# Analysis of Information Availability for Seismic and Volcanic Monitoring Systems: A Review
## 2 Methodology Validation
### Data Analysis  
In this section, 51 articles are identified which contribute to the objectives of this study. Below, an overview includes the research area, justification for the study, the sampling strategy, the methodology, and the publication year. Application areas in recent studies are data transmission networks, data acquisition and processing, seismic data standards, and early warning trends. * Data transmission networks. [PERSON] et al. [23] proposed a strategy for a virtual seismologist (VS) through an open-source real-time monitoring software for SC3 to test and evaluate the EEW algorithm. The objective was latency reduction, upgrade software in network components, and reconfiguration in dataloggers. Within this methodology used for VS(SC3) evaluation, Monte Carlo simulation was applied to optimize alert times, P- and S-wave delays, filtering, phase detection, and true and false alert detections. [PERSON] et al. [24] made a latency data recognition for seismic data transmission as a crucial parameter in EEW. A partial solution is proposed through the reconfiguration of datalogger parameters, deploying software upgrades in seismic networks. Other studies by [PERSON] et al. [29], [PERSON] et al. [30], and [PERSON] et al. [28] described seismic sensors, data-logger components, and methods used in specific networks for real-time monitoring. [PERSON] et al. [27] developed ad hoc software applied in wireless data transmission systems, as well as acquisition and visualization systems, for a specific volcanic area. The main measured parameters were delay, standard deviation, and packet loss statistics. Other QoS metrics such as real time delay, availability, and robustness (fault tolerance) identified network performance. [PERSON] et al. [38] proposed an ad hoc development wireless transmission for heterogeneous networks in seismic exploration. A test environment considered acquisition, wireless transmission, and data control. The system used IEEE 802.15.4 and IEEE 802.11b/g. [PERSON] et al. [37] proposed a procedure and simulation for energy consumption reduction with a large number of hops. Network architecture was based on the IEEE 802.11 ad. Evaluation parameters were: average power consumption, end-to-end latency in contrast with operating frequency, bandwidth, transmit power, and receiver sensitivity. [PERSON] et al. [32] and [PERSON] et al. [33] reviewed TDMA protocols and the advantage of using WSN and LoRa networks. The objective was to improve energy consumption, transmission latency, traffic, bandwidth use, and others for seismic monitoring applications. [PERSON] et al. [34] made a WSN analysis for seismic data acquisition networks; the study considered data throughput and transmission time from wireless geophones to gateway node in a wireless network architecture based on IEEE802.11 af standards. [PERSON] et al. [35] proposed a mechanism to improve reliable data transmission in a wireless sensor using Markov decision processes, because of wireless link fluctuations in faulty regions. The model helped to improve the packet level reliability with stringent delivery delay requirements in the presence of faulty nodes. The measured parameter, packet  
Figure 4: Identified Issues. redundancy levels in the network coding process, applied link loss rates and redundancy levels. [PERSON] et al. [31] proposed a routing protocol for underwater sensor networks (UWSN), i.e., \"Q-learning-based localization-free any path routing (QLFR) protocol\" which focused on holding time mechanism for packet forwarding, and analysis of routing protocol performance. The goal was to decrease high energy consumption and large latency in the underwater environment using Q-learning-based localization-free anypath routing. [PERSON] et al. [25] proposed a data compression algorithm to decrease the size of SEG-Y files and the conversion of miniSEED files for the transmission and storage of large amounts of seismic exploration data.