2021
DOI: 10.1016/j.micpro.2020.103613
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Deep learning, machine learning and internet of things in geophysical engineering applications: An overview

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Cited by 36 publications
(14 citation statements)
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“…Other authors presented a review of the methods for data processing, storage, and availability of information used in volcanic seismic monitoring centers, as well as trends to decrease data gaps identified due to limitations of the acquisition systems and transmission networks, leading to possible errors in the quantification and interpretation of seismic monitoring in real time [ 67 ]. Furthermore, a review of IoT models, deep learning, and machine learning algorithms for EEW and geophysical applications summarized methods for seismic imaging [ 72 ]. Furthermore, convolutional neural networks could be applied to seismic wave simulation, velocity prediction, and density profiles used in earthquake detection, EEW, seismic tomography, and earthquake geodesy.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Other authors presented a review of the methods for data processing, storage, and availability of information used in volcanic seismic monitoring centers, as well as trends to decrease data gaps identified due to limitations of the acquisition systems and transmission networks, leading to possible errors in the quantification and interpretation of seismic monitoring in real time [ 67 ]. Furthermore, a review of IoT models, deep learning, and machine learning algorithms for EEW and geophysical applications summarized methods for seismic imaging [ 72 ]. Furthermore, convolutional neural networks could be applied to seismic wave simulation, velocity prediction, and density profiles used in earthquake detection, EEW, seismic tomography, and earthquake geodesy.…”
Section: Resultsmentioning
confidence: 99%
“…The proposed solutions at software and network infrastructure use data recovery mechanisms through traffic control points in primary nodes and redundancy in data transmission networks to increase information availability. Dimililer et al [ 72 ] presented an overview of IoT models, deep learning and machine learning studies for EEW, and geophysical applications. The study suggested combination techniques for high-resolution seismic imaging based on deep learning algorithms.…”
Section: Methodology Validationmentioning
confidence: 99%
“…The main brain of this system is the NodeMCU ESP8266. NodeMCU ESP8266 is a System on Chip (SoC) equipped with a WiFi feature [9]. The ESP8266 NodeMCU hardware is built based on the ESP-12 module [10].…”
Section: Fig 2 Inventory System Block Diagrammentioning
confidence: 99%
“…Applications such as smart medical care, smart home and smart transportation have been widely used in daily life, bringing great convenience to people. For example, smart homes can not only provide home appliance control services, but also realize real-time environmental monitoring and anti-theft alarm functions, which helps us build a comfortable and safe living environment [2,3]. On the other hand, the vigorous development of Internet of Things (IoT) and sensing technology has led to the explosive growth of data.…”
Section: Introductionmentioning
confidence: 99%