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Keep It Physical,
Keep It Real
Steven GlaserCenter for Information Technology Research in the Interest of Society
UC Berkeley College of Engineering
25 Motes onDamaged sidewall
Dense Instrumentation of Full Scale Structure
- Performed through 12+ strong shakings- 100+ channels of acceleration data per test
30 Motes onGlue-lam beam
2003, [email protected]
Instrument the Golden
Gate Bridge!
• Have a prototype structural health monitoring system up and running within a year•Culler, Fenves, Demmel, Glaser
Current Application:
The Berkeley "Smart Dust" Concept
Spread thousands of wireless sensor nodes casually over an arbitrary area of interest
They self-organize into a network conveying arbitrary information from any point to any other at whatever bandwidth is demanded...
..while operating at incredibly low energy usage (i.e, off most of the time) to run for years on small batteries and harvested energy
..and being extremely responsive in timesof key activity
..without ever bothering you about design considerations, intended usage, faults, or constraints
From Culler
(Stevie wants to be 6 foot tall)
Achieving this dream requires a broad-based team approaching the pieces as part of a system
Cohort:• David Culler – computer science, electrical engineering• Greg Fenves – structural engineering, computer science• Roger Howe – electrical engineering, MEMS fabrication• Al Pisano – mechanical engineering, MEMS• Kris Pister – electrical engineering, smart dust• Tim Sands – materials science, microfabrication• Nick Sitar - geoengineering, geology
Me – GeoEngineering,
Philosophy, driller, vision thing
Students:• Laurie Baise: PhD – GeoEng; MS - Seismo; Prof. Tufts• Chen Min: BS, MS - EE; PhD - Civil Systems• JianYe Ching: MS, PhD – GeoEng; MS - EECS; Housner Fellow, CalTech• Dom Galic: MS, Appl. Math; PhD - Civil Systems• Jeff Moore: BS – Eng. Geol.; PhD – GeoEng• Albert To – MS – geo; MS – seismo; PhD - GeoEng• Ying Zhang: MS – Mat. Eng; MS – EE; PhD - Civil Systems
Private Industry:• Senera Inc. – remote structural prognostication • Dust Inc. – microMotes• INTEL Laboratory @ Berkeley • Marathon Products – environmental recorders• Shinkawa Sensor Tech. – rotating machinery health 2003, [email protected]
6-D accelerometer arrays - MOTE as brains- 24 bit, low noise accel- 9 bit, high amplitude- rate gyros- orientation magnetometer- pH, pwp, temp
• integration of advanced technology accelerometers (30 ngrms/Hz noise floor, 24-bit direct digital)
• integration of 3-D rate gyros, giving 6-DOF dynamic point measurements
• integration of solar power, improved batteries, GPS timing, and ethernet server at the Local Gateway
• fully dynamic networking, real-time reprogramming and peer-to-peer sensor fusion
• integration of magnetometer, pH, pore pressure, and tilt
• current 1-off price $4000 per 6-D station
Local Gateway - LINUX machine
- high-powered radio - Ethernet server - power source - array aggregator - GPS
TERRASCOPE - 4-D Distributed Seismic Monitoring Network
Great Valley Sequencesandstone
Franciscan Formationmetamorphosed shale, sandstone
Hayward Fault
3 m
15 m
Colluvium3 -5 m
Alluvial depositssands, gravels,
silty clays
yagiantenna
solarcollector
3-D accelerometer arrays - 24 bit, low noise - 9 bit, high amplitude - rate gyros - orientation magnetometer - Mote intelligence - pH, pwp, temp
Optional custom-formed bladder for
open holes
Local Gateway
- LINUX machine - high-powered radio - Ethernet server - power source - array aggregator - link to base server
70 m 35 m
Cartoon of the vertical seismic array and SeisMote
rf does not work well in soils, so we must use wires anyway
Wires work well for transmitting power
Relatively simple set of commands needed for thie experiment
We know where the sensor nodes are, and they do not move much
A few sensors in each hole
Development and refinement of vertical arrayseismic monitoring systems
–16-bit MCU with 14-bit A/Ds
–Bank of progammible gaim opamps
–4 ~ 8 Mb memory
–Power control
–GUI interface
any analog sensor
any digital sensor
Formatted output
–LINUX machine
–GPS timing
–Power source
–Rf link (high/low power)
–Web server
Create an
"Instrumentation
Processor" COTS
COTS
COTS
FireBug: Adaptive Real-Time Geoscience and Environmental Data
Analysis, Modeling and Visualization
Nicholas Sitar (Civil and Environmental Engineering)George Brimhall (Earth and Planetary Science)Steven Glaser (Civil and Environmental Engineering)John Radke (Landscape Architecture and Environmental Planning)Raja Sengupta (Civil and Environmental Engineering)
2003, [email protected]
• Drop GPS Motes - field networks capable of real-time distributed data evaluation and transmission
• Helicopter based real-time topographic and ground cover mapping
• GIS: real-time updating from multiple information streams
•Full data field coupled to real-time burn model
• Visualization and adaptive modeling of observed phenomena returned to in situ fire fighter
Current accomplishments• The web/ database toolchain works well.
• The “Fireboard” hardware is past its fi rst iteration and appears to working well.
• Container design for field deployment has been prototyped.
• Personnel have been Type I I wildfi re certified f or controlled burns.
• Project has survived personnel turnover and intermittent participation well.
Top Bottom
• Race/deadlocks still exist in sensor board driver code.• Weather and air quality concerns limit controlled burn
opportunities. We have to be able to move fast when necessary.
• “Uplink” details for remote deployment are still sketchy.
Current FireBug Tasks
Prof. Steven D. GlaserCivil EngineeringUniversity of California, [email protected]/642-1264
Thanks!
The Boss