Deep Learning and Internet of Things (IoT) Based Monitoring System for Miners

被引：2

作者：

Cetinkaya, T. S. ^{[1
]}

Senan, S. ^{[2
]}

Orman, Zeynep ^{[2
]}

机构：

[1] Istanbul Gelisim Univ, TR-34000 Istanbul, Turkey

[2] Istanbul Univ Cerrahpasa, TR-34320 Istanbul, Turkey

来源：

JOURNAL OF MINING SCIENCE | 2022年 / 58卷 / 02期

关键词：

Internet of Things (IoT); miner monitoring; artificial neural networks; deep learning; LSTM model; PRE-ALARM SYSTEM; NEURAL-NETWORKS; TAILINGS DAM; MODEL; PREDICTION; COAL;

D O I：

10.1134/S1062739122020156

中图分类号：

TD [矿业工程];

学科分类号：

0819 ;

摘要：

In this study, a miner monitoring system is designed using the Deep Learning (DL) approach and the IoT technology together. It is aimed to determine the area where the miners are located while a possible accident occurs by the proposed system. Experiments were carried out to analyze the effectiveness of the proposed system and the performance evaluations were made. The best result was obtained with an accuracy rate of 97.14%. This rate indicates that the designed miner monitoring system can be used effectively in practice.

引用

页码：325 / 337

页数：13

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