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Dt Italk

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Dt Italk

  1. 1. Proactive monitoring in natural environments Ian Marshall , Computing Laboratory, University of Kent [email_address] Technical Director of the Envisense Research centre http://envisense.org
  2. 2. Current research methods <ul><li>Single expensive package </li></ul><ul><li>In situ process studies </li></ul><ul><li>Low spatial resolution </li></ul><ul><li>Short lifetime </li></ul><ul><li>Small areas </li></ul>
  3. 3. Wireless Sensor networks <ul><li>Ad-hoc wireless communication </li></ul><ul><li>Physical measurement </li></ul><ul><li>No access to mains </li></ul><ul><li>Large area (sq kms) </li></ul><ul><li>Long life (months) </li></ul><ul><li>Many measurement points </li></ul>
  4. 4. WSN management <ul><li>Low probability of manual intervention </li></ul><ul><li>Highly dynamic, unpredictable environment </li></ul><ul><li>Very unreliable nodes and comms </li></ul><ul><li>Need to automate response to events </li></ul><ul><li>‘ model free’ adaptive control </li></ul>
  5. 5. Peak district Experiments
  6. 6. Floodnet
  7. 7. SECOAS Scroby sands wind farm and its impact on sedimentation processes
  8. 8. CEFAS Survey April 2002
  9. 9. Mechanical General Arrangement Buoy (yellow) Radio equipment Data cable Warp Chain Chain Warp Plough anchor
  10. 10. Real trial Oct-Nov 2004
  11. 11. Initial Deployment Areas 1 NM 6 Sensors 150m apart Shore station
  12. 12. Seabed Package <ul><li>Measure Oceanographic variables (15 minute cycle) </li></ul><ul><ul><ul><li>Temperature (1 sample/min) </li></ul></ul></ul><ul><ul><ul><li>Pressure (1 sample/s for 5 mins) </li></ul></ul></ul><ul><ul><ul><li>Turbidity (10 samples/min) </li></ul></ul></ul><ul><ul><ul><li>Tilt (aka current) - (1 sample/s for 5 mins) </li></ul></ul></ul><ul><ul><ul><li>Conductivity (1 sample/min) </li></ul></ul></ul><ul><li>Adapt sampling rates </li></ul><ul><li>Adaptively log data </li></ul><ul><li>Transmit selected data to radio buoy </li></ul>
  13. 13. Adaptive sampling <ul><li>Measure, delete, combine, forward, sleep </li></ul><ul><li>Use local variability, neighbour variability and internal state </li></ul><ul><li>Self configure using distributed evolutionary “algorithm” (bacteria) </li></ul><ul><li>Can adjust priorities and frequency of actions </li></ul><ul><li>Can form groups (quorum sensing) </li></ul><ul><li>Reward set by user using a diffusion (gossip) protocol – changes drive auto-reconfiguration of genome </li></ul>
  14. 14. QoS on a Sensor Network
  15. 15. Processing
  16. 19. Summary <ul><li>Autonomous adaptive control is needed in environmental sensor networks </li></ul><ul><li>Network protocols must support and respond to application semantics (be app aware) </li></ul><ul><li>In simulation adaptation was almost as good as optimal sliding window </li></ul><ul><li>In practice it dealt well with change from calm to stormy </li></ul><ul><li>More research will be needed </li></ul><ul><ul><li>www.secoas.org </li></ul></ul><ul><ul><li>www.envisense.org </li></ul></ul>

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