# Analysis of Information Availability for Seismic and Volcanic Monitoring Systems: A Review
## 2 Methodology Validation
### Data Analysis
The model was trained with 700,000 waveforms from the Northern California earthquake catalog and showed detection accuracy, identification of events and noise, and low computing resources for processing P- and S-wave arrival times. The designed software includes an application terminal interface, docker container, data visualization, and SSH protocol data transmission, and also supports SAC, MSEED, and NumPy array. [PERSON] et al. [52], 2021, made a review of IoGN sensing devices, algorithms, architecture, and applications for seismic data acquisition units and data servers. The main techniques that could be applied to IoGN are denoising methods, including compressed sensing (CS) and autoencoders (AE) used to reduce seismic noise. IoGN sensing devices are accelerometers and geophones. Common ADC 16/24-bit resolutions and communication modules use IEEE 802.11 or cellular network standards, as well as ZigBee and GPRS communications from end devices to remote Web servers. [PERSON] et al. [50] proposed a seismic data reconstruction model through recurrent neural network (RNN) algorithms. The authors made tests of different RNN algorithms via the traces to trace approach using available field data provided by a petroleum geo-services company. The ML model training split the training data and validation sets. The proposed model learns high-level features from complex field data and predicts the missing traces in the sparsely seismic sample. A simple comparison of deep bidirectional with and without skip connections was made, using architectures and hyperparameters for both models. * Seismic data standards. [PERSON] et al. [53] described the structure and goals of an integrated system of networks within the International Federation of Digital Seismograph Networks (FDSN), as well as the instrumentation characteristics, data exchange of high-quality seismological data, standardization format, and access. [PERSON] et al. [54] summarized Global Seismographic Network (GSN) data that are used for the research of operational missions of the USGS, the NOAA, and the Comprehensive Nuclear Test Ban Treaty, as well as studies of earthquakes, tectonics, and volcanology. [PERSON] et al. [57] proposed a communications system, LoRaMoto, which aimed to exchange information about civilians' safety aftermath of an earthquake when outages in communication networks following earthquakes limit the capacity to obtain information. LoRaMoto helps to extend the LoRaWAN architecture and implements a packet forwarding mechanism to keep emergency management organizations informed. The LoRaWAN network protocol has scalability and performance limitations when there is node mobility. However, the LoRaMoto system does not use node mobility; it is closer to an ad hoc network. A performance evaluation was made by simulating a realistic environment to understand scalability and portability. Limitations in scalability were related to the density and capacity of gateways for node communication. [PERSON] et al. [18] presented a description of a seismic monitoring network (RSN--U.S), transmission media, data processing, and collaboration with other organizations to improve the monitoring technology. Its main products have been active structure/fault monitoring, use of earthquake focal mechanisms, and classification of event types. [PERSON] et al. [59] made a description of the OTRIONS seismic network waveform database, their cloud infrastructure for acquisition, and a storage system with access to the station metadata. Their network had a high level of security in data exchange through multi-protocol VPN services. [PERSON] et al. [55] summarized the main station information system (SIS) features that are a repository for managing, checking, and distributing high-quality metadata. Data centers, such as the Advanced National Seismic System (ANSS), use SIS information to identify parameters such as the overall response, channel gain, and hardware components. [PERSON] et al.