A wireless sensor network for monitoring volcano-seismic signals (original) (raw)

A wireless sensor network for monitoring volcanic tremors

Natural Hazards and Earth System Sciences Discussions, 2013

Monitoring of volcanic activity is important to learn about the properties of each volcano and provide early warning systems to the population. Monitoring equipment can be expensive and thus, the degree of monitoring varies from volcano to volcano and from country to country, with many volcanoes not being monitored at all. This paper describes the development of a Wireless Sensor Network (WSN) capable of collecting geophysical measurements on remote active volcanoes. Our main goals were to create a flexible, easy to deploy and maintain, adaptable, low-cost WSN for temporary or permanent monitoring of seismic tremor. The WSN enables the easy installation of a sensor array on an area of tens of thousand of m 2 , allowing the location of the magma movements causing the seismic tremor to be calculated. This WSN can be used by recording data locally for latter analysis or by continuously transmitting it in real time to a remote laboratory for real-time analyses. 1 Introduction Volcanologists often use wired arrays of sensors, usually seismometers, to monitor volcanic eruptions and tremor: a very low frequency seismic signal that precedes a volcanic eruption, caused by the movements of the magma in the interior of the crater. The installation of a sensor array enables seismic tremor to be measured at different places, allowing the location and depth of the magma movements to be calculated. Most of the equipment used in these systems had the particularity of being extremely heavy, normally the size of a small cabinet, and expensive to purchase or maintain. These properties limit the number of devices which can be feasibly installed on a remote location. Also, from a technical perspective, these devices usually rely on specific non-standardised communication protocols, which constrain the system's maintenance, evolution and integration.

Towards a New Volcano Monitoring System Using Wireless Sensor Networks

This paper presents a seismic signal analysis framework on data sensed by a wireless sensor network deployed on Cotopaxi volcano. The results obtained by measuring environmental signals in the volcano and applying wavelet analysis, it is possible to find a signal classification to interpret the behaviour of the volcano. Sixteen sensors have been used and deployed in a strategy area, the information was obtained during three days of continuous monitoring. This information was sent to a surveillance laboratory located 45 km away from the station placed in the volcano, a WiFi-based long distance technology was used to this purpose. Volcanic information was processed using wavelet transform, a spectral pattern of seismic events determined four kinds of events, corresponding to a volcanic tremor, hybrid seisms, long period seisms and tectonic seisms.

Monitoring volcanic eruptions with a wireless sensor network

2005

This paper describes our experiences using a wireless sensor network to monitor volcanic eruptions with low-frequency acoustic sensors. We developed a wireless sensor array and deployed it in July 2004 at Volcán Tungurahua, an active volcano in central Ecuador. The network collected infrasonic (low-frequency acoustic) signals at 102 Hz, transmitting data over a 9 km wireless link to a remote base station. During the deployment, we collected over 54 hours of continuous data which included at least 9 large explosions. Nodes were time-synchronized using a separate GPS receiver, and our data was later correlated with that acquired at a nearby wired sensor array. In addition to continuous sampling, we have developed a distributed event detector that automatically triggers data transmission when a well-correlated signal is received by multiple nodes. We evaluate this approach in terms of reduced energy and bandwidth usage, as well as accuracy of infrasonic signal detection.

Performance evaluation of a volcano monitoring system using wireless sensor networks

2014 IEEE Latin-America Conference on Communications (LATINCOM), 2014

Deploying a wireless sensor network on an active volcano

IEEE Internet …, 2006

Augmenting heavy and power-hungry data collection equipment with lighter, smaller wireless sensor network nodes leads to faster, larger deployments. Arrays comprising dozens of wireless sensor nodes are now possible, allowing scientific studies that aren't feasible with traditional instrumentation. Designing sensor networks to support volcanic studies requires addressing the high data rates and high data fidelity these studies demand. The authors' sensor-network application for volcanic data collection relies on triggered event detection and reliable data retrieval to meet bandwidth and data-quality demands.

Volcanic Earthquake Timing Using Wireless Sensor Networks

Recent years have witnessed pilot deployments of inexpensive wireless sensor networks (WSNs) for active volcano monitoring. This paper studies the problem of picking arrival times of primary waves (i.e., P-phases) received by seismic sensors, one of the most critical tasks in volcano monitoring. Two fundamental challenges must be addressed. First, it is virtually impossible to download the real-time high-frequency seismic data to a central station for P-phase picking due to limited wireless network bandwidth. Second, accurate P-phase picking is inherently computationintensive, and is thus prohibitive for many low-power sensor platforms. To address these challenges, we propose a new P-phase picking approach for hierarchical volcano monitoring WSNs where a large number of inexpensive sensors are used to collect fine-grained, real-time seismic signals while a small number of powerful coordinator nodes process collected data and pick accurate P-phases. We develop a suite of new in-network signal processing algorithms for accurate P-phase picking, including lightweight signal pre-processing at sensors, sensor selection at coordinators as well as signal compression and reconstruction algorithms. Testbed experiments and extensive simulations based on real data collected from a volcano show that our approach achieves accurate Pphase picking while only 16% of the sensor data are transmitted.

Quality-driven Volcanic Earthquake Detection using Wireless Sensor Networks

Volcano monitoring is of great interest to public safety and scientific explorations. However, traditional volcanic instrumentation such as broadband seismometers are expensive, power-hungry, bulky, and difficult to install. Wireless sensor networks (WSNs) offer the potential to monitor volcanoes at unprecedented spatial and temporal scales. However, current volcanic WSN systems often yield poor monitoring quality due to the limited sensing capability of low-cost sensors and unpredictable dynamics of volcanic activities. Moreover, they are designed only for shortterm monitoring due to the high energy consumption of centralized data collection. In this paper, we propose a novel quality-driven approach to achieving real-time, insitu, and long-lived volcanic earthquake detection. By employing novel in-network collaborative signal processing algorithms, our approach can meet stringent requirements on sensing quality (low false alarm/missing rate and precise earthquake onset time) at low power consumption. We have implemented our algorithms in TinyOS and conducted extensive evaluation on a testbed of 24 TelosB motes as well as simulations based on real data traces collected during 5.5 months on an active volcano. We show that our approach yields near-zero false alarm/missing rate and less than one second of detection delay while achieving up to 6-fold energy reduction over the current data collection approach.

On Real-Time Performance Evaluation of Volcano-Monitoring Systems With Wireless Sensor Networks

IEEE Sensors Journal, 2015

Volcanic eruption early warning has to be launched with effectiveness and within the shortest time possible, which imposes the requirement of using real-time (RT) systems. In this setting, volcano monitoring systems using wireless sensor networks (WSN) may play a key role. Previous works did not report detailed enough performance evaluation, in order to identify their main constraints as RT systems, either in simulation tools or in test-bed scenarios. The aim of this work was to identify the optimum number of sensors to be deployed a posteriori, based on simulation results considering throughput, packet loss, and end-to-end delay, as metrics to satisfy RT requirements. We corroborated the simulation results obtained by a test-bed deployment within a controlled environment. We determined that optimal scenario for volcano monitoring is random topology, and the results show that twelve nodes should be deployed as maximum to satisfy the RT constraints. To test the system in a real scenario, ten sensors were deployed in a strategic area at Cotopaxi Volcano, and information was collected during three days of continuous monitoring. This information was sent to a remote surveillance laboratory located 45 km away from the station placed at the volcano using WiFi-based long distance technology. Our study shows that the coordinator node is the main bottleneck in the real application scenario, given that its processing rate provokes an excessive time delay near to 3s, which has to be solved to satisfy RT requirements. We conclude that a comprehensive study including simulation, test-bed, and in-situ deployment provides valuable information for the specifications to be accounted in permanent WSN RT volcano monitoring.

Fusion-based Volcanic Earthquake Detection and Timing in Wireless Sensor Networks

Volcano monitoring is of great interest to public safety and scientific explorations. However, traditional volcanic instrumentation such as broadband seismometers are expensive, power-hungry, bulky, and difficult to install. Wireless sensor networks (WSNs) offer the potential to monitor volcanoes at unprecedented spatial and temporal scales. However, current volcanic WSN systems often yield poor monitoring quality due to the limited sensing capability of low-cost sensors and unpredictable dynamics of volcanic activities. In this paper, we propose a novel quality-driven approach to achieving real-time, distributed, and long-lived volcanic earthquake detection and timing. By employing novel in-network collaborative signal processing algorithms, our approach can meet stringent requirements on sensing quality (low false alarm/missing rate, short detection delay, and precise earthquake onset time) at low power consumption. We have implemented our algorithms in TinyOS and conducted extensive evaluation on a testbed of 24 TelosB motes as well as simulations based on real data traces collected during 5.5 months on an active volcano. We show that our approach yields near-zero false alarm/missing rate, less than one second of detection delay, and millisecond precision earthquake onset time while achieving up to 6-fold energy reduction over the current data collection approach.

A wireless sensor network for monitoring volcano-seismic signals (original) (raw)

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