The mining industry is one of the most significant contributors to a country’s GDP. The importance of mining industry can be understood by the fact China the second largest and one of the fastest growing economy of the world owns the world’s largest mining industries. Additionally, the fact that mining contributes around 8.5% in Australia’s GDP every year (Maslyuk & Dharmaratna, 2013). However, the scenario was not the same and had seen significant up and downs which is shown in the image as follows:
It is evident from the graph shown above that post-2011 the mining industry had become less productive for Australia. It is not just the scenario of the considered country the condition had worsen for the mining industry globally, and in that dire situation, IoT was gaining the much-deserved attention. After the introduction of the subject (IoT) the scenario started to change which is visible in the graph. IoT is the system which connects human, machine and services with the objective of streamlining the flow of data, enable new opportunities and real-time decision makings. The table following shows the core benefits offered by the subject in the mining industry.
|
Advancement in automation technique |
It creates a virtual network of the devices that are used in the operations, enabling them to operate simultaneously. |
|
Enhanced mining safety |
It eliminates the risk of injuries and collapsing of unstable shafts that are caused by mining trucks by taking account of real-time data and predicting the possible areas where undesirable circumstances make occur. |
|
Assists in maintenance |
The subject offers advantage of auto-detecting the faulty part of the equipment before maintenance or repair work which offers safety and saves extra effort and time. |
|
Reduces expenditure |
It reduces the energy expenditure in developing and maintaining the site. |
Table 1: Core benefits of IoT in Mining Industry
(Source: Created by Author)
The IoT in the mining industry also offers other benefits. However, the deemed technology even offers some challenges to the mining industry. The challenges are associated with the implementation of the deemed technology and developing skills among the mining stakeholders over using the IoT based equipment. The impact that the subject has cited over the mining industry will also be a part of the discussion in the paper to be developed. To achieve the objectives of the paper, the paper will review the literature works that had been assessed in the past over the subject and the mining industry. After assessing the literature different methodologies will be determined from which the most suitable methodology will be selected to assist in achieving the objective. The paper will even offer justification statements to validate the selection. Finally, the findings will be evaluated before concluding the paper.
IoT Challenges and solutions in Industry:
Breivold & Sandstorm, (2015) in the reviewed article has attempted at evaluating challenges that IoT offers in the organisational operations and potential solutions to tackle the identified challenges. The authors have started the paper by introducing the IoT and what is the role that it plays in the industrial automation. Following the introduction of the IoT and its role, the paper shifted its focus to the challenges, which were identified as the security, privacy, scalability, and interoperability. Additionally, verification of the timing & determinism, reliability & availability, safety & criticality, interoperability and others. Following the challenges, the paper offered the potential measures to manage the challenges before summarising the paper. On the evaluation of the paper, it is evident that the authors put a lot of effort and practise before they started working on the paper. The challenges included as part of the paper are divided into categories according to their viability, which enhances the understanding of the subject. However, the paper would have been more reliable, if it offered graphs and stats to support the claims made by the authors. Though, after evaluating the article, the author of the proposed paper has identified the challenges of IoT in the industries and based upon that devise the platform to pursue the objective of identifying the impact of IoT in the mining industry.
Reddy & Lakshmi, (2015), offered a prototype of IoT system to monitor and refer safety measures to the safety workers of the mining industries. The system has been designed to take input from different sensors installed in different sections of the mining industry. The inputs are analysed in the microcontrollers of the discussed system and if a dire situation is determined then an alert is distributed in the wrong section through the web servers and Wi-Fi communication. The Wi-Fi communication is enabled by linking the mining worker’s wearables and the web servers. The paper has further discussed results and cases developed from implementing the developed system in a real-world scenario. The results cite that the system is efficient in a real-world scenario and can be of great assistance in preventing casualties in underground mining which has been a matter of concern for a long time in the mining sector. Hence, the review of the literature can be emphasised to conclude that the developed report will be of great vitality in the underground mining and can be implemented in the real-life scenario. The presentation of the report is also excellent in quality, and appropriate referencing makes it more reliable. Additionally, reviewing the article has made the author of the proposed paper aware of the threats that are associated with the mining especially underground mining which will consist of high vitality in concluding the proposed report.
Elias & Espinoza, (2017) in the reviewed article have stated that the new technological wave that is transforming the industrial operation is bringing the end to the industrial revolution and initiating the technological revolution. The authors have ‘informed’ the mining industry that it is time they adopt disruptive technologies if the latter wishes to maintain sustainability with other sectors. Following the introduction, the reviewed article offers a detailed analysis of the data and stats of the industries and their productivity ratio in the past decade. Starting from the steam engine to the currently equipped mechanised process for organisational operations all has been highlighted by the authors. The following sections discuss the resource efficiency and how equipping technology in mining industries can transform the destructive industry to a creative destruction domain. Before concluding the paper, a brief discussion over the advancement offered by the technology in the mining sector has been discussed by the authors. In conclusion, it can be stated that the reviewed article is knowledgeable and guiding with all those figure and stats. Additionally, the critical thinking approach adopted by the authors to pursue the objective of the paper is a delight for the readers. The author of the proposed report after assessing the report is now able to understand the changes that the technology has and further can bring in the mining sector.
Eliasson et al., (2013), has focused on stakeholder’s safety in the mining industry from shotcrete and rock bolts. The safety concern is so high that even though the mining sector is booming, then also hiring of employees is proving to be difficult for the industries associated with the mining. The authors have recommended that instead of adopting different measures for the employees, the rock bolts should be made smart. The authors also recommended that the deemed objective can be achieved by accepting assistance from the IoT. The authors have quoted that adopting the recommended measure will prevent any casualties from occurring by alarming the labours and machinery of rock bolts status through real-time monitoring. The paper adopted practical implementation of the stated measure in the real world, to determine the results and it was positive. Finally, the review of the paper can be emphasised to state that authors have offered a real-world life-saving measure which if adopted in the mining industry can reduce or even nullify the safety concerns. No, negative side of the reviewed article has been identified. Instead, it has even offered pathways for future research. The author of the proposed paper has also been benefitted with a real-world example of the benefit offered by the IoT in the mining sector.
Sganzerla, Sexias & Conti, (2016), has focused on the mining industry and how they are adopting new technological business model to earn sustainability. The authors in the reviewed article have focused on detailing three points: firstly, defining digital transformation (DT), the impact of DT on mining industries and what measures mining industries can adapt to utilise the DT to its full extent. The authors offer a detailed analysis of the three critical points of interest of the article and have elaborately explained it. Additionally, the article has even offered potential measures that can enable the mining industry to achieve the maximum potentiality of the digital transformation for its organisational operations. In the conclusion of the paper, a summarised form of all the findings from the research work has been listed which will enable the readers to understand the whole concept of the journal without diving deep in the same. The reviewed paper is a detailed and knowledge-offering and has left minimal scope of error. However, the only limitation of the paper is its theoretical approach rather than offering any real-life experience of the mining industry. Reviewing the article has enabled the author of the proposed paper to understand the significant changes that IoT can bring in the mining industries along with the change and challenges that are associated with IOT (DT) in the mining industry.
Xu, He & Li, (2014), were motivated to pursue the reviewed literature by witnessing the broad domain of the industrial application offered by the IoT in the industries. To achieve their objective, the authors have attempted at measuring the progress of the subject in industries. The understanding of the subject has been developed by reviewing the data from the past literary work on the same subject along with the trends and challenges in the research. The paper has even summarised the “current state-of-the-art of IoT in industries systematically.”. The reviewed article has been distributed in multiple sections to enhance the understanding of the report. The paper has even offered section to relevant to the challenges and future trends that may influence the subject in the industrial role. Finally, the report has been summarised to add up all the findings through the secondary research method and critical thinking. The report is well presented. However, it is also elaborate and even offers no new idea that has not been discussed in the above-reviewed articles. Hence, it can be emphasised to conclude that new assistance can be taken from the discussed article that already had not been taken from the earlier reviewed work. Though, it can act as a verification review for the above-collected data.
Ravindran, Yomas &Jubin Sebastian (2015) has discussed the security issues that may arise due to the implementation of the IoT. The discussed article has even taken account of the possible remedy for the security issues that may arise due to the IoT in a sector. The reason for the selection of the discussed journal as part of the literature review lays on the fact that evaluating the journal will offer the author of the proposed report an idea about the managing the changes related to security in the mining industry after IoT’s implementation. To achieve the suitable security measures for the IoT infrastructure in the mining sector the authors have offered an underlying security architecture which they claim can help make the IoT network secure. The reviewed article does discuss an essential aspect of the IoT implementation in the mining industry. However, the journal had been kept very brief, so not much clarity is available over the dependency of the proposed architecture which is a major drawback. Additionally, the lack of the practical implementation of the model in real-life experience raises question over the feasibility of the paper. The only significant advantage of the paper can be stated that it had discussed a much-needed factor associated with the IoT.
Fekete, (2015) was motivated to pursue the reviewed article after witnessing the decreasing the productivity of the mining industry. The author associated reason for the decreasing productivity with the changing market and failure of the mining sector to cope up with the technological advancement of other sectors. The discussion of the paper had been laid around the big data analysis of the mining data collected from through the sensors from different mining sections. The paper has followed primary qualitative data collection method to derive the conclusion. Additionally, necessary case studies have been provided to support the collected evidence and proposed a model to earn competitive advantage. The reviewed article is very well presented document which stayed true to its objective while offering the readers an idea about how IoT can offer competitive advantage to an organisation.
According to Sun, Zhang & Li (2012), tailing disposal is one of the most crucial operations of the mining sector. However, it is also one of the cause of multiple accidents in the discussed sector recently. Hence, taking motivation from the same, the authors devised a model called as “Tailings dam monitoring and pre-alarm system (TDMPAS)” to enhance the safety of the tailings disposal. The devised model takes assistance of the IoT and CC (Cloud computing) collaboratively known as CoT (Cloud of things). The authors claim it to be a hugely successful and efficient system which has been tested in multiple mines before presenting the discussed report. The figures and stats offered by the paper support the claims made by the authors, and the architecture of the system is even suitable for the practical implementation. Additionally, no shortcomings were identified in the presentation or detailing of the paper. The revised paper will also offer its assistance in understanding the enhanced capability that IoT earns when integrated with the CC.
Sharma, Sharma & Gupta, (2017) in the discussed article has focused on the role that the discussed technology plays in the optimisation of safety, profit and production in the mining sector. The authors have listed the core advantage of the discussed technology, following just after the introducing the paper. The authors have followed a secondary data collection approach to validate the objective of the discussed article. The primary focus of the paper has been kept limited to the coal mining rather than underground or metal and oil mining or overall mining sector. The paper even offers a four-layered architecture to be implemented in the coal mine to maintain safety and productivity levels and in the procedure sustaining the organisational profit. The implementation process along with the role it will play is also a part of the reviewed journal before concluding it. Like the above-reviewed article, the considered article has discussed safety and benefits of the IoT in the mining industry. However, it should be noted that the paper has also taken consideration of the commercial benefit of the mining industry which no one of the above-discussed articles has done. Reviewing the journal has inspired the author of the proposed paper to take consideration of the commercial vitality of the IoT in the mining industry.
The articles discussed above offered various significant intel about the IoT and the role that it plays in the mining industries. Some of the reviewed articles has even offered some methodologies that can be of great significance in managing and maintaining the IoT in the mining industry while enhancing the capabilities of the latter. The deemed section has been devised to cite light on the identified methodologies and based upon them the author will attempt to offer the most suitable methodology. Following that the gap in the literary work will be evaluated for the IoT in mining industry.
Rock bolts and other similar devices are used for monitoring the rock stress and seismic activities. It has reduced the risk associated with the mining industry however, the reduction of risk is considerably moderate and hence, Eliasson et al., (2013) offered a framework for the smart rock bolt. They proposed that integrating the rock bolts with the IoT will assist in real-time monitoring and in the process detect anomalies early which can prove to be life-saving. The image below shows the framework proposed by the authors.
The “Intelligent rock bolt consists of several components – a sensor board and a Mulle v6.2 wireless sensor node” (Eliasson et al., 2013). The Mulle operates on the Contiki O.S while communication process id done with assistance from CoAP and 6LoWPAN. The results of practical implementation of the deemed framework reveals that the framework does offer some reliability. However, there are certain challenges that need to be addressed before it is declared suitable and worth implementing in the real-world mining industry. Hence, in conclusion it can be stated that the discussed framework is worth the research and investment because it can pave way for a fast and secure mining industry.
Reddy & Lakshmi, (2015) has proposed a system for the effective monitoring of the process in underground mining. The proposed method includes a wearable helmet that is equipped with multiple sensors such as the fire, humidity, natural gas sensor, light, temperature and others sensors. It also includes MEMS Accelerometer along with ESP8266 MODULE modem and other necessary devices which are evident in the diagram shown below:
The module at the miner’s end indicates any abnormalities to the core system through alerts enabling the operators to capture real-time data. The developers also evaluated the module in real-life scenario to determine the functionality and the retails have been listed in the report. The graphs that are listed cites positive response for the users and can be emphasised to state that the system can be implemented in the underground mining and will offer positive results. The developers have also offered options to clear the previous feed to limit the data load on the servers. The temperature and humidity graphs have been attached to cite reliability for the claimed facts.
Unlike, the above discussed methodologies Ravindran, Yomas &Jubin Sebastian, (2015) has not offered any framework or module for technological assistance through IoT in the mining industry. Instead they have opted to highlight the techniques that can assist in omitting the security threats of the mining industry that are related to the IoT. The discussed methodology has divided the security concerns of the IoT in three layers namely; application layer, sensing layer and transport layer. The sensing layer is consisting of sensors, GPS & other sensory devices and is mostly concerned with RIFD security. The authors of the discussed methodology states that “Physical methods or code mechanisms or a combination of both the methods are used for providing the RFID security.”. Transport layer concerns with the internet, cloud computing and other communicative means. It is the most volatile in terms of all the layers and hence the recommendations have been made to keep the transported data encrypted. Additionally, adopting MFA (multifactor authentication) has also been recommended to sustain the security. The application layer contributes of the interfacing applications {APIs (Application program interfaces) & UIs (user interfaces)}. The authors have recommended that the security of the application layer can be ensured by ‘security-focused code review’ where the security capabilities of the codes are audited and ‘rigorous penetration testing’ where the systems are attacked to test their security strength.
The author, Fekete, (2015), in the discussed methodology has offered a generalised structure for the IoT and big data in the mining industry. The methodology offered by the author is for the predictive maintenance in the mining sector. The discussed model has been inspired by the Lewin’s model which works on three layers namely; unfreeze-move-freeze. The author has modified the model to be suitable for the IoT issues. Just like the Lewin’s model the discussed model states that the first step would be unfreeze the current technology and assess the need of technological advancement. The second step would be adding of sensors and much need IoT instruments & tools to the mining equipment before finally freezing the system until further needed. The discussed model is a chain process which must be repeated periodically to ensure the proper functioning of the organisational operations. The deemed model is more suitable for the corporate’s perception rather than security or any other IoT’s perception. It also assists in managing the changes and the crucial situations that may arise due to the adoption of the subject in the mining industry. Hence, in conclusion it can be stated that the deemed technology integrated with other model can offer a sustainable competitive advantage in the mining industry.
Failure of dams is one of the most crucial concern for the mining industry. The deemed scenario has even resulted in many catastrophic incidents and hence, the authors have offered a model to avoid such undesired results. TDMPAS (‘tailing dam monitoring and pre-alarm system’) framework was designed to avoid any incidents from occurring by pre-intimating the stakeholders. The framework works with assistance of the cloud computing (CC) and IoT for real-time data monitoring of dam deformation, saturated line, dry beach elevation and dam deformation (Sun, Zhang & Li, 2012). The discussed framework is a three-layered system inclusive of sensor layer, application layer and the network layer. The sensor layer like the above discussed methodologies sense the real-time data and transport it through the network layer to the core system where the application layer evaluates it and responds accordingly to the field workers. The response from the system is in form of alarm that informs the field worker of the next step that should take. The discussed methodology can be of great assistance in the mining industry and can save a lot of life in the process. The diagram attached below shows the framework along with its core components.
It is evident from the discussion above that the discussed methodologies are developed for individual sections of the mining industry. One of them has taken consideration of the underground mining while other has offered safety and security measure for the tailing dam. Eliasson et al., (2013), has offered enhancement of the mining security by adopting smart rock bolt. Ravindran, Yomas &Jubin Sebastian (2015), has offered a generalised solution while Reddy & Lakshmi, (2015) has offered methodology for methodology for monitoring of overall mining. Hence, it can be stated that the methodology offered by Reddy & Lakshmi, (2015) is the most suitable methodology out of all the methodologies. However, the discussed methodology only consists of the monitoring services and no proper recommendation has been made for the security concerns of the mining industry.
The discussion above reveals that the though the discussed methodologies are suitable for individual sections or in-general monitoring of the mining industry. Hence, it is recommended that an integrated model for the safety and monitoring of the mining industry would be the best suited methodology. The integrated methodology will be based upon all the five methodologies that had been discussed above. The proposed methodology will be outlined based on the guidelines offered by (Ravindran, Yomas &Jubin Sebastian, 2015) and (Fekete, 2015). While the former methodology will offer guideline for the security, the latter will assist in maintenance and in the process earn a competitive advantage in the mining industry. The model proposed by Eliasson et al., (2013) can be used for planting the IoT sensors in place without consuming any additional place or creating difficulties for the field labours. The framework offered by (Sun, Zhang & Li, 2012) will be used to broadcast a generalised alarm for the worker in dire situation. Finally, all of the process will be integrated in the wearable proposed by (Reddy & Lakshmi, 2015). The reason for proposing the wearable into the methodology when a generalised alarm has already been introduced is because at a particular instance, a problem may arise at a specific location and it would not be feasible to halt the whole operation of that whole section or industry. Hence, the wearable will inform the workers of that specific area where the anomaly has been detected letting the other workers work without interruption. However, during certain dire situations, broadcasting the message of threat is not advisable because such huge broadcast may affect the network and the message may not be received by every worker which could have catastrophic results. Hence, the alarming system has been recommended as the part of the methodology. Finally, it can be stated that the integrated methodology will be suitable for security of the mining industry with assistance of IoT and will also enable the organisation to earn competitive advantage.
Conclusion:
The evaluation of the IoT in the mining industry have revealed that the former can prove to be of significant benefit in the latter and hence, has emerged as one of the most popular choice. Adoption of the IoT along with the security benefit also offers competitive advantage to the mining industry. However, the risk involved in the mining sector can be greatly minimised by adoption of the IoT. Dams and underground mining which are the most crucial section are the most benefitted sections on adoption of the deemed technology. The paper has also reviewed different literary works that have been assessed on the role and impact of IoT in the mining industry. Different models, frameworks and methods have been identified in the process of reviewing of the literary work which then had been compared to analysed the best suited methodology. On evaluation, it has been identified that all of the methodology were lacking in one sector or other and hence, an integrated method had been proposed which can suit the requirements of the mining industry. Hence, in conclusion, it can be sated that IoT in mining industry is a desirable choice because of the benefits it offer.
8412.0 – Mineral and Petroleum Exploration, Australia, Dec 2017. (2017). Abs.gov.au. Retrieved 1 April 2018, from https://www.abs.gov.au/ausstats/[email protected]/mf/8412.0
Aguilar, R. (2016). Putting the human factor at the heart of health & safety. Aluminium International Today, 28(6), 39.
Arshad, R., Zahoor, S., Shah, M. A., Wahid, A., & Yu, H. (2017). Green IoT: An Investigation on Energy Saving Practices for 2020 and Beyond. IEEE Access, 5, 15667-15681.
Barrie, G., Whyte, A., & Bell, J. (2017, March). IoT security: challenges and solutions for mining. In Proceedings of the Second International Conference on Internet of things and Cloud Computing (p. 38). ACM.
Breivold, H. P., & Sandström, K. (2015, December). Internet of Things for Industrial Automation–Challenges and Technical Solutions. In Data Science and Data Intensive Systems (DSDIS), 2015 IEEE International Conference on (pp. 532-539). IEEE.
Chen, F., Deng, P., Wan, J., Zhang, D., Vasilakos, A. V., & Rong, X. (2015). Data mining for the internet of things: literature review and challenges. International Journal of Distributed Sensor Networks, 11(8), 431047.
Da Xu, L., He, W., & Li, S. (2014). Internet of things in industries: A survey. IEEE Transactions on industrial informatics, 10(4), 2233-2243.
Delsing, J., Eliasson, J., Punal, P., & Gebart, J. (2015). The IoT rockbolt. In IoT conference: 26/10/2015-28/10/2015.
Elias, I., & Espinoza, J. (2017). Disrupting technologies and their impact in the Mining & Metals sector.
Eliasson, J., Delsing, J., Raayatinezhad, A., & Kyusakov, R. (2013, February). A SOA-based framework for integration of intelligent rock bolts with internet of things. In Industrial Technology (ICIT), 2013 IEEE International Conference on(pp. 1962-1967). IEEE.
Fekete, J. (2015). BIG DATA IN MINING OPERATIONS. Studenttheses.cbs.dk. Retrieved 2 April 2018, from https://studenttheses.cbs.dk/bitstream/handle/10417/5945/jonatan_adam_fekete.pdf?sequence=1
Garcia, L. G. U., Almeida, E. P., Barbosa, V. S., Caldwell, G., Rodriguez, I., Lima, H., … & Mogensen, P. (2016). Mission-critical mobile broadband communications in open-pit mines. IEEE Communications Magazine, 54(4), 62-69.
Gnoni, M. G., Elia, V., & Bragatto, P. A. (2016, December). An IOT-based system to prevent injuries in assembly line production systems. In Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on(pp. 1889-1892). IEEE.
Hwang, Y. M., Kim, M. G., & Rho, J. J. (2016). Understanding Internet of Things (IoT) diffusion: Focusing on value configuration of RFID and sensors in business cases (2008–2012). Information development, 32(4), 969-985.
Jacobs, J., & Webber-Youngman, R. C. W. (2017). A technology map to facilitate the process of mine modernization throughout the mining cycle. Journal of the Southern African Institute of Mining and Metallurgy, 117(7), 636-648.
Jung, J., Baek, J., & Choi, Y. (2016). Analysis of Features and Applications of Bluetooth Beacon Technology for Utilization in the Mining and Construction Industries. Tunnel and Underground Space, 26(3), 143-153.
Kaur, J., & Kaur, K. (2016, March). Availing Internet of Things in Industrial decision making—A survey. In Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on (pp. 2164-2168). IEEE.
Kiziroglou, M. E., Boyle, D. E., Yeatman, E. M., & Cilliers, J. J. (2017). Opportunities for sensing systems in mining. IEEE Transactions on Industrial Informatics, 13(1), 278-286.
Lee, C. K. M., Yeung, C. L., & Cheng, M. N. (2015, December). Research on IoT based cyber physical system for industrial big data analytics. In Industrial Engineering and Engineering Management (IEEM), 2015 IEEE International Conference on (pp. 1855-1859). IEEE.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440.
Li, G. (2015). WSN Data Acquistion System for Mobile Service Based on IoT Gateway. Metallurgical & Mining Industry, (6).
Lodewijks, G., Li, W., Pang, Y., & Jiang, X. (2016, September). An application of the IoT in belt conveyor systems. In International Conference on Internet and Distributed Computing Systems (pp. 340-351). Springer, Cham.
Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(05), 164.
Maslyuk, S., & Dharmaratna, D. (2013). Impact of shocks on Australian coal mining. In Global Energy Policy and Security (pp. 231-255). Springer, London.
Nickels, L. (2016). Additive manufacturing: A user’s guide. Metal Powder Report, 71(2), 100-105.
Nikitenko, M. S., Malakhov, Y. V., Neogi, B., Chakraborty, P., & Banerjee, D. (2017, September). Robotic complex for the development of thick steeply-inclined coal seams and ore deposits. In IOP Conference Series: Earth and Environmental Science (Vol. 84, No. 1, p. 012002). IOP Publishing.
Ohno, H., Nuss, P., Chen, W. Q., & Graedel, T. E. (2016). Deriving the metal and alloy networks of modern technology. Environmental science & technology, 50(7), 4082-4090.
Ravindran, R., Yomas, J., & Jubin Sebastian, E. (2015). IoT: A Review on Security Issues and Measures. International Journal of Engineering Science and Technology, 5(6), 348-351.
Reddy, G. P., & Lakshmi, M. V. (2015). IOT in Mines for Safety and Efficient Monitoring. International Journal for Advanced Research in Computer Engineering & Technology, 4(11).
Rogers, W. P., Nelson, M. G., Richins, A., & Hodgson, A. (2017). Data Management Best Practices of Complex Socio-technical Systems: A Review of US Mining Safety and Health Management. Geo-Resources Environment and Engineering (GREE), 2, 83-88.
Sganzerla, C., Seixas, C., & Conti, A. (2016). Disruptive innovation in digital mining. Procedia Engineering, 138, 64-71.
Sharma, A., Sharma, A., & Gupta, S. (2017). IoT in MINING: A Review. International Journal Of Electronics, Electrical And Computational System, 6(2), 1-8. Retrieved from https://academicscience.co.in/admin/resources/project/paper/f201702171487306044.pdf
Sindhu, S., Subashree, J., Suganthi, J., Vinodhini, M., & Umamaheswari, R. (2017). Coal Mining Safety using IoT. Imperial Journal of Interdisciplinary Research, 3(3).
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.
Wessels, C. H. (2017). To IOT or not IOT: a critical analysis of the key legal considerations applicable in internet of things of implementations in the mining industry (Doctoral dissertation, University of Pretoria).
Wu, T., Zhang, Y., Chen, M., Yan, S., Yang, X., & Xiong, Y. (2017). Review for GGD Intelligent Mining Technology. DEStech Transactions on Computer Science and Engineering, (icitia).
Zafrilla, J. E. (2014). The mining industry under the thumb of politicians: the environmental consequences of the Spanish Coal Decree. Journal of cleaner production, 84, 715-722.
Zeman, K., Masek, P., Krejci, J., Ometov, A., Hosek, J., Andreev, S., & Kroepfl, F. (2017, May). Wireless M-BUS in Industrial IoT: Technology Overview and Prototype Implementation. In European Wireless 2017; 23th European Wireless Conference; Proceedings of (pp. 1-6). VDE.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download