploration of Vein-Type Cu Mineralization
by Mehdi Honarmand and Hadi Shahriari
Minerals 2021, 11(6), 585; https://doi.org/10.3390/min11060585 - 31 May 2021
Cited by 25 | Viewed by 9475
Abstract
In this research, drone-based photogrammetry was utilized for mapping geology with the objective of mineral exploration in the Shahzadeh Abbas Cu deposit, Kerman province, Iran. Cu mineralization is of vein-type and follows geological structures. A low-cost drone was used to collect geological data. [...] Read more.
In this research, drone-based photogrammetry was utilized for mapping geology with the objective of mineral exploration in the Shahzadeh Abbas Cu deposit, Kerman province, Iran. Cu mineralization is of vein-type and follows geological structures. A low-cost drone was used to collect geological data. A spatial resolution of 3.26 cm was achieved by considering a flight altitude of 70 m. To reach the accuracy of less than 5 cm, 70% lateral and 80% front image overlaps were applied and 220 temporary ground control points (TGCPs) were used in an area of 2.02 km2. TGCPs were accurately positioned using DGPS-RTK measurements. Agisoft PhotoScan software was used for photogrammetric processing. The orthophoto product was performed for outlining geological units through visual interpretation. The digital elevation model (DEM) was converted to a hill-shade model in ArcGIS software to extract the geological structures such as faults and dikes. A draft geology map was prepared using orthophoto and hill-shade images to minimize the time and cost of the subsequent field work. Rock sampling was carried out and Cu-bearing veins were specified through field investigations. The geology map was finalized based on field work data and petrology studies. The geological survey indicated that diabase dikes with a northwest–southeast strike often host Cu mineralization in the study area. The position of Cu-bearing dikes was delineated for the next stage of the exploration program. This research demonstrated the time- and cost-effectiveness of using drone-based photogrammetry for preparing base geology maps for the exploration of vein-type mineralization in far districts with rough topography. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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10 pages, 2498 KiB  
Article
Monitoring and Controlling Saturation Zones in Heap Leach Piles Using Thermal Analysis
by Omar Daud, Mauricio Correa, Humberto Estay and Javier Ruíz-del-Solar
Minerals 2021, 11(2), 115; https://doi.org/10.3390/min11020115 - 24 Jan 2021
Cited by 4 | Viewed by 3058
Abstract
This manuscript describes a method that is based on the implementation and setup of a mechatronic system that can recognize and detect, through thermal analysis, the zones where heap leaching piles may become locally saturated. Such a condition could trigger the potential of [...] Read more.
This manuscript describes a method that is based on the implementation and setup of a mechatronic system that can recognize and detect, through thermal analysis, the zones where heap leaching piles may become locally saturated. Such a condition could trigger the potential of liquefaction, generating local or general collapse in the pile. In order to reduce this potential danger, and therefore achieve full stability in the pile, the irrigation system must be properly controlled; for instance, in potentially saturated zones, the irrigation flow can be reduced or eliminated until the saturation has disappeared. The mechatronic system consists of a hexacopter, equipped with a thermal infrared camera mounted on its structure and pointing down to the ground, which is used to obtain the temperature information of the heat transfer between the heap pile and the environment. Such information is very useful, as the level of saturated zones can then be traced. The communication between the operator of the irrigation system and the mechatronic system is based on a radio-frequency link, in which geo-referenced images are transmitted. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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Review

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20 pages, 5337 KiB  
Review
Systematic Review of Machine Learning Applications in Mining: Exploration, Exploitation, and Reclamation
by Dahee Jung and Yosoon Choi
Minerals 2021, 11(2), 148; https://doi.org/10.3390/min11020148 - 31 Jan 2021
Cited by 66 | Viewed by 15892
Abstract
Recent developments in smart mining technology have enabled the production, collection, and sharing of a large amount of data in real time. Therefore, research employing machine learning (ML) that utilizes these data is being actively conducted in the mining industry. In this study, [...] Read more.
Recent developments in smart mining technology have enabled the production, collection, and sharing of a large amount of data in real time. Therefore, research employing machine learning (ML) that utilizes these data is being actively conducted in the mining industry. In this study, we reviewed 109 research papers, published over the past decade, that discuss ML techniques for mineral exploration, exploitation, and mine reclamation. Research trends, ML models, and evaluation methods primarily discussed in the 109 papers were systematically analyzed. The results demonstrated that ML studies have been actively conducted in the mining industry since 2018, mostly for mineral exploration. Among the ML models, support vector machine was utilized the most, followed by deep learning models. The ML models were evaluated mostly in terms of their root mean square error and coefficient of determination. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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32 pages, 4467 KiB  
Review
Applications of Unmanned Aerial Vehicles in Mining from Exploration to Reclamation: A Review
by Sebeom Park and Yosoon Choi
Minerals 2020, 10(8), 663; https://doi.org/10.3390/min10080663 - 26 Jul 2020
Cited by 116 | Viewed by 15135
Abstract
Over the past decade, unmanned aerial vehicles (UAVs) have been used in the mining industry for various applications from mineral exploration to mine reclamation. This study aims to review academic papers on the applications of UAVs in mining by classifying the mining process [...] Read more.
Over the past decade, unmanned aerial vehicles (UAVs) have been used in the mining industry for various applications from mineral exploration to mine reclamation. This study aims to review academic papers on the applications of UAVs in mining by classifying the mining process into three phases: exploration, exploitation, and reclamation. Systematic reviews were performed to summarize the results of 65 articles (June 2010 to May 2020) and outline the research trend for applying UAVs in mining. This study found that UAVs are used at mining sites for geological and structural analysis via remote sensing, aerial geophysical survey, topographic surveying, rock slope analysis, working environment analysis, underground surveying, and monitoring of soil, water, ecological restoration, and ground subsidence. This study contributes to the classification of current UAV applications during the mining process as well as the identification of prevalent UAV types, data acquired by sensors, scales of targeted areas, and styles of flying control for the applications of UAVs in mining. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation)
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