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The PermaSense Project Low-power Sensor Networks for Extreme Environments

The PermaSense Project Low-power Sensor Networks for Extreme Environments. Jan Beutel, ETH Zurich National Competence Center in Research – Mobile Information and Communication Systems. PermaSense – Alpine Permafrost Monitoring. Cooperation with Uni Basel and Uni Zurich.

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The PermaSense Project Low-power Sensor Networks for Extreme Environments

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  1. The PermaSense ProjectLow-power Sensor Networks for Extreme Environments Jan Beutel, ETH Zurich National Competence Center in Research – Mobile Information and Communication Systems

  2. PermaSense – Alpine Permafrost Monitoring • Cooperation with Uni Basel and Uni Zurich

  3. PermaSense – Aims and Vision Geo-science and engineering collaboration aiming to: • provide long-term high-quality sensing in harsh environments • facilitate near-complete data recovery and near real-time delivery • obtain better quality data, more effectively • obtain measurements that have previously been impossible • provide relevant information for research or decision making, natural hazard early-warning systems

  4. To Better Understand Catastrophic Events… Eiger east-face rockfall, July 2006, images courtesy of Arte Television

  5. PermaSense Deployment Sites 3500 m a.s.l. A scientific instrument for precision sensing and data recovery in environmental extremes

  6. PermaSense – Key ArchitecturalRequirements • Support for ~25 nodes • Different sensors • Temperatures, conductivity, crack motion, ice stress, water pressure • 1-60 min sensor duty-cycle • Environmental extremes • −40 to +65° C, ΔT ≦5° C/min • Rockfall, snow, ice, rime, avalanches, lightning • Near real-time data delivery • Long-term reliability • ≧99% data yield • 3 years unattended lifetime • Relation to other WSN projects • Comparable to other environmental monitoring projects • GDI [Szewczyk], Glacsweb [Martinez], Volcanoes [Welsh], SensorScope [Vetterli], Redwoods [Culler] • Lower data rate • Harsher, higher yield & lifetime • Data quality/integrity

  7. PermaSense Technology

  8. PermaSense – System Architecture Sensor network Base station Backend

  9. Powerful embedded Linux (Gumstix) 4 GB storage, all data duplicated Solar power (2x 90W, 100 Ah, ~3 weeks) WLAN/GPRS connectivity, backup modem PermaSense – Base Station Overview

  10. Base Station with Stacked Mikrotik WLAN Router Gumstix Verdex WLAN Router TinyNode GSM EMP Protectors IP68 Enclosure and Connectors

  11. PermaSense – Sensor Node Hardware • Shockfish TinyNode584 • MSP430, 16-bit, 8MHz, 10k SRAM, 48k Flash • LP radio: XE1205 @ 868 MHz • Waterproof housing and connectors • Protective shoe, easy install • Sensor interface board • Interfaces, power control • Stabilized measurements • 1 GB memory • 3-year life-time • Single battery, 13 Ah • ~300 A power budget

  12. Precision Sensing – Architectural Considerations • One platform vs. family of devices? Make vs. buy? • Capabilities for multiple sensors • Extreme low-power • High quality data acquisition (ADC resolution on MSP430 not sufficient) • Reliability in extreme environment • Based on existing platform, Dozer low-power protocol • 0.167% duty-cycle, 0.032mA • Modular, accommodating different sensors on one platform • Single, switchable serial bus architecture • Strict separation of operating phases (TDMA) [Burri – IPSN2007]

  13. Precision Sensing – Sensor Interface Board I • Extension: One Serial Bus • (Power) control using GPIO • Optimized for low-power duty cycling

  14. Precision Sensing – Sensor Interface Board II • External Memory • Data buffering • End-to-end validation

  15. Precision Sensing – Sensor Interface Board III Power Control and Protection Design for Testbed Integration

  16. Dozer Low-Power System Software Integration • Dozer ultra low-power data gathering system • Beacon based, 1-hop synchronized TDMA • Optimized for ultra-low duty cycles • 0.167% duty-cycle, 0.032mA • System-level, round-robin scheduling • “Application processing window” between data transfers and beacons • Custom DAQ/storage routine contention window data transfer beacon jitter time slot 1 slot 2 slot k [Burri – IPSN2007] Application processing window time slot 1 slot 2 slot k

  17. Validation Using Simultaneous Power Traces

  18. PermaDozer – Power Performance Analysis 1/120 sec 1/30 sec 148 uA average power

  19. PermaSense Sensors • Sensor rods (profiles of temperature and electric conductivity) • Thermistor chains • Crack meters • Water pressure • Ice stress • Self potential • Data: Simple sensors, constant rate sampling, few integer values

  20. PermaSense Sensors – Sensor Rod Example

  21. Sensors Rod Data –Temperature and Resistivity

  22. PermaSense Sensors – Crack Meter Example

  23. Crack Meter Data – Happy Geo-Science Partners

  24. Of Testing, Bugfixing and Learning it the Hard Way…

  25. Power Optimization – A Squeeze with Implications • Regulator uses 17uA quiescent current • Bypass used to shutdown regulator -> ~1uA in standby • No Bypass increases ADC accuracy: std dev 0.8844 -> 0.0706

  26. The Result – Power Quality Increases Data Accuracy After Before

  27. Of Sensors, Placement and Power Consumption

  28. Testing – Physical Reality Impacting Performance Ambient Temperature DAQ Duration Storage Duration time Watchdog Resets

  29. Networked testbed: Deployment-Support Network Power profiling Power trace verification [Woehrle – FORMATS2009] Temperature cycling Sensor calibration Rooftop system break-in PermaSense – Test and Validation Facilities [Beutel – EWSN2007]

  30. But Nothing Can Replace Real Field Experience System Outages Lost Packets Battery Voltage & Temperature

  31. Node Health Data – Indispensable for Analysis # Lost Packets System Outages Network Disconnect Nodes Reset

  32. Understanding the Exact Causes is Hard... • Missing EMP protector – broken radio chip? • If so is it snow/wind or lightning induced? • Long-term software bug – buffer overflow; timing? • Misunderstood “feature” of the implementation? • Hardware breakdown? • Energy-supply dependent? • Spring-time behavior based on the environment? • Cosmic rays at 3500 m a.s.l. ? • Can external effects trigger the reed contact on the reset? • … • Probably not feasible to test/reproduce this in the lab!

  33. Installation – Timeconsuming and Demanding PermaSense installation 2007, images courtesy of Arte Television

  34. Pro’s and Con’s of Solar Panels

  35. Demo – Live Data at http://tik42x.ee.ethz.ch:22001

  36. Key PermaSense Challenges Correct Test and Validation System Integration Actual Data Interdisciplinary Team

  37. PermaSense Achievements – Current Status 148 uA average power • Dozer integration successful • Best-in-class low power • DAQ vs. COM power consumption • Extreme installation effort (time) • Relative relaxation of multihop requirement • Continuous data since mid July 2008 • Media attention • First joint geo-science publications [Gruber etal. – NICOP2008]

  38. Acknowledgements • All PermaSense collaborators • Uni Basel, Uni Zurich, EPFL, SLF, ETH Zurich, … • Further reading • J. Beutel, S. Gruber, A. Hasler, R. Lim, A. Meier, C. Plessl, I. Talzi, L. Thiele, C. Tschudin, M Woehrle, M. Yuecel: PermaDAQ: A Scientific Instrument for Precision Sensing and Data Recovery in Environmental Extremes. IPSN 2009. • J. Beutel, S. Gruber, A. Hasler, R. Lim, A. Meier, C. Plessl, I. Talzi, L. Thiele, C. Tschudin, M Woehrle, M. Yuecel: Operating a Sensor Network at 3500 m Above Sea Level . IPSN 2009. • 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), vol. 1, pp. 669–674, June 2008. • M. Woehrle, C. Plessl, J. Beutel and L. Thiele: Increasing the Reliability of Wireless Sensor Networks with a Unit Testing Framework . EmNets 2007. • J. Beutel, M. Dyer, M. Yücel and L. Thiele: Development and Test with the Deployment-Support Network . EWSN 2007. • K. Aberer, G. Alonso, G. Barrenetxea, J. Beutel, J. Bovay, H. Dubois-Ferriere, D. Kossmann, M. Parlange, L. Thiele and M. Vetterli: Infrastructures for a Smart Earth - The Swiss NCCR-MICS Initiative. Praxis der Informationsverarbeitung und Kommunikation, pages 20-25, Volume 30, Issue 1, January 2007. • 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), pp. 450–459, ACM Press, New York, Apr. 2007.

  39. Project Webpage: http://www.permasense.ch

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