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PermaDAQ: A scientific instrument for precision sensing and data recovery in environmental extremes

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Published:13 April 2009Publication History

ABSTRACT

The PermaSense project has set the ambitious goal of gathering real-time environmental data for high-mountain permafrost in unattended operation over multiple years. This paper discusses the specialized sensing and data recovery architecture tailored to meet the precision, reliability and durability requirements of scientists utilizing the data for model validation. We present a custom sensor interface board including specialized sensors and redundancy features for end-to-end data validation. Aspects of high-quality data acquisition, design for reliability by strict separation of operating phases and analysis of energy efficiency are discussed. The system integration using the Dozer protocol scheme achieves a best-in-class average power consumption of 148µA considerably exceeding the lifetime requirement.

References

  1. K. Aberer, M. Hauswirth, and A. Salehi. A middleware for fast and flexible sensor network deployment. In Proc. 32nd Int'l Conf. Very Large Data Bases (VLDB '06), pages 1199-1202. ACM Press, New York, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Arora, P. Dutta, S. Bapat, V. Kulathumani, H. Zhang, V. Naik, V. Mittal, H. Cao, M. Demirbas, M. Gouda, Y. Choi, T. Herman, S. Kulkarni, U. Arumugam, M. Nesterenko, A. Vora, and M. Miyashita. A line in the sand: a wireless sensor network for target detection, classification, and tracking. Computer Networks, 46(5):605 - 634, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. Barrenetxea, F. Ingelrest, G. Schaefer, M. Vetterli, O. Couach, and M. Parlange. Sensorscope: Out-of-the-box environmental monitoring. In Proc. 7th Int'l Conf. Information Processing Sensor Networks (IPSN '08), pages 332-343. IEEE CS Press, Los Alamitos, CA, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. N. Burri, P. von Rickenbach, and R. Wattenhofer. Dozer: ultra-low power data gathering in sensor networks. In Proc. 6th Int'l Conf. Information Processing Sensor Networks (IPSN '07), pages 450-459. ACM Press, New York, April 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. K. Chebrolu, B. Raman, N. Mishra, P.K. Valiveti, and R. Kumar. Brimon: a sensor network system for railway bridge monitoring. In Proc. 6th Int'l Conf. Mobile Systems, Applications, and Services (MobiSys 2008), pages 2-14, New York, NY, USA, 2008. ACM Press, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. H. Dubois-Ferrière, L. Fabre, R. Meier, and P. Metrailler. Tinynode: a comprehensive platform for wireless sensor network applications. In Proc. 5th Int'l Conf. Information Processing Sensor Networks (IPSN '06), pages 358-365. ACM Press, New York, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. P. Dutta, J. Taneja, J. Jeong, X. Jiang, and D. Culler. A building block approach to sensornet systems. In Proc. 6th ACM Conf. Embedded Networked Sensor Systems (SenSys 2008), pages 267-280. ACM Press, New York, November 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. Gruber and W. Häeberli. Permafrost in steep bedrock slopes and its temperature-related destabilization following climate change. Journal of Geophysical Research, 112(F02S18), 2007.Google ScholarGoogle ScholarCross RefCross Ref
  9. S. Gruber and W. Häeberli. Mountain permafrost. In R. Margesin, editor, Permafrost Soils, Biology Series, page 348pp. Springer, Berlin, 2008.Google ScholarGoogle Scholar
  10. A. Hasler, I. Talzi, J. Beutel, C. Tschudin, and S. Gruber. Wireless sensor networks in permafrost research - concept, requirements, implementation and challenges. In Proc. 9th Int'l Conf. on Permafrost (NICOP 2008), volume 1, pages 669-674, June 2008.Google ScholarGoogle Scholar
  11. K. Martinez, P. Padhy, A. Elsaify, G. Zou, A. Riddoch, J. K. Hart, and H. L. R. Ong. Deploying a sensor network in an extreme environment. In Proc. Int'l Conf. Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC 2006), volume 1, pages 186-193. IEEE, Piscataway, NJ, June 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. G.J. Pottie and W.J. Kaiser. Wireless integrated network sensors. Communications of the ACM, 43(5):51-58, May 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J.M. Rabaey, M.J. Ammer, J.L. da Silva Jr., D. Patel, and S. Roundy. PicoRadio supports ad hoc ultra-low power wireless networking. IEEE Computer, 33(7):42-48, July 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. K. Römer and F. Mattern. The design space of wireless sensor networks. IEEE Wireless Communications, 11(6):54-61, December 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. L. Selavo, A. Wood, Q. Cao, T. Sookoor, H. Liu, A. Srinivasan, Y. Wu, W. Kang, J. Stankovic, D. Young, and J. Porter. LUSTER: wireless sensor network for environmental research. In Proc. 5th ACM Conf. Embedded Networked Sensor Systems (SenSys 2007), pages 103-116. ACM Press, New York, November 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. R. Szewczyk, J. Polastre, A. Mainwaring, and D. Culler. Lessons from a sensor network expedition. In Proc. 1st European Workshop on Sensor Networks (EWSN 2004), volume 2920 of Lecture Notes in Computer Science, pages 307-322. Springer, Berlin, January 2004.Google ScholarGoogle ScholarCross RefCross Ref
  17. I. Talzi, A. Hasler, S. Gruber, and C. Tschudin. PermaSense: investigating permafrost with a WSN in the Swiss Alps. In Proc. 4th IEEE Workshop on Embedded Networked Sensors (EmNetS-IV), pages 8-12. ACM Press, New York, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. G. Werner-Allen, K. Lorincz, J. Johnson, J. Lees, and M. Welsh. Fidelity and yield in a volcano monitoring sensor network. In Proc. 7th Symp. Operating Systems Design and Implementation (OSDI '06), pages 27-27, Berkeley, CA, 2006. USENIX Association, Berkeley, CA. Google ScholarGoogle ScholarDigital LibraryDigital Library

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              • Published in

                cover image ACM Conferences
                IPSN '09: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
                April 2009
                441 pages
                ISBN:9781424451081

                Publisher

                IEEE Computer Society

                United States

                Publication History

                • Published: 13 April 2009

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                Overall Acceptance Rate143of593submissions,24%

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