Slope stability monitoring system based on the ORLPStarNET IoT platform

Jump To References Section

Authors

  • ,IN

DOI:

https://doi.org/10.18311/jmmf/2022/30443

Keywords:

Slope stability, internet of things, opencast mine, sensor node, prediction interval based woodpecker mating algorithm (PI-WMA), optimal routing low power star topology networking (ORLPStarNet), balanced vector sparrow search algorithm (BVSSA)

Abstract

A promising system for mining industries is deemed as a slope monitoring system (SMS). Additional benefits are possessed by the progression of wireless sensor network (WSN) along with Internet of Things (IoT) for real-time SMS. For observing slope failure (SF) in opencast mines (OCM), a low power, long-range (LoRa), along with an energyeffective solution are suitable. The mine officials along with workers become poorer as they could not have an enhanced smart mine monitoring system owing to severe environmental conditions of mines. For overcoming the existing challenge, a slope stability (SS) monitoring system is created by the work centered on the optimal routing low power star topology networking (ORLPStarNet) IoT platform. Optimal nodes are chosen by the work in a heterogeneous environment utilizing the prediction interval based Woodpecker Mating Algorithm (PI-WMA) technique for avoiding high energy consumption, storage limitation, regular disconnections, and limited bandwidth to gather the slope data. High throughput is attained with the selection of nodes followed by ORLPStarNet gateway networking. Then, the optimal routing of the path is performed utilizing balanced vector sparrow search algorithm (BVSSA) for data transfer. The problems linked with coverage, routing, cost, and loss of data are overcome by the developed gateway networking. Lastly, the data is saved into the IoT Cloud server. As of the server, the data is accessed by the mine officers, and the SS is monitored by them. For detecting slope collapse, the proposed framework system assists in examining the continual monitoring of the deformation, deformation rate (DR), along with inverse-velocity trends as revealed by the experimental analysis. Concerning throughput, the proposed one stays better when analogized to prevailing methods.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Downloads

Published

2022-06-10

How to Cite

Srikanth, B. (2022). Slope stability monitoring system based on the ORLPStarNET IoT platform. Journal of Mines, Metals and Fuels, 70(3), 124–128. https://doi.org/10.18311/jmmf/2022/30443

Issue

Section

Articles
Received 2022-06-10
Accepted 2022-06-10
Published 2022-06-10

 

References

Xuan-nam Bui, Hoang nguyen, Yosoonchoi, Trungnguyen-thoi, Jian Zhouand JieDou, (2020): “Prediction of slope failure in openpit mines using a novel hybrid artificial intelligence model based on decision tree and evolution algorithm”, Scientific Reports, vol.10, pp.1-17.

Xiliang Zhang, Hoang Nguyen, Xuan-Nam Bui, Quang- Hieu Tran, Dinh-An Nguyen, Dieu Tien Bui and Hossein Moayedi, (2019): “Novel soft computing model for predicting blast-induced ground vibration in open-pit mines based on particle swarm optimization and XGBoost”, Natural Resources Research, vol. 29, no. 9, pp. 711-721.

Rybin V. V, Konstantinov K. N and Kalyuzhny A. S, (2019): “Integrated approach to slope stability estimation in deep open pit mines”, Eurasian Mining, vol. 2019, no.2, pp. 23-26.

Prashanth Ragam and Nimaje D. S, (2019): “Performance evaluation of LoRa LPWAN technology for IoT-based blast-induced ground vibration system”, Journal of Measurements in Engineering, vol. 7, no. 3, pp. 119-133.

Ankit Singh, Dheeraj Kumar and Jurgen Hotzel, (2018): “IoT based information and communication system for enhancing underground mines safety and productivity genesis, taxonomy and open issues”, Ad Hoc Networks, vol. 78, pp. 115-129.

Zhigang Tao, Mengnan Li, Chun Zhu, Manchao He, Xiaohui Zheng and Shibo Yu, (2018): “Analysis of the critical safety thickness for pretreatment of mined-out areas underlying the final slopes of open-pit mines and the effects of treatment”, Shock and Vibration, Doi: 10.1155/2018/1306535.

Jiandong Huang, Tianhong Duan, Yawei Lei and Mahdi Hasanipanah, (2020): “Finite element modeling for the antivibration pavement used to improve the slope stability of the open-pit mine”, Shock and Vibration, Doi: 10.1155/2020/6650780.

Zebarjadi Dana H, KhalooKakaie R, Rafiee R and YarahmadiBafghi A. R, (2018): “Effects of geometrical and geomechanical properties on slope stability of open-pit mines using 2D and 3D finite difference methods”, Journal of Mining and Environment, vol. 9, no. 4, pp. 941-957.

Romer C and Ferentinou M, (2019): “Numerical investigations of rock bridge effect on open pit slope stability”, Journal of Rock Mechanics and Geotechnical Engineering, Doi: 10.1016/j.jrmge. 2019.03.006.

Sai CharithaVemulapalli and Shashi Mesapam, (2021): “Slope stability analysis for mine hazard assessment using UAV”, Journal of the Indian Society of Remote Sensing, vol. 49, no. 3, pp. 1-9.

Devendra Kumar Yadav, Pragyan Mishra, SingamJayanthu and Santos Kumar Das, (2021): “On the application of IoT slope monitoring system for open cast mines based on LoRa wireless communication”, Arabian Journal for Science and Engineering, Doi: 10.1007/ s13369-021-05941-9.

Marc Elmouttie and Peter Dean, (2020): “Systems engineering approach to slope stability monitoring in the digital mine”, Resources, vol.9, no.4, pp.1-15.

Devendra Kumar Yadav, Singam Jayanthu, Santos Kumar Das, Suchismita Chinara and Pragyan Mishra, (2019): “A critical review on slope monitoring systems with a vision of unifying WSN and IoT”, IET Wireless Sensor Systems, vol.14, pp.1-19.