CS HONORS UNDERGRADUATE RESEARCH PROGRAM - PROJECT PROPOSAL

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CS HONORS UNDERGRADUATE RESEARCH PROGRAM -
PROJECT PROPOSAL

• Tingyu Thomas Lin
• Advisor Professor Deborah Estrin
• January 25, 2007

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PROJECT PROPOSAL

• Acoustic Localization
• Acoustic Embedded Networked Sensing Box (ENSBox)
• Expanding the capabilities of the ENSBox
• Using motes

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OUTLINE

• Acoustic Localization and the ENSBox
• Expanding the ENSBox adding motes
• Methodology and milestones
• Summary

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OUTLINE

• Acoustic Localization and the ENSBox
• Expanding the ENSBox adding motes
• Methodology and milestones
• Summary

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ACOUSTIC LOCALIZATION

• Why acoustic sensing platform?
• Scientific
• Tracking calls of birds, wolves, other animals
• Military
• Tracking vehicle and personnel movements
• Commercial
• Smart spaces
• Distributed Sensing Networks
• Low-cost nodes
• Scalability
• May need to cover large area

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TYPICAL IMPLEMENTATION OF ACOUSTIC PLATFORM

• Source L. Girod et al. The Design and
  Implementation of a Self-Calibrating Distributed
  Acoustic Sensing Platform. SenSys06, November
  1-3, 2006, Boulder, Colarado, USA.

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EXISTING DISTRIBUTED ACOUSTIC SENSING PLATFORMS

• Heavily Optimized
• e.g. Countersniper system, troop tracking sensing
  platforms
• Not ideal as a prototyping platform
• General purpose acoustic sensing platforms
• Off-the-shelf solutions
• Doesnt scale easily
• WINS NG, VanGo, and other Berkeley/Telos Mote
  based systems
• Generally, doesnt provide tight time
  synchronization
• Tight constraints on resources
• ENSBox

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ENSBOX

• Source L. Girod et al. The Design and
  Implementation of a Self-Calibrating Distributed
  Acoustic Sensing Platform. SenSys06, November
  1-3, 2006, Boulder, Colarado, USA.

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ENSBOX

• Acoustic Source Localization
• At node
• If source is far field, sound waves are planar
• If not, discard information
• Approximate bearing of source
• Using difference in time of arrivals at the
  microphones
• Relative positions of microphones known and fixed
• In the network
• Approximate location of source
• Using bearing estimates of several nodes
• Using difference in time of arrivals at nodes
• Possible through tight time synchronization
• Possible only if nodes know their relative
  locations
• How do they know? Through Self Localization

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ENSBOX

• Acoustic Self Localization
• At node
• Onboard speaker, emits a calibration tone
• Other nodes estimates bearing to the node
• Each node takes turns
• In the network
• Reconcile bearing estimates
• Determine relative positions of nodes

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ENSBOX

• Internal workings
• 400 MHz Intel PXA255 w/ 64MB RAM
• On-board 32MB flash
• Dual slot PCMCIA interface
• 802.11 wireless
• Digigram VXPocket440 four-channel sampling card
• Runs Linux 2.6.10
• Modifications to kernel and Digigram firmware
• Support accurate timestamping
• Custom circuit board
• Battery powered

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ENSBOX

• Functional Performance
• Very accurate
• About 5 cm 2D positional error and 1.5 degree
  average orientation error
• partially obstructed 80x50m field
• About 5x better than the next best solution
• General purpose
• Enables rapid prototyping
• Self calibrating system

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OUTLINE

• Acoustic Localization and the ENSBox
• Expanding the ENSBox adding motes
• Methodology and milestones
• Summary

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MOTES

• Components
• Single microphone (vs. 4 for ENSBox)
• Speaker (for calibration tone)
• Severely limited resources
• Runs on TinyOS
• Radio for networking

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MOTES

• Proposed Functionality
• Acoustic Self Localization
• Smaller and cheaper
• Can easily add motes around points of interests
• Additional nodes gt Denser network
• Better detection of events
• More accuracy to estimates
• Increased robustness in face of obstructions
• Additional features to network
• Early warning for ENSBox nodes
• Highly unlikely doable in allotted time

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COMPARISON WITH VS. WITHOUT MOTES

• Without motes

• With motes

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OUTLINE

• Acoustic Localization and the ENSBox
• Expanding the ENSBox adding motes
• Methodology and milestones
• Summary

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INCREMENTAL DEVELOPMENT

• Phase 1 Self Localization of motes (4 weeks)
• Have ENSBox locate motes
• Initially constrain to single mote and 2D
• Determine best mote configuration
• find a robust calibration signal
• Find optimal mote placements
• Phase 2 Interface motes with ENSBoxes
• Have them talk so ENSBoxes knows where motes are
• Phase 3 Integrate motes into system
• Motes assist in estimating acoustic sources
• Experiment, test and analyze the impact of motes
  on the system

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MILESTONES

• By Project Checkpoint
• Phase 1 complete
• Self Localization of motes
• Deliverable Analysis of optimal mote
  configuration
• Phase 2 under way
• By Project End
• Phase 2 complete
• Motes and ENSBoxes talking
• Deliverable Discussion on issues and solutions
  encountered
• Phase 3 complete
• Motes assist in source localization
• Deliverable Quantitative analysis of impact
  motes have on the system

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POTENTIAL DIFFICULTIES

• Phase 1 finding optimal mote configurations
• Testing and analyzing data might take longer than
  expected, but still within the first quarter
• Push back Phase 2 and 3 if necessary
• Phase 2 Integrating motes into network
• Coding intensive phase
• Depending on how swiftly the coding goes, may
  take shorter or longer (most likely longer) than
  expected
• If necessary, drop Phase 3
• Phase 3 Using motes to find sources
• Coding intensive and a lot of data analysis
• Drop Phase 3 if necessary

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POTENTIAL DIFFICULTIES

• As progress is made, a better feel of whats
  feasible will develop
• Project goals and scope will change

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OUTLINE

• Acoustic Localization and the ENSBox
• Expanding the ENSBox adding motes
• Methodology and milestones
• Summary

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SUMMARY

• Motes have the potential of improving ENSBox
• Motes are cheap
• Easier to deploy and in greater numbers than the
  larger and more expensive ENSBoxes
• Denser network gt More information in system gt
  better estimates