PermaDAQ A Scientific Instrument for Precision Sensing and Data Recovery in Environmental Extremes Jan Beutel, Stephan Gruber †, Andreas Hasler †, Roman Lim, Andreas Meier, Christian Plessl *, Igor Talzi ‡, Lothar Thiele, Christian Tschudin ‡, Matthias Woehrle, Mustafa Yuecel Computer Engineering and Networks Lab, ETH Zurich † Physical Geography Division, Department of Geography, University of Zurich * Paderborn Center for Parallel Computing, University of Paderborn ‡ Computer Science Department, University of Basel

PermaSense – Aims and Vision Geo-science and engineering collaboration aiming to understand permafrost in steep bedrock walls. –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

Understanding Permafrost and Catastrophic Events Eiger east-face rockfall 2006, images courtesy of Arte Television

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

PermaSense – Key Architecture Facts 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 Near real-time data delivery Long-term reliability – ≧ 99% data yield –3 years unattended lifetime Relation to other projects Comparable to other environmental monitoring: GDI, Glacsweb, Volcanoes Lower data rate Harsher, higher yield & lifetime Data quality/integrity

PermaSense – System Architecture BackendSensor networkBase station

PermaSense – Sensor Node Hardware Overview Shockfish TinyNode584 –MSP430, 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

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]

Sensor Interface Board I Extension: One Serial Bus (Power) control using GPIO Optimized for low-power duty cycling

Sensor Interface Board II External Memory Data buffering End-to-end validation

Sensor Interface Board III Power Control and Protection Design for Testbed Integration

Power Optimization – A Squeeze with Implications Regulator uses 17uA quiescent current Bypass used to shutdown regulator -> ~1uA in standby No Bypass increases ADC accuracy: stddev >

Result – Power Quality Increases Data Accuracy After Before

Testing – Physical Reality Impacting Performance Storage duration Temperature ADC duration Watchdog resets time

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, scalar values

PermaSense – Sensor Rod Example

PermaSense – Crack Meter Example

Dozer Low-Power System 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 time jitter slot 1slot 2slot k data transfer contention window beacon [Burri – IPSN2007] time slot 1slot 2slot k Application processing window

Validation Using Simultaneous Power Traces

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

Of Sensors, Placement and Power Consumption

Finally Data – Making Our Science Partners Happy

Key PermaSense Challenges System Integration Correct Test and Validation Actual DataInterdisciplinary Team

PermaSense Achievements – Current Status 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 Media attention First joint geo-science publications [Gruber etal. – NICOP2008] 148 uA average power

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