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Air-dropped sensor network for real-time high-fidelity volcano monitoring
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International Conference On Mobile Systems, Applications And Services archive
Proceedings of the 7th international conference on Mobile systems, applications, and services table of contents
Kraków, Poland
SESSION: Applications and services table of contents
Pages 305-318  
Year of Publication: 2009
ISBN:978-1-60558-566-6
Authors
Wen-Zhan Song  Washington State University, Vancouver, WA, USA
Renjie Huang  Washington State University, Vancouver, WA, USA
Mingsen Xu  Washington State University, Vancouver, WA, USA
Andy Ma  Washington State University, Vancouver, WA, USA
Behrooz Shirazi  Washington State University, Pullman, WA, USA
Richard LaHusen  U.S.Geological Survey, Vancouver, WA, USA
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

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 UTC-time 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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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OASIS: Optimized Autonomous Space In-Situ Sensor Web. http://sensorweb.vancouver.wsu.edu.
 
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3
 
4
 
5
 
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TinyOS. http://www.tinyos.net/tinyos-1.x.
 
7
ION Inc.http://www.iongeo.com/
8
9
10
11
12
13
14
15
 
16
17
 
18
19
 
20
T. L. Murray and E. T. Endo. A real-time seismic-amplitude measurement system (rsam). volume 1966 of USGS Bulletin, pages 5--10. 1992.
 
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Y. Peng, R. Lahusen, B. Shirazi, and W. Song. Design of smart sensing component for volcano monitoring. In The 4th IET International Conference on Intelligent Environments (IE), July 2008.
 
22
Y. Peng, W. Song, R. Huang, M. Xu, and B. Shirazi. Cacades: a reliable dissemination protocol for data collection sensor network. In IEEE Aerospace Conference, March 2009.
 
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R. Scarpa and R. I. Tilling. Monitoring and Mitigation of Volcano Hazards. Springer, 1 edition, January 1996.
 
24
S. Shukla, S. Shukla, N. Bulusu, N. Bulusu, S. Jha, and S. Jha. Cane-toad monitoring in kakadu national park using wireless sensor networks. In Networks Research Workshop, July 2004.
 
25
 
26
K. Srinivasan and P. Levis. RSSI is under appreciated. In Proc. 3rd Workshop on Embedded Networked Sensors (EmNets), May 2006.
27
28
29
 
30
31
32
 
33
F. Yuan, W.-Z. Song, N. Peterson, Y. Peng, L. Wang, and B. Shirazi. Lightweight sensor network management system design. In The 4th IEEE International Workshop on Sensor Networks and Systems for Pervasive Computing, March 2008.

Collaborative Colleagues:
Wen-Zhan Song: colleagues
Renjie Huang: colleagues
Mingsen Xu: colleagues
Andy Ma: colleagues
Behrooz Shirazi: colleagues
Richard LaHusen: colleagues