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Vol.:(0123456789)
Mineral Economics
https://doi.org/10.1007/s13563-024-00455-w
ORIGINAL PAPER
Technological advances andtrends inthemining industry:
asystematic review
RosalynnOrnellaFlores‑Castañeda1 · SandroOlaya‑Cotera2· MáximoLópez‑Porras3·
EstherTarmeño‑Juscamaita3· OrlandoIparraguirre‑Villanueva4
Received: 14 March 2024 / Accepted: 24 June 2024
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024
Abstract
Nowadays, in a competitive world, industries are faced with the urgent need to establish strategies for innovation, this is how
the mining industry, a sector that contributes to the global economy, has been implementing digital technologies obtaining
great results. Therefore, this paper aims to identify the most used technologies in the mining industry, determine in which
mining processes these technologies are applied, assess their positive environmental impact, and analyze the benefits derived
from their application to provide an integral view on the use and advantages of technology in the mining industry. The
PRISMA methodology was applied, considering 63 manuscripts from databases such as Scopus, Web of Science, Taylor
& Francis and ScienceDirect. As a result, it was found that the main digital technologies applied in the mining industry are
Internet of things (IoT) and artificial intelligence (AI). The main benefits of the application of digital technologies in the min-
ing industry are increased productivity, cost reduction, occupational safety, better working conditions, improved operational
efficiency and reliability of information. It is concluded that digital technologies achieve economic benefits, but above all
they contribute to the care of the environment and provide better working conditions. In other words, mining companies that
adopt digital technologies will be well positioned to succeed in the future.
Keywords Artificial intelligence· Mining· Technology· Automation· Mining exploration· Sensors
Introduction
The mining industry, is today, one of the main sectors that
contributes greatly to the global economy. However, moni-
toring factors associated with sustainability and safety in
mining operations globally is crucial to mitigate negative
socio-environmental effects. This includes the efficient
use of water, reduction of the carbon footprint, adoption of
renewable energies, reduction of mining waste and mini-
mization of occupational hazards Cacciuttolo etal. (2023).
In addition, with the evolution of geotechnology during the
Fourth Industrial Revolution, it focused on its application by
mining companies globally, offering significant benefits in
terms of operational optimization, informed decision making
and risk management Minbaleev etal. (2022).
In Colombia, one mining company has played a signifi-
cant role in the region of Segovia and Remedios, Antioquia,
providing approximately 20% of employment and contribut-
ing to gross wealth generation. In the 2002 period, the com-
pany generated 22,711 million pesos, and in 2003, 21,873
million pesos. In Chile, there was a notable decrease in pov-
erty levels in several localities between 2000 and 2006 due
to the presence of mining companies. For example, in Antof-
agasta, the poverty rate decreased from 12.9% to 6.1%; in
Sierra Gorda it fell from 3.4% to 2.7%; in Maria Elena from
14.6% to 5.3%; and in Tatlal from 32.9% to 5.5%. These
places experienced an increase in the quantity and quality
of jobs due to mining operations. In Peru, the mining indus-
try has had a significant impact on the economic and social
development of the southern region from 2007 to 2020, with
a contribution of 94.6% Simon etal. (2023)
It is indisputable that technologies have had a growth in
recent years involving continuos development in computer
* Rosalynn Ornella Flores-Castañeda
rfloresc@ucv.edu.pe
1 Universidad César Vallejo, Lima, Perú
2 Universidad San Ignacio de Loyola, Lima, Perú
3 Universidad Privada del Norte, Lima, Perú
4 Universidad Tecnológica del Perú, Chimbote, Perú
R.O.Flores-Castañeda et al.
applications, network technology, data storage technology.
However, choosing which digital technologies to apply is no
simple task Barnewold and Lottermoser (2020). Regardless
of the sector, the application of digital technologies pro-
vides multiple benefits because it facilitates the collection
and transmission of data between devices, leaving behind
traditional methods that lead to higher investment, costs,
and maintenance. AI can be combined with cloud comput-
ing, big data, computational intelligence, intelligent sensors,
IoT and others Wei etal. (2023). In other words, soon it
will be possible to significantly outperform human perfor-
mance in a variety of applications that are currently car-
ried out Ong and Gupta (2019). Specifically, AI is playing a
key role in helping companies address these challenges and
find more effective solutions Barnewold and Lottermoser
(2020). In the mining industry, the implementation of AI
is being considered for two main reasons: first, to optimize
productivity and, second, to reduce the potential impact on
the environment through the adoption of ethical mining
practices Mishra (2021). So, in recent years, there has been
a significant increase in the application of AI, especially
machine learning Sirisha etal. (2022) and deep learning (Ali
and Frimpong 2020), in production environments. This pro-
gress has led to the development of intelligent tools capable
of instantaneous information gathering and sharing Sirisha
etal. (2022) to solve different problems related to mineral
exploration, extraction, and processing Ali and Frimpong
(2020). The selection and operation of both underground
and surface equipment, drilling and blasting of rocks, etc.,
are also important factors Ali and Frimpong (2020). In
other words, greater accuracy in the extraction of miner-
als can be obtained with respect to conventional methods,
improving time, safety, productivity, and profitability Yada-
gir etal. (2023). This means that machines are being built
that perform their functions more efficiently, perform tasks
more quickly and safely, and are also more environmentally
friendly Ali and Frimpong (2020). Therefore, the integra-
tion of data from various sources is important, consider-
ing important aspects such as ethics and safety McGaughey
(2020).
The adoption of advanced technology has had a positive
impact in several areas of the mining industry. For exam-
ple, Onifade etal. (2023) analyzed the technological evolu-
tion in mining, highlighting the possible adoption of digital
technologies such as: automation, virtual reality, Big Data,
IoT, cyber security. Improvements are foreseen in processes
such as drilling, ventilation, and subway support, as well as
in communication. However, identified challenges, such as
privacy, legislation, and limitations in wireless networks in
complex mines.
Xu etal. (2023) reported on the relationship between
digital transformation (DT) and corporate social responsi-
bility (CSR) in the mining sector, analyzing 1305 publicly
traded mining companies. Technologies such as AI, block-
chain, cloud computing and big data were highlighted for
application in the mining industry. It was concluded that
miners can use emerging technologies to improve effi-
ciency, address social and environmental concerns, and
reduce negative impact on the environment and employee
health.
In addition, Pouresmaieli etal. (2023) focused on
understanding the impact of IoT technology on mining
and sustainable development. They concluded that IoT, by
interacting with industrial machinery and interconnected
networks, enables real-time monitoring and operation of
production systems, improving efficiency and reducing
human intervention. This impacts on increased production,
occupational safety, and reduced pollution. The results
indicated that IoT-based mining can boost productivity,
wealth, revenue, and gross domestic product (GDP), as
well as reduce operating expenses and depreciation costs,
with a positive impact on the environment by reducing
pollution.
Zhironkin and Taran (2023) explored the influence of
digitalization on open-pit mining and its impact on global
energy supply. Predicted that by 2050, 80–90% of the min-
ing industry will adopt digital technologies such as AI,
IoT, machine vision and unmanned equipment to address
energy, environmental and social issues. In addition, it was
recognized that the transition to renewable energy sources
will take time and it is crucial to drive innovation in Min-
ing 4.0 to reduce environmental impact. In this regard,
the need to modernize fossil energy production in a more
efficient pointed out that sustainable alternatives to renew-
able energy will remain important. In other words, mining
companies can maintain their profitability through smart
mining systems based on Industry 4.0 and Mining 4.0.
Similarly, Zhironkina and Zhironkin (2023) addressed
the transition of the mining industry to Mining 4.0 in the
context of Industry 4.0. They emphasized the importance
of humanization, with "smart" unmanned machines and
consideration of post-mining recycling activities. Digitiza-
tion in mining opens opportunities to improve productivity
and occupational safety. As for Mining 4.0 it differs from
previous industrial revolutions by focusing on the con-
nection between people, machines, and technologies, not
just automation. It was concluded that Mining 4.0 has the
potential to increase production, reduce costs and improve
occupational safety.
This paper aims to identify the most used technologies
in the mining industry, determine in which mining pro-
cesses these technologies are applied, assess their positive
environmental impact, and analyze the benefits derived
from their application to provide an integral view on the
use and advantages of technology in the mining industry.
Technological advances andtrends inthemining industry: asystematic review
Materials andmethods
This study uses the PRISMA methodological approach,
which provides advantages for authors, editors and review-
ers involved in the evaluation of systematic reviews. This
methodology guides researchers in the task of concisely
synthesizing the information contained in articles or
research sources related to the research. It aims to improve
the transparency, completeness, and accuracy of publica-
tions to facilitate decision-making based on solid evidence
Sohrabi etal. (2021).
Prisma offers a structure that acts as a set of guidelines
for a more systematic and understandable development.
The following are the corresponding steps according to
the PRISMA method:
– Include documents relevant to the research.
– Exclude duplicate documents.
– Eligibility analysis is developed.
Research questions
The questions for the present research in the systematic
review are:
RQ1: What are the most used technologies in the mining
industry?
RQ2: In which process of the mining industry can the
technologies be applied?
RQ3: What is the positive environmental impact of these
technologies?
RQ4: What are the benefits of applying the technologies
in the mining industry?
Search strategy
The string used for the research-responsive manuscript
search is presented in Fig.1.
After searching the databases using the search strings
described in Table1 the manuscripts that meet the research
objective were reviewed as shown in Fig.2 the largest num-
ber Web of Science.
A total of 1755 scientific articles were identified dur-
ing the search in various databases. These articles were
subjected to exclusion criteria that included verification
of duplicities between the results of the databases and rel-
evance to the research topic. After this process, 63 articles
relevant to the research were selected, as detailed in Fig.3
which illustrates the application of the PRISMA methodol-
ogy in the selection process.
Manuscripts were selected by applying the inclusion and
exclusion criteria, as shown in Table2.
"mining industry" OR "mining exploration" AND "mining activity" AND "minerals" AND
technology
Fig. 1 Search chain for documents related to the research topic
Table 1 Search string
Database Search string Filters
Scopus "mining industry" OR "mining exploration" AND "mining
activity" AND "minerals" AND technology
TITLE-ABS-KEY ("mining industry" OR "mining explora-
tion" AND "mining activity" AND "minerals" AND tech-
nology) AND PUBYEAR > 2012 AND PUBYEAR < 2024
AND (LIMIT-TO (DOCTYPE, "ar") OR LIMIT-TO
(DOCTYPE, "cp"))
Web of Science "mining industry" OR "mining exploration" AND "mining
activity" AND "minerals" AND technology (All Fields)
and 2024 or 2023 or 2022 or 2021 or 2020 or 2015 or
2014 or 2013 or 2016 or 2017 or 2018 or 2019 (Publica-
tion Years) and Open Access and Article or Proceeding
Paper (Document Types) and English (Languages)
Taylor & Francis [All: "mining industry"] OR [[All: "mining exploration"]
AND [All: "mining activity"] AND [All: "minerals"] AND
[All: technology]] AND [Article Type: Article] AND
[Publication Date: (01/01/2013 TO 12/31/2023)]
ScienceDirect "mining industry" OR "mining exploration" AND "mining
activity" AND "minerals" AND technology
R.O.Flores-Castañeda et al.
Fig. 2 Information resources
Fig. 3 Scientific article selec-
tion process according to
PRISMA methodology
Technological advances andtrends inthemining industry: asystematic review
Results
In the present study, 1755 articles obtained from the vari-
ous databases were analyzed. After applying the PRISMA
methodology, as shown in Fig.4, 3 articles were found in
Science Direct, 3 articles in Scopus, 1 article in Taylor &
Francis and 56 articles in Web of Science for a total of 63
scientific articles with relevant information were obtained.
Figure4 shows the distribution of articles obtained
from the different databases with the keywords used, with
a clear majority of articles obtained from Web of Science
for the period from 2013 to 2023.
Figure5 specifies the database and the year of publication
of the articles, showing that 17 manuscripts were published
in 2022 which is the year when publications peaked in the
given time frame.
The country with the highest number of published arti-
cles significant for this research is China with a total of 10
manuscripts, the United States with 7, Poland with 6, South
Africa with 5 and Russia with 4, as shown in Fig.6.
As what continents the research was focussed on it was
found that Asia and Europe are the leading continents with
a total of 23 articles respectively, followed by the Americas
with 12 publications and finally Africa with 5 publications,
as can be seen in Fig.7.
A bibliometric analysis was performed, which consists
of a quantitative analysis using statistical methods, biblio-
graphic mapping, among others, with the objective of find-
ing trends in a specific topic Rahman etal. (2020).
VOSviewer was the tool used to perform the bibliomet-
ric analysis, which makes graphical representation of bib-
liometric networks possible. These networks can consider
journals, researchers or individual publications being cre-
ated from citations, co-authorships, bibliometric coupling,
or co-citation VOSviewer—Visualizing Scientific Land-
scapes (2024).
Figure8 shows the network diagram which represents
the main digital technologies that are having a great impact
on the mining industry. The technologies are grouped
Table 2 Inclusion and exclusion criteria
Inclusion criteria Justification
• Manuscripts related to technological advances and trends in the min-
ing industry
• Aligned with the research objective
• Manuscripts mentioning mining industry processes in which tech-
nologies can be applied
• Obtain specific and practical knowledge that is valuable for the
improvement and sustainable development of the industry
• Manuscripts mentioning the contribution to environmental care of the
technologies applied in the mining industry
• To provide essential information to assess the environmental sustain-
ability of mining practices, facilitating responsible decision making
and the promotion of greener approaches in the sector
• Manuscripts mentioning the benefits of the application of technolo-
gies in the mining industry
• Analyze how technologies improve efficiency, reduce costs, optimize
processes, and contribute to safety, facilitating informed decisions for
the development and competitiveness of the mining sector
• Manuscripts no more than 11years old • It guarantees the relevance and timeliness of the information, allow-
ing access to recent research that reflects advances and current trends
in the application of technologies in the mining industry
• Full text manuscripts • Increased number of publications and reliability
• Manuscripts in English • Increased number of publications and reliability
• Papers published in relevant databases • Credibility ensuring the authenticity of the investigation
Exclusion criteria Justification
• Research other than articles • Books, theses, manuals, or similar research
• Studies unrelated to technological developments and trends in the
mining industry
• They do not contribute to the research
• Items over 11years old • Recent information is needed to contribute to the study
Fig. 4 Articles grouped by database
R.O.Flores-Castañeda et al.
around four main themes: first sustainability because
they seek to reduce the environmental impact they cause
when extracting minerals, the second theme is artificial
intelligence with which it is possible to ensure job safety
and efficiency, highlighting robotics, artificial vision, and
autonomous mining. The third theme is digitalization
because with IoT, big data and augmented reality data are
collected in real time for analysis and finally the theme of
Fig. 5 Articles grouped by year and database
Fig. 6 Articles grouped by
country of affiliation of first
author
Technological advances andtrends inthemining industry: asystematic review
innovation stands out because with digital technologies
new approaches to mining such as space mining and urban
mining are presented.
In other words, digital technologies are driving the
transformation of the mining industry, making it more
sustainable, efficient, and safe. Considering the reduction
of environmental impact and achieving sustainability by
finding ways to operate sustainably.
Discussion
RQ1: What are the most used technologies in the mining
industry?
As can be seen in Table3 and Fig.9, in the last ten
years, IoT is the most used digital technology in the mining
industry. Involves the creation of a networks where vari-
ous devices communicate making possible remote monitor-
ing and access to information in real time of the activities
performed by workers in the mine. Sensors integrated into
work clothes monitor the health and physical conditions of
workers and thus can assess urgent medical situations. Also,
with IoT you can monitor environmental conditions such as
temperature, humidity, and air quality to identify hazard-
ous situations. Therefore, with IoT it is possible to improve
efficiency, reduce human intervention, increase production,
reduce pollution, and ensure occupational safety Poures-
maieli etal. (2023). According to Adjiski etal. (2019) nowa-
days worker safety has become a priority with the objective
of using all the information collected to prevent accidents.
As for other digital technologies, it was found that artifi-
cial intelligence (autonomous learning, neural networks,
machine learning, automatic speech recognition (ASR),
Big Data and robotics) represent important new applied
digital technologies for the automation of processes, simu-
late human behavior, autonomous vehicles, robotization of
operational and risky activities, in all making mining more
sustainable Onifade etal. (2023).
Fig. 7 Articles grouped by continent
Fig. 8 Visualization of the bib-
liometric analysis network
R.O.Flores-Castañeda et al.
RQ2: In which process of the mining industry can the
technologies be applied?
Table4 and Fig.10 shows the various processes in the
mining industry in which digital technologies are being
applied to improve efficiency and sustainability. For exam-
ple, in the exploration process, remote sensors, satellite
sensors and drones are used to analyze geological and
topographic data considering the ruggedness of the area,
in addition to the fact that there may not be a wireless
communications infrastructure that makes possible the
application of IoT, which enables accessibility to infor-
mation in a more accurate and efficient way Pouresmaieli
etal. (2023). In addition, with machine learning it is pos-
sible to analyze historical data to locate the occurrence of
minerals, thus optimizing the exploration process. As for
the extraction process, which includes excavation, great
achievements have also been made with digital technolo-
gies such as improving the safety of personnel, ensuring
much more responsible practices, use of machines that
Table 3 Most applied digital technologies in the mining industry
Technologies % Manuscripts
Industrial Revolution 3.0 Internet of Things (IoT) 35 (Adjiski etal. 2019; Aguirre-Jofré etal. 2021; Alenezi etal. 2022; Barnewold and
Lottermoser 2020; Bi etal. 2022; Bisschoff and Grobbelaar 2022; Bui etal. 2019;
Evsutin and Meshcheryakov 2020; Gackowiec and Podobinska-Staniec 2019; Jacksha
and Raj 2021; Li etal. 2021; Lööw etal. 2019; Majstorovic etal. 2021; McNinch
etal. 2019; Min etal. 2023; Oltmanns and Petruska 2023; Pandey and Mishra 2022;
Radonjic etal. 2022; Samylovskaya etal. 2022; Stefaniak etal. 2023; Van Hau etal.
2022; Zulu etal. 2021)
Big Data 13 (Barnewold and Lottermoser 2020; Bi etal. 2022; Bisschoff and Grobbelaar 2022;
Evsutin and Meshcheryakov 2020; Pytel etal. 2020; Samylovskaya etal. 2022; Van
Hau etal. 2022; Zulu etal. 2021)
Cloud computing 10 (Aguirre-Jofré etal. 2021; Bi etal. 2022; Majstorovic etal. 2021; Newman etal. 2018;
Pandey and Mishra 2022; Van Hau etal. 2022)
Indust rial Revolution 4.0 Autonomous learning 11 (Barnewold and Lottermoser 2020; Bi etal. 2022; Gackowiec and Podobinska-Staniec
2019; Li etal. 2021; Mtotywa and Dube 2023; Stefaniak etal. 2022; Zulu etal. 2021)
Neural networks 3 (Li etal. 2023; Santoro etal. 2022)
Machine learning 3 (Barnewold and Lottermoser 2020; Min etal. 2023)
Blockchain 5 (Bi etal. 2022; Evsutin and Meshcheryakov 2020; Liang etal. 2020)
Robotics 8 (Barnewold and Lottermoser 2020; Li etal. 2022; Lopes etal. 2018; Samylovskaya
etal. 2022; Zulu etal. 2021)
Augmented reality 3 (Kim etal. 2018; Samylovskaya etal. 2022)
Virtual reality 3 (Kim etal. 2018; Samylovskaya etal. 2022)
Automatic Speech
Recognition (ASR)
2 (Stefaniak etal. 2022)
Fig. 9 Most applied digital
technologies in the mining
industry
35%
13%
10%
11%
8%
5%
3%
3%
3%
3%
2%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Internet of Things (IoT)
Big Data
Cloud computing
Autonomous learning
Robotics
Blockchain
Neural networks
Machine learning
Augmented reality
Virtual reality
Automatic Speech Recognition (ASR)
Technological advances andtrends inthemining industry: asystematic review
have an autonomous learning which can perform opera-
tional activities risky for humans Lopes etal. (2018). Pro-
cessing is the third process in which processes have been
automated to increase efficiency, and an important factor
is the quality of the minerals extracted to meet established
standards. The transportation process continues with the
routes followed to transport the minerals, as well as the
importance of remote monitoring of the vehicles to ensure
safety. Finally, the closing process, which must be planned
to minimize the environmental impact, the Blockchain
technology is applied to know the traceability of this pro-
cess through the registration of activities, verification and
compliance, waste management, audits, and mine closure
certifications Zhironkin and Taran (2023).
In conclusion, all mining industry processes can evolve
significantly, to make more informed decisions, reduce
risks, and optimize the identification of valuable mineral
deposits with the application of digital technologies.
RQ3: What is the positive environmental impact of these
technologies?
It is no secret that human activities have negatively
impacted the environment with decreased biodiversity,
pollution of land, air, and water, work related injuries and
causalties as well negative impact on local communities
as a consequence Zhironkin and Taran (2023). Table5 and
Fig.11 lists digital technologies that have a positive envi-
ronmental impact on the mining industry by facilitating
accurate planning and process automation, contributing to
the protection and restoration of terrestrial ecosystems. In
addition, real-time monitoring, water purification and air
quality control ensure pollution reduction, while process
optimization reduces waste and favors the use of renew-
able energy. The implementation of these technologies not
only protects the surrounding ecology, but also reduces
the overall ecological footprint of the mining activity,
Table 4 Mining industry processes where digital technologies are being applied
Processes % Manuscripts
Exploration 17 (Alenezi etal. 2022; Bertoni etal. 2022; Evsutin and Meshcheryakov 2020; Kim etal. 2018; Li etal. 2023; Lopes
etal. 2018; Newman etal. 2018; Ozhigin etal. 2022; Qarahasanlou etal. 2022; Shrivastava and Vidhi 2020;
Stefaniak etal. 2022)
Extraction (Excavation) 44 (Evsutin and Meshcheryakov 2020; Flores etal. 2020; Gackowiec and Podobinska-Staniec 2019; Karu etal. 2013;
Li etal. 2023; Liang etal. 2020; Lopes etal. 2018; Majstorovic etal. 2021; McNinch etal. 2019; Min etal. 2023;
Newman etal. 2018; Ngoma etal. 2023; Ozhigin etal. 2022; Pandey and Mishra 2022; Pesa 2021, 2022; Pytel
etal. 2020; Radonjic etal. 2022; Raevich etal. 2023; Rahimi etal. 2022; Rebbah etal. 2021; Samylovskaya etal.
2022; Shrivastava and Vidhi 2020; Sobczyk etal. 2021; Van Hau etal. 2022; Zarubin etal. 2021; Zeng etal.
2023)
Processing 11 (Gackowiec and Podobinska-Staniec 2019; Li etal. 2021, 2022; Li etal. 2023; Lööw etal. 2019; Min etal. 2023;
Shrivastava and Vidhi 2020)
Transportation 8 (Aguirre-Jofré etal. 2021; Evsutin and Meshcheryakov 2020; Li etal. 2021; Shrivastava and Vidhi 2020; Stefaniak
etal. 2023)
Closing 3 (Qarahasanlou etal. 2022; Shrivastava and Vidhi 2020)
Fig. 10 Mining industry pro-
cesses where digital technolo-
gies are being applied
17%
44%
11% 8%
3%
0%
10%
20%
30%
40%
50%
%
Exploration Extraction (Excavation)
Processing Transportation
Closing
R.O.Flores-Castañeda et al.
improving ecological quality and promoting sustainable
practices in the industry Zhironkina and Zhironkin (2023).
Therefore, the mining industry is applying digital tech-
nologies because there are many benefits that are achieved
from an economic perspective and the added value that
these technologies reduce the negative impact on the envi-
ronment and ensures the health of workers Zhironkina and
Zhironkin (2023).
Effective implementation of these technologies can lead
to more environmentally responsible mining, allowing the
industry to move towards more sustainable practices and
mitigate the historical negative impacts associated with
the extraction of mineral resources.
RQ4: What are the benefits of the application of tech-
nologies in the mining industry?
Today it has been demonstrated that digital technolo-
gies bring with them many benefits in the various sectors
in which they are applied and that one of their main objec-
tives is to improve the quality of life of people. The applica-
tion of technologies in the mining industry brings several
significant benefits in several key aspects as mentioned in
Table6 and Fig.12. These benefits include significantly
increased productivity and competitiveness, effective reduc-
tion of operating costs, strengthened occupational safety
through monitoring systems, enhanced value creation both
Table 5 Positive environmental impact because of the application of digital technologies
Positive environmental impact % Manuscripts
Social responsibility 10 (Litvinenko etal. 2020; Posleman and Sallan 2019; Shrivastava and Vidhi 2020; Tur-
cotte and Lachance 2023; Wozniak and Pactwa 2018; Yousefian etal. 2023)
Sustainable Development (Protect, restore, and
promote the sustainable use of terrestrial eco-
systems)
17 (Litvinenko etal. 2020; Marimuthu etal. 2021; Nguyen etal. 2021; Pandey and Mishra
2022; Poudyal etal. 2019; Qarahasanlou etal. 2022; Shrivastava and Vidhi 2020;
Sobczyk etal. 2021; Van Hau etal. 2022; van Wyk and de Villiers 2019; Zulu etal.
2021)
Reduction of environmental impact 14 (Bertoni etal. 2022; Bi etal. 2022; Li etal. 2022; Ngoma etal. 2023; Oncioiu etal.
2019; Van Hau etal. 2022; van Wyk and de Villiers 2019; Wozniak and Pactwa 2018;
Zarubin etal. 2021)
Water purification 5 (Karu etal. 2013; Li etal. 2022; Stander and Broadhurst 2021)
Air quality monitoring 2 (Bui etal. 2019)
Waste reduction 10 (Karu etal. 2013; Li etal. 2022; Lopes etal. 2018; Marimuthu etal. 2021; Shrivastava
and Vidhi 2020; Stander and Broadhurst 2021)
Increased use of renewable energy 5 (Marimuthu etal. 2021; Shrivastava and Vidhi 2020; Stander and Broadhurst 2021)
Ecological protection 2 (Zeng etal. 2023)
Improves ecological quality 2 (Tang etal. 2022)
Reduction of the ecological footprint 3 (Rebbah etal. 2021; Turcotte and Lachance 2023)
Fig. 11 Positive environmental
impact because of the applica-
tion of digital technologies
17%
14%
10%
5%
3%
2%
2%
10%
2%
5%
0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%
Sustainable Development (Protect, restore,…
Reduction of environmental impact
Waste reduction
Water purification
Reduction of the ecological footprint
Air quality monitoring
Ecological protection
Social responsibility
Improves ecological quality
Increased use of renewable energy
Technological advances andtrends inthemining industry: asystematic review
Table 6 Benefits of the application of technologies in the mining industry
Benefits % Manuscripts
Increased productivity 24 (Aguirre-Jofré etal. 2021; Barnewold and Lottermoser 2020; Flores etal. 2020; Gackowiec and
Podobinska-Staniec 2019; Kim etal. 2018; Li etal. 2021, 2022; Lopes etal. 2018; Mtotywa and
Dube 2023; Oncioiu etal. 2019; Ozhigin etal. 2022; Radonjic etal. 2022; Van Hau etal. 2022;
van Wyk and de Villiers 2019; Zulu etal. 2021)
Increased competitiveness 3 (Bi etal. 2022; Mtotywa and Dube 2023)
Cost reduction 24 (Aguirre-Jofré etal. 2021; Barnewold and Lottermoser 2020; Bertoni etal. 2022; Bui etal. 2019;
Gackowiec and Podobinska-Staniec 2019; Li etal. 2022; Lööw etal. 2019; Lopes etal. 2018;
Marimuthu etal. 2021; Oltmanns and Petruska 2023; Oncioiu etal. 2019; Pesa 2022; Radonjic
etal. 2022; Samis and Steen 2020; Samylovskaya etal. 2022)
Occupational safety 25 (Adjiski etal. 2019; Gackowiec and Podobinska-Staniec 2019; Jacksha and Raj 2021; Li etal. 2021;
Liang etal. 2020; Lopes etal. 2018; McNinch etal. 2019; Nguyen etal. 2021; Nguyen and Pham
2019; Oltmanns and Petruska 2023; Ozhigin etal. 2022; Pacheco etal. 2022; Shrivastava and
Vidhi 2020; Stefaniak etal. 2023; Van Hau etal. 2022; van Wyk and de Villiers 2019)
Increased value creation 3 (Lopes etal. 2018; Stander and Broadhurst 2021)
Monitoring of environmental hazards 2 (Adjiski etal. 2019)
Process automation 3 (Aguirre-Jofré etal. 2021; Samylovskaya etal. 2022)
Fulfillment of objectives 6 (Aguirre-Jofré etal. 2021; Kim etal. 2018; Marimuthu etal. 2021; Oncioiu etal. 2019)
Time reduction 3 (Aguirre-Jofré etal. 2021; Stefaniak etal. 2022)
Better communication 5 (Alenezi etal. 2022; Min etal. 2023; Stefaniak etal. 2022)
Better decision making 6 (Bisschoff and Grobbelaar 2022; Evsutin and Meshcheryakov 2020; Newman etal. 2018; Zulu etal.
2021)
Better working conditions 17 (Jacksha and Raj 2021; McNinch etal. 2019; Nguyen etal. 2021; Oltmanns and Petruska 2023;
Ozhigin etal. 2022; Pacheco etal. 2022; Shrivastava and Vidhi 2020; Stefaniak etal. 2022; Tur-
cotte and Lachance 2023; Yousefian etal. 2023; Zulu etal. 2021)
Improved operating efficiency 24 (Gackowiec and Podobinska-Staniec 2019; Li etal. 2023; Liang etal. 2020; Lopes etal. 2018;
McNinch etal. 2019; Min etal. 2023; Newman etal. 2018; Oltmanns and Petruska 2023; Ozhigin
etal. 2022; Pandey and Mishra 2022; Radonjic etal. 2022; Samylovskaya etal. 2022; Stefaniak
etal. 2023; Zarubin etal. 2021; Zulu etal. 2021)
Reliability of information (Evsutin and Meshcheryakov 2020; Min etal. 2023; Samis and Steen 2020; Samylovskaya etal.
2022; Santoro etal. 2022; Stefaniak etal. 2023)
Economic growth (Pandey and Mishra 2022; Pesa 2022; Yousefian etal. 2023; Zulu etal. 2021)
Community engagement (Posleman and Sallan 2019)
Fig. 12 Benefits of the applica-
tion of technologies in the
mining industry
25%
17%
2%
10%
6%
24%
24%
24%
3%
3%
6%
3%
3%
6%
5%
2%
0% 5% 10% 15%20% 25%30%
Occupational safety
Better working conditions
Community engagement
Reliability of information
Better decision making
Increased productivity
Cost reduction
Improved operational efficiency
Process automation
Time reduction
Economic growth
Increased competitiveness
Increased value creation
Fulfilment of objectives
Better communication
Monitoring of environmental hazards
R.O.Flores-Castañeda et al.
economically and environmentally, efficient monitoring
and mitigation of environmental hazards, process automa-
tion for more efficient production, effective achievement of
operational and sustainable goals, reduced production times,
improved communication, more informed decision making,
safer working conditions, increased operational efficiency,
reliability of information supported by advanced data analyt-
ics, fostering economic growth, and enhanced engagement
with local communities through sustainable and responsible
practices. Taken together, these benefits contribute to more
efficient, safer, and sustainable mining Pouresmaieli etal.
(2023) thanks to optimization, autonomous learning, con-
stant monitoring, among others. Undoubtedly the decision
to implement digital technologies involves a thorough and
deep analysis of all that it implies, considering the legisla-
tion and the limitations that may arise during the process
Onifade etal. (2023).
The mining industry is important for the world economy
because it provides the necessary resources to produce goods
and services; however, it is essential to provide job security
to workers because they are the ones who carry out the pro-
cesses inside and outside the mine.
The Table7 shows a matrix detailing in which mining
processes the most used digital technologies are applied and
the benefits obtained.
Conclusions
Manuscripts from 2013 and 2023 have been selected, find-
ing at the beginning 1755, of which 63 manuscripts meet
the inclusion and exclusion criteria, as for the methodology
PRISMA was applied. Regarding the questions posed, the
following results were obtained: First, the digital technolo-
gies applied in the mining industry are: Iot which stands out
because it allows the use of sensors and digital twins, arti-
ficial intelligence (autonomous learning, neural networks,
machine learning, automatic speech recognition (ASR), big
data and robotics), augmented reality, virtual reality, cloud
computing and blockchain. Secondly, it was found that the
process of exploration and extraction (excavation) is where a
greater application of digital technologies is evident because
a key factor is to obtain information about the area and min-
erals to be extracted, another key factor is how to excavate
and extract the minerals efficiently, as well as the processing,
transportation, and closure of the mine. Thirdly, it is impor-
tant to analyze the contribution of digital technologies to
environmental care because there is still time to reverse all
the damage that has been caused by contributing to sustain-
able development, reducing environmental impact, purifying
water and monitoring air quality, reducing waste, promoting
greater use of renewable energy, protecting the ecology and
reducing the ecological footprint as a result of the processes
carried out in the mining industry: increased productiv-
ity, cost reduction, labor safety, better working conditions,
improved operational efficiency and reliability of informa-
tion. In other words, mining companies that adopt digital
technologies will be well positioned to succeed in the future.
Finally, the results of this research will help future
researchers to investigate in which branches of digital tech-
nologies are specifically applied in the mining industry con-
sidering the size and geographical location of the mine, as
well as the type of ore they extract. In addition, considering
the evolution of technology in a changing environment, it
will be possible to consider the application and integration
of the technologies that are being created focused on achiev-
ing a more responsible and technologically advanced mining
industry.
In terms of limitations, a relevant aspect is the invest-
ment required to implement digital technologies, followed
by time, knowledge, resistance to change, geographical
barriers and accessibility to information. However, it is
all part of a transition process that today is necessary for
any company seeking to stay in the market. Finally, mining
companies must create awareness of the working conditions
they offer their workers, as well as focus on environmental
preservation.
The systemic limitations found in the literature review are
as follows: there is a possibility that some relevant studies
have been omitted in the review due to the limited availabil-
ity of specific databases for the mining industry. On the other
hand, the diverse nature of technological advancements in
the mining industry can result in significant heterogeneity
among the included studies, making it difficult to present
quantitative data. As for the specific limitations, there is a
lack of comparative studies in the selected articles, as no
studies were found that directly compare different technolo-
gies, benefits, or approaches in the mining industry, limiting
the review's ability to provide clear recommendations on
which technologies are most effective in different contexts.
Finally, the studies included in the review come from spe-
cific geographical regions or operational contexts, which
limits the generalization of the results to a global level or to
different types of mining operations.
The systematic review process highlights the pivotal role
of the Internet of Things (IoT) in the mining industry, spe-
cifically in the extraction process. The implementation of
IoT allows real-time monitoring of excavation operations,
leading to significant improvements in operational efficiency.
Additionally, IoT contributes to sustainable development
by minimizing negative environmental impact, protecting,
restoring, and promoting the sustainable use of terrestrial
ecosystems. These benefits are crucial for various stakehold-
ers, including mining companies, workers, and local com-
munities, underscoring the importance of IoT in optimizing
the mining industry.
Technological advances andtrends inthemining industry: asystematic review
Table 7 Matrix of digital technologies, mining processes and benefits of their application
Technolo-
gies
Mining industry processes where digital tech-
nologies are being applied
Benefits of the application of technologies in the mining industry
Explo-
ration
Extrac-
tion
(Exca-
vation)
Pro-
cess-
ing
Trans-
porta-
tion
Clos-
ing
Increased
productiv-
ity
Increased
competi-
tiveness
Cost
reduc-
tion
Occu-
pational
safety
Increased
value
creation
Moni-
toring
of envi-
ron-
mental
hazards
Process
automa-
tion
Fulfil-
ment of
objec-
tives
Time
reduc-
tion
Better
com-
muni-
cation
Better
deci-
sion
mak-
ing
Better
work-
ing
condi-
tions
Improved
opera-
tional
efficiency
Relia-
bility of
infor-
mation
Eco-
nomic
growth
Com-
munity
engage-
ment
Internet of
Things
(IoT)
x x x x x x x x x x x x x x x x
Big Data x x x x x x x x x x x
Cloud
comput-
ing
x x x x x x x x x x
Autono-
mous
learn-
ing
x x x x x x x x
Robotics x x x x x x x x x x x x x
Block-
chain
x x x x x x x x x
Neural
net-
works
x x x
Machine
learn-
ing
x x x x x x
Aug-
mented
reality
x x x x x
Virtual
reality
x x x x x
Automatic
Speech
Recog-
nition
(ASR)
x x x x
R.O.Flores-Castañeda et al.
Author contributions All authors contributed to the study conception
and design. Material preparation, data collection and analysis were
performed by [Rosalynn Ornella Flores-Castañeda], [Sandro Olaya-
Cotera], [Máximo López-Porras], [Esther Tarmeño-Juscamaita] and
[Orlando Iparraguirre-Villanueva]. The first draft of the manuscript
was written by [Rosalynn Ornella Flores-Castañeda] and all authors
commented on previous versions of the manuscript. All authors read
and approved the final manuscript.
Funding The authors declare that no funds, grants, or other support
were received during the preparation of thismanuscript.
Declarations
Competing interests The authors have no relevant financial or non-
financial interests to disclose.
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