Design of smart sensing components for volcano monitoring (original) (raw)

Real-World Sensor Network for Long-Term Volcano Monitoring: Design and Findings

IEEE Transactions on Parallel and Distributed Systems, 2000

This paper presents the design, deployment and evaluation of a real-world sensor network system in an active volcano -Mount St. Helens. In volcano monitoring, the maintenance is extremely hard and system robustness is one of the biggest concerns. However, most system research to date have focused more on performance improvement and less on system robustness. In our system design, to address this challenge, automatic fault detection and recovery mechanisms were designed to autonomously roll the system back to the initial state if exceptions occur. To enable remote management, we designed a configurable sensing and flexible remote command and control mechanism with the support of a reliable dissemination protocol. To maximize data quality, we designed event detection algorithms to identify volcanic events and prioritize the data, and then deliver higher priority data with higher delivery ratio with an adaptive data transmission protocol. Also, a light-weight adaptive linear predictive compression algorithm and localized TDMA MAC protocol were designed to improve network throughput. With these techniques and other improvements on intelligence and robustness based on a previous trial deployment, we air-dropped 13 stations into the crater and around the flanks of Mount St. Helens in July 2009. During the deployment, the nodes autonomously discovered each other even in-the-sky and formed a smart mesh network for data delivery immediately. We conducted rigorous system evaluations and discovered many interesting findings on data quality, radio connectivity, network performance, as well as the influence of environmental factors.

Volcano Monitoring: A Case Study in Pervasive Computing

Computer Communications and Networks, 2009

Recent advances in wireless sensor network technology have provided robust and reliable solutions for sophisticated pervasive computing applications such as inhospitable terrain environmental monitoring. We present a case study for developing a real-time pervasive computing system, called OASIS for optimized autonomous space in situ sensor-web, which combines ground assets (a sensor network) and space assets (NASA's earth observing (EO-1) satellite) to monitor volcanic activities at Mount St. Helens. OASIS's primary goals are: to integrate complementary space and in situ ground sensors into an interactive and autonomous sensorweb, to optimize power and communication resource management of the sensorweb and to provide mechanisms for seamless and scalable fusion of future space and in situ components. The OASIS in situ ground sensor network development addresses issues related to power management, bandwidth management, quality of service management, topology and routing management, and test-bed design. The space segment development consists of EO-1 architectural enhancements, feedback of EO-1 data into the in situ component, command and control integration, data ingestion and dissemination and field demonstrations.

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.

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.

Optimized Autonomous Space In-situ Sensor-Web for Volcano Monitoring

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2008

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensorweb. 12 1 1-4244-1488-1/08/$25.00 ©2008 IEEE 2 IEEEAC paper #1144, Version 2, Updated October 24, 2007 mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be integrated such that each element is capable of autonomously tasking the other. Sensor-web data acquisition and dissemination will be accomplished through the use of the Open Geospatial Consortium Sensorweb Enablement protocols. The three-year project will demonstrate end-to-end system performance with the in-situ test-bed at Mount St. Helens and NASA's EO-1 platform.

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.

A Multi-agent Space, In-situ Volcano Sensorweb

2010

We have deployed and demonstrated operations of an integrated space in-situ sensorweb for monitoring volcanic activity. This sensorweb includes a network of ground sensors deployed to the Mount Saint Helens volcano as well as the Earth Observing One spacecraft. The ground operations and space operations are interlinked in that ground-based intelligent event detections can cause the space segment to acquire additional data via observation requests and space-based data acquisitions (thermal imagery) can trigger reconfigurations of the ground network to allocate increased bandwidth to areas of the network best situated to observe the activity. The space-based operations are enabled by an automated mission planning and tasking capability which utilizes several Open Geospatial Consortium (OGC) Sensorweb Enablement (SWE) standards which enable acquiring data, alerts, and tasking using web services. The ground-based segment also supports similar protocols to enable seamless tasking and data delivery. The space-based segment also supports onboard development of data products (thermal summary images indicating areas of activity, quicklook context images, and thermal activity alerts). These onboard developed products have reduced data volume (compared to the complete images) which enables them to be transmitted to the ground more rapidly in engineering channels.. We have deployed a general agent-based framework for sensorwebs focused on the EO-1 spacecraft. In this architecture, the principal sensorweb processes of event detection, campaign matching, and response generation are performed continuously. This cycle is shown below

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.

Volcano multiparameter monitoring system based on Internet of Things (IoT)

Australian Journal of Electrical and Electronics Engineering, 2020

Indonesia is an archipelagic country that lies within the Circum-Pacific belt or the Ring of Fire. Currently, the country hosts 127 active volcanoes, of which only 69 are properly monitorable for the activity around the clock. In light of volcanic disaster risk reduction and early warning system, volcano monitoring becomes indispensable. Since volcanoes have steep terrestrial contour and vast area, plenty of monitoring points are thus necessary. The higher the number of the monitoring points, the more costly it will be to procure the instruments required for the volcano monitoring. Therefore, it requires monitoring devices that are effective and efficient. This paper presents an application monitoring for active volcano using Wireless Sensor Network (WSN) and Internet of Things (IoT). Our main goals were to create low power consumption monitoring systems that are easy to maintain, easy to deploy, energy-saving, flexible and integrated. The wireless communication system on this device uses the IEEE 802.15.4 standard. Finally, this paper demonstrates the applicability of the proposed system for the detection of volcanic multi parameters such as Carbon Monoxide (CO), Hydrogen Sulphide (H2S), Crater Temperature, pH and Seismic.

Air-dropped sensor network for real-time high-fidelity volcano monitoring

Proceedings of the 7th international conference on Mobile systems, applications, and services - Mobisys '09, 2009

This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTCtime synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99% with an overall system uptime of about 93.8% over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments.