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Internet of Things technology in mineral remote sensing monitoring
International Journal of Circuit Theory and Applications ( IF 1.8 ) Pub Date : 2020-10-27 , DOI: 10.1002/cta.2890
Yanbing Liu 1, 2 , Sanjev Dhakal 1, 2
Affiliation  

At present, the rapid development of the national economy consumes a lot of mineral resources, but the national resource extraction efficiency is low. The traditional prospecting methods consume time, money, and personnel, which cannot meet the national demand for resources in a short time. Therefore, technological innovation is needed to reduce consumption in all aspects. With the continuous development of Internet of Things technology, its application is also more extensive. This paper studies the application of Internet of Things technology in mineral remote sensing monitoring. First of all, this research mainly uses the wireless communication technology in the Internet of Things to achieve data transmission and sharing in a short distance and, second, based on the remote sensing monitoring results of the mine environment to comprehensively understand the mining area and find the suitable mining mineral resources at the fastest speed; finally, the dynamic frame time slot ALOHA algorithm is used to estimate the existing data to ensure the availability of the data. The experimental data show that vector point encryption is performed on the center line of the mine at intervals of 10, 15, 20, 30, and 50 m, respectively, and the dynamic frame slot algorithm is used to calculate the appropriate mine mining curve radius. The experimental results show that the application of Internet of Things technology in mineral remote sensing monitoring can accelerate the mining of mineral resources.

中文翻译:

物联网技术在矿物遥感监测中的应用

当前,国民经济的快速发展消耗了大量的矿产资源,但国民资源开采效率低下。传统的勘探方法浪费时间,金钱和人力,无法在短期内满足国家对资源的需求。因此,需要技术创新以减少所有方面的消耗。随着物联网技术的不断发展,其应用也越来越广泛。本文研究了物联网技术在矿物遥感监测中的应用。首先,这项研究主要使用物联网中的无线通信技术来实现短距离的数据传输和共享,其次,根据矿山环境的遥感监测结果,全面了解矿区,以最快的速度找到合适的矿产资源;最后,采用动态帧时隙ALOHA算法对现有数据进行估计,以保证数据的可用性。实验数据表明,在矿井中心线上分别以10、15、20、30和50 m的间隔进行矢量点加密,并使用动态帧缝算法来计算合适的矿井开采曲线半径。实验结果表明,物联网技术在矿产遥感监测中的应用可以加速矿产资源的开采。动态帧时隙ALOHA算法用于估计现有数据,以确保数据的可用性。实验数据表明,在矿井中心线上分别以10、15、20、30和50 m的间隔进行矢量点加密,并使用动态帧缝算法来计算合适的矿井开采曲线半径。实验结果表明,物联网技术在矿产遥感监测中的应用可以加速矿产资源的开采。动态帧时隙ALOHA算法用于估计现有数据,以确保数据的可用性。实验数据表明,在矿井中心线上分别以10、15、20、30和50 m的间隔进行矢量点加密,并使用动态帧缝算法来计算合适的矿井开采曲线半径。实验结果表明,物联网技术在矿产遥感监测中的应用可以加速矿产资源的开采。动态帧缝算法用于计算合适的矿山开采曲线半径。实验结果表明,物联网技术在矿产遥感监测中的应用可以加速矿产资源的开采。动态帧缝算法用于计算合适的矿山开采曲线半径。实验结果表明,物联网技术在矿产遥感监测中的应用可以加速矿产资源的开采。
更新日期:2020-12-04
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