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In-Situ Habitat and Environmental Monitoring Alan Mainwaring, Joe Polastre and Rob Szewczyk

Explore the potential impact of sensor networks in habitat monitoring, with a focus on design context, applications, and field site requirements for in-situ data collection. Learn about instrumentation in natural spaces, data logging to databases, and real-time sensor node inspection.

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In-Situ Habitat and Environmental Monitoring Alan Mainwaring, Joe Polastre and Rob Szewczyk

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  1. In-Situ Habitat and Environmental Monitoring Alan Mainwaring, Joe Polastre and Rob Szewczyk Intel Research - Berkeley Lablet

  2. Talk Outline • Introduction to habitat monitoring • Field sites and application requirements • Establishing the design context • Summer milestones and wrap-up • Demo: live data from two networks

  3. Introduction • Habitat monitoring represents a class of sensor network applications enormous potential impact for scientific communities and society as a whole. • Instrumentation of natural spaces enables long-term data collection at scales and resolutions that are difficult, if not impossible, to obtain otherwise. • Intimate connection with physical environment allows sensor networks to provide local information that complements macroscopic remote sensing.

  4. Application-Driven Sensor Network Research • Benefits to others • Computer scientists help life scientists • Small steps for us can be revolutionary for others • Provides design context • Eliminates some issues, constrains others • Can add new ones, e.g., packaging • Prioritizes issues • Low-power communication stacks • Run-time systems and VM’s for re-tasking • Health and status monitoring systems • Tools deployment and on-site interaction

  5. Habitat Monitoring • Goal: Remote, in-situ system consisting of • Sensor networks in scientifically interesting areas • WLANs link sensor networks to base station (DB) • Internet link remote users to local resources • Access models • Remote DB, admin, health and status monitoring • Continuous data logger to DB for long-term analysis • Interactive inspection of sensor nodes (near real-time) • Sensors of interest: too many to list • E,g., light, temperature, relative humidity, barometric pressure, infrared, O2, CO2, soil moisture, fluid flow, chemical detection, weight, sound pressure levels, vibration • Need both relative and absolute measurements with units

  6. Field Sites and Application Requirements

  7. James Reserve (CA) Great Duck Island (ME) Habitat Monitoring Field Sites

  8. Application Requirements I • Internet access • 24x7 • 3 to 4 sensor networks (habitats) • network of sensor networks • 128 stationary motes per network • 50% may miss interesting phenomena • 1 year lifetime -- minimum • standalone data-loggers run 1 to 10 years • Change and adaptation may take days • Static node locations, infrequent occlusions • Off-the-grid power: it’s off, it’s big, or it’s solar • Disconnected operation possible at all levels

  9. Application Requirements II • Field re-tasking (local or remote) • Adjust sampling rates, operational parameters, • Remote management (one site visit per year) • 1 person can locate/touch/service all motes in 1 week • Inconspicuous packaging and operation • No bright colors, no sounds (buzzing) or blinking lights • Pack it out: cannot “deploy and forget” • Must find motes in field after year(s) of operation • Can’t leave 1000’s of leaking Li/Cd batteries • Users want predictable system operation • Cannot burden users with more complexity

  10. Sensing Requirements: Weather Board

  11. Some Non-Requirements • Localization • Oftentimes nodes are precisely placed • Data aggregation • Of readings on node (yes), across nodes (no) • Precise time synchronization (yet) • Depends on what precise means… • Instantaneous adaptation to change • Prompt detection but not reaction • Object tracking • Unless it’s passive and over large distances

  12. Establishing the Design Context

  13. Design Context:Power Budget Basics • Batteries • 2xAA 2850 mAhr (est. 75% usable) • daily 5.86 mAhr (365 day target lifetime) • What can the mica do with 5.86 mAhr? • Compute for 46 minutes • Or send 70320 messages • Or take 281000 temp readings

  14. Design Context:Sensing Demands • Sensor frequency bytes/day compressed • Photo 1 min 2800 144 (95%) • I2C temp 15 min 192 192 • Baro/pressure 15 min 192 192 • Baro/temp 15 min 192 192 • %RH 15 min 192 192 • IR thermopile second 172800 8640 (95%) • Thermistor second 172800 8640 (95%) • Totals • 0.04 mAhr for sensing • 349KB/day or ~11600 msgs • 18KB/day or ~600 msgs (compressed)

  15. Design Context: TwoCommunications Budgets • (1) Low-power listening (2) Global scheduling 98% idle 1.17 mAhr 99% idle 1.188 mAhr 1% listen 3.60 mAhr listen time n/a 1% runtime 1.08 mAhr 1% runtime 4.668 mAhr sensing 0.044 mAhr sensing 0.044 mAhr for comm: 1.036 mAhr for comm: 4.624 mAhr • What’s 1 mAhr worth? And 4.6 mAhr? • 12431 msg opportunities 55487 msg opportunities • 1 msg every 7 seconds 1 msg every 1.5 seconds • In 128 node network, In 128 node network, 32 msgs/leaf-node/day 144 msgs/leaf-node/day

  16. Communications Design Challenge • Want network to last 1 year • Want uniform amount of data from motes • Route 18KB from each sensor to DB • 1 mAhr communication budget (low-power listening) • 4 mAhr communication budget (global scheduling) The key design challenge for habitat monitoring with sensor networks is resolving the trade-off between globally-scheduled approaches to communications and alternative approaches based on local information.

  17. Summer Milestones

  18. Summer Milestones • June • Weather sensor board debug and SW • Low-power multi-hop routing for 1% duty cycle • Setup lab network with new sensors and SW (6/27) • July • Upgrade Great Duck Island network (7/8 – 7/12) • Upgrade James Reserve network (7/24 – 7/25) • Monitor data collection, begin evaluation • August • Invited talk: COA board of trustees (8/1) • TR: experiences and initial evaluation (8/25) • NPR segment / National Geographic article (tbd)

  19. Conclusions • Habitat monitoring is broadly representative of a seemingly simple class of sensor network applications. • Reference for benchmarking and comparison • The habitat monitoring application domain makes some systems issues concrete yet leaves others open. • no mobility, 1 year longevity, resource budgets • We can pursue sensor network systems research while delivering significant value to life scientists, today. • what’s trivial to one can be revolutionary to another • We need robust multi-hop routing on spanning trees • You’ve got 1 to 4 mAhr per day to accomplish it

  20. Demo?

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