scholarly journals Applications of Unmanned Aerial Vehicles in Mining from Exploration to Reclamation: A Review

Minerals ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 663 ◽  
Author(s):  
Sebeom Park ◽  
Yosoon Choi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Mineral Exploration ◽  
Mining Industry ◽  
Working Environment ◽  
Ground Subsidence ◽  
Research Trend ◽  
Environment Analysis ◽  
Mining Sites ◽  
Aerial Vehicles ◽  
Exploration Exploitation

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.

scholarly journals Urban Natural Environment Analysis through Deep Learning Techniques on Automatically Acquired Images from Unmanned Aerial Vehicles

2020 ◽  
Author(s):  
Marco A Moreno-Armendáriz ◽  
Hiram Calvo ◽  
Carlos A Duchanoy ◽  
Anayantzin P López-Juárez ◽  
Israel A Vargas-Monroy ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Natural Environment ◽  
Environment Analysis ◽  
Aerial Vehicles ◽  
Learning Techniques

scholarly journals Systematic Review of Machine Learning Applications in Mining: Exploration, Exploitation, and Reclamation

Minerals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 148
Author(s):  
Dahee Jung ◽  
Yosoon Choi
Keyword(s):  
Machine Learning ◽  
Mineral Exploration ◽  
Mining Industry ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Research Papers ◽  
Recent Developments ◽  
Machine Learning Applications ◽  
Exploration Exploitation ◽  
Mining Exploration

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.

scholarly journals Assessing Peruvian University Students’ Preferences for Labor Conditions in Mining Site

2021 ◽  
Vol 13 (17) ◽  
pp. 9648
Author(s):  
Shuto Mikami ◽  
Yutaka Ito ◽  
Hernan Gabriel Oyola Gonzales
Keyword(s):  
Mining Industry ◽  
Individual Characteristics ◽  
Working Environment ◽  
Strong Impact ◽  
Skilled Workers ◽  
Mining Site ◽  
Mining Sites ◽  
Labor Conditions ◽  
Males And Females ◽  
Stable Employment

The mining industry is one of the biggest industries and has a strong impact in Peru. Despite the mining industry’s importance, it faces labor shortages and environmental risks. For these situations, mining students are important sources of workers not only as labor forces but also as skilled workers who can contribute to solving the environmental issues of mining companies. Thus, the purpose of this paper is to assess Peruvian university mining students’ preferences for labor conditions in mining sites using a discrete choice experiment in order to promote efficient improvements in labor conditions in mining sites that contribute to stable employment and address environmental concerns. The number of respondents was 222 in two Peruvian universities, including males and females aged 16–35 years. The analysis’s findings indicate that labor conditions at mining sites can be optimized by adjusting them to specific individual characteristics of potential mining workers, resulting in a more efficient working environment for companies and workers.

Development of thickened semi-synthetic engine oil M-5z / 20 AERO for four-stroke gasoline engines aircraft piston of unmanned aerial vehicles (UAVs)

2020 ◽  
Vol 06 ◽  
pp. 44-47
Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Engine Oil ◽  
Motor Oil ◽  
Gasoline Engines ◽  
State Research Institute ◽  
Technical Requirements ◽  
Aerial Vehicles ◽  
State Research ◽  
Industrial Batch ◽  
The Russian Federation

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.

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