A Comprehensive Review of Applications of Drone Technology in the Mining Industry

Shahmoradi, Javad; Talebi, Elaheh; Roghanchi, Pedram; Hassanalian, Mostafa

doi:10.3390/drones4030034

Cited by 230 publications

(128 citation statements)

References 94 publications

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“…Using image matching and photogrammetric methods, we can orient the bunch of images along both the horizontal and height axes. Thus, we obtain volume data in a relative coordinate system, which is oriented into the national coordinate system with the help of classical or GNSS technologies [4]. [4].…”

Section: Alternative Observation Methodsmentioning

confidence: 99%

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Monitoring after the conclusion of mining works

Hribar

Pečolar

Vižintin

2020

Materials and Geoenvironment

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After mining works are completed and the mine is permanently closed, the holder of the mining rights must carry out monitoring in accordance with the applicable legislation and for the purpose of controlling the extraction area. This includes monitoring of the changes that have occurred during the process of mining, both on the surface and below it. This article presents an example of a monitoring program after the mining works are completed. The extraction of raw mineral material in an underground mine results in various impacts on the surface and underground space. The areas or segments of monitoring are divided into two parts in this article: The underground part includes monitoring of the geomechanical, climatic, and hydrogeological changes, while monitoring on the surface requires special attention to be paid to the stability conditions of the surface above old mine works and hydrogeological conditions in the area above the extraction or impact area. A practical example of the monitoring program that needs to be made when a mine closes is given in the article. The program covers areas, presents the ways and methods of measurement, as well as reporting of the measurements. The analysis procedure of already existing measurements, which need to be analyzed and included in the preparation of the monitoring program, is also presented.

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Section: Alternative Observation Methodsmentioning

confidence: 99%

“…Thus, we obtain volume data in a relative coordinate system, which is oriented into the national coordinate system with the help of classical or GNSS technologies [4]. [4]. Surface modeling is performed using the geostatic surface adjustment method.…”

Section: Alternative Observation Methodsmentioning

confidence: 99%

Monitoring after the conclusion of mining works

Hribar

Pečolar

Vižintin

2020

Materials and Geoenvironment

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“…Salah satu cara yang dapat dilakukan dengan bantuan Unamanned Aerial Vehicle (UAV) atau pesawat tanpa awak. UAV mampu terbang dengan kendali remote control maupun terbang secara autonomouos (Shahmoradi, 2020).…”

Section: Pendahuluanunclassified

Super Resolution pada Citra Udara menggunakan Convolutional Neural Network

2021

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ABSTRAKBencana di Indonesia didominasi oleh bencana hidrometeorologi yang mengakibatkan kerusakan dalam skala besar. Melalui pemetaan, penanganan yang menyeluruh dapat dilakukan guna membantu analisa dan penindakan selanjutnya. Unmanned Aerial Vehicle (UAV) dapat digunakan sebagai alat bantu pemetaan dari udara. Namun, karena faktor kamera maupun perangkat pengolah citra yang tidak memenuhi spesifikasi, hasilnya menjadi kurang informatif. Penelitian ini mengusulkan Super Resolution pada citra udara berbasis Convolutional Neural Network (CNN) dengan model DCSCN. Model terdiri atas Feature Extraction Network untuk mengekstraksi ciri citra, dan Reconstruction Network untuk merekonstruksi citra. Performa DCSCN dibandingkan dengan Super Resolution CNN (SRCNN). Eksperimen dilakukan pada dataset Set5 dengan nilai scale factor 2, 3 dan 4. Secara berurutan SRCNN menghasilkan nilai PSNR dan SSIM sebesar 36.66 dB / 0.9542, 32.75 dB / 0.9090 dan 30.49 dB / 0.8628. Performa DCSCN meningkat menjadi 37.614dB / 0.9588, 33.86 dB / 0.9225 dan 31.48 dB / 0.8851.Kata kunci: citra udara, deep learning, super resolution ABSTRACTDisasters in Indonesia are dominated by hydrometeorological disasters, which cause large-scale damage. Through mapping, comprehensive handling can be done to help the analysis and subsequent action. Unmanned Aerial Vehicle (UAV) can be used as an aerial mapping tool. However, due to the camera and image processing devices that do not meet specifications, the results are less informative. This research proposes Super Resolution on aerial imagery based on Convolutional Neural Network (CNN) with the DCSCN model. The model consists of Feature Extraction Network for extracting image features and Reconstruction Network for reconstructing images. DCSCN's performance is compared to CNN Super Resolution (SRCNN). Experiments were carried out on the Set5 dataset with scale factor values 2, 3, and 4. The SRCNN sequentially produced PSNR and SSIM values of 36.66dB / 0.9542, 32.75dB / 0.9090 and 30.49dB / 0.8628. DCSCN's performance increased to 37,614dB / 0.9588, 33.86dB / 0.9225 and 31.48dB / 0.8851.Keywords: aerial imagery, deep learning, super resolution

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“…CRP is the technique to define the coordinates of the points of digital images in a local coordinate system on pictures. Moreover, recently RFID systems were helpful in zoning danger areas and alarming the dispatch center, while drone technologies adapted for operating in narrow and confined spaces such as mine excavations are used for gas monitoring, point-cloud scanning, surveillance and visual reconnaissance of inaccessible areas, among other applications (Shahmoradi et al, 2020b).…”

Section: Global Positioning System and Coordinationmentioning

confidence: 99%

A Comprehensive Review on Internet of Things (IoT) and its Implications in the Mining Industry

Molaei

Rahimi

Siavoshi

et al. 2020

American Journal of Engineering and Applied Sciences

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The integration of computer-based technologies interacting with industrial machines or home appliances through an interconnected network, for teleoperation, workflow control, switching to autonomous mode, or collecting data automatically using a variety of sensors, is known as Internet of Things (IoT). When applied inside an industrial context, it is possible to immediately benefit from the analytics obtained, contributing to process optimization, machine health, the safety of workers and asset management. IoT can assist real-time platforms in remotely monitoring and operating a complex production system with minimal intervention of humans. Hence it can be beneficial for hazardous industries, such as mining, by increasing the safety of personnel and equipment while reducing operation costs. An ideal smart automated mine could potentially be achievable by gradually taking advantage of IoT. Currently, different sensors are used in mine-related activities, such as geophones in exploration and blast control, piezometers in dewatering and toxic gas detectors in working frontlines. However, a fully integrated automated system is challenging in practice due to infrastructural limitations in communication, data management and storage. Moreover, the tendency of mining companies to continue with traditional methods instead of relying on untested novel techniques decelerates this progress. In this study, the adaptability of the mining industry to IoT systems and its current development is reviewed. Significant challenges of this progress are investigated and recommendations to develop a comprehensive model suited for different mining sections such as exploration, operation and safety considering flexible technologies such as Wireless Sensor Networks and the introduction of Global Data Management.

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A Comprehensive Review of Applications of Drone Technology in the Mining Industry

Cited by 230 publications

References 94 publications

Monitoring after the conclusion of mining works

Monitoring after the conclusion of mining works

Super Resolution pada Citra Udara menggunakan Convolutional Neural Network

A Comprehensive Review on Internet of Things (IoT) and its Implications in the Mining Industry

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