1. Global Environmental MEMS Sensors (GEMS): A Revolutionary Observing Systemfor the 21st CenturyNIAC Phase II CP_02-01John Manobianco, Randolph J. Evans, David A. ShortENSCO, Inc. Dana Teasdale, KristoferS.J. PisterDust, Inc. Mel SiegelCarnegie Mellon UniversityDonna ManobiancoManoNanoTechnologies, Research, & ConsultingNovember 2003
2. Outline
•Description
•Potential applications
•Phase I (define major feasibility issues)
•Phase II
–Methods / Approach
–Plan
•Summary
3. Description
•Integrated system of airborne probes–Mass produced at very low per-unit cost–Disposable–Suspended in the atmosphere–Carried by wind currents–MicroElectroMechanicalSystem (MEMS)-based sensors•Meteorological parameters (temperature, pressure, moisture, velocity) •Particulates•Pollutants•O3, CO2, etc. •Acoustic, seismic, imaging•Chemical, biological, nuclear contaminants•Self-contained with power source for–Sensing–Navigation–Communication–Computation
4. Description (con’t)
Broad scalability & applicability~1010probesGlobal coverage1-km spacingRegional coverage100-m spacing•Mobile, 3D wireless network with communication among–Probes, intermediate nodes, data collectors, remote receiving platforms
5. Potential ApplicationsWeather / climate analysis & predictionBasic environmental scienceField experimentsGround truth for remote sensingResearch & operational modeling
6. Potential ApplicationsPlanetary science missionsManobianco et al.: GEMS: A Revolutionary Concept for Planetary and Space Exploration, Space Technology and Applications International Forum, Symposiumon Space Colonization, Space Exploration Session, Albuquerque, NM, February 2004.
7. Potential Applications
Planetary science missionsManobianco et al.: GEMS: A Revolutionary Concept for Planetary and Space Exploration, Space Technology and Applications International Forum, Symposiumon Space Colonization, Space Exploration Session, Albuquerque, NM, February 2004. Space Environment Monitoring
9. Phase I (Define Feasibility Issues) CommunicationNetworkingDeploymentScavengingEnvironmentalData collection/managementData impactCostNavigationDispersionProbe designPowerMeasurement
10. Phase II Methods / Approach
Optimization of trade-offs(cost, practicality, feasibility) Multi-Dimensional Parameter Space(Power, Deployment, Cost,…) Physical limitations(measurement & signal detection) Scaling(probe & network size)
11. Phase II Plan
•Study major feasibility issues
–Extensive use of simulation
•Deployment, dispersion, data impact, scavenging, power,…
•System model
–Experimentation as appropriate / practical
–Cost-benefit analysis
•Projected per unit & infrastructure cost
•Compare w/ future observing systems
•Quantify benefits
•Develop technology roadmap & identify enabling technologies
•Pathways for development & integration w/ NASA missions
12. Meteorological Issues
•Deployment strategies
•Dispersion
•Scavenging
•Impact of probe data on analyses & forecasts
–Dynamic simulation models
–Virtual weather scenarios
–Dispersion patterns
–Simulated probe data & statistics
–OSSE (Observing System Simulation Experiments)
13. Deployment / Dispersion
•Release (N. Hemisphere)
–High-altitude balloons
–10ox 10o lat-lon
•Deployment
–4-day release
–18-km altitude
–1 probe every 6 min
•Terminal velocity
–0.01 m s-1
•Duration
–24 days
–15 Jun –9 Jul 2001
•Total # of probes
–~200,000
23. The Next Generation: NanoDust?
•Nanotubesensors
•Nanotubecomputation
•Nanotubehydrogen storage
•Nanomechanicalfilters for communication!
24. Cost of Basic Operations
Operation
Current
[A]
Time
[s]
Charge
[A*s]
Sleep
3μ
Sample
1m
20μ
0.020μ
Talk to neighbor
15 byte payload
25m
5m
125μ
Listen to neighbor
15 byte payload
10m
8m
80μ
Sound an alarm
25m
1s?
25,000μ?
Listen for alarm
2m
2m
4μ
QAAbattery= 2000mAh = 7,200,000,00 μA*s
25. Mesh Network Routing & LocalizationProbe network determines optimal route to gateway, and locates probes based on signal strength and GPS sensors. Three motes’routing pathsSpecialized GPS motes send position information to gateway. Limit: Message traffic increases near gateway
26. Communication Limits
•RF noise limit: Preceived> kTBNfSNRminSensitivity ≈-102 dBm(<0.1 pW) But, transmit power must be greater due to path loss•Network communication must be rapid enough to avoid errors or loss of path due to probe motion Signal Power ReceivedThermal Noise -174+53 dBmReceiver Noise+9 dBmSignal to Noise required by downstream processing+10 dBm
27. Link Budget↑Probe Spacing = ↑Transmission PowerTransmit Power vs. Probe Spacing 00.020.040.060.080.10.120.1402000400060008000100001200014000160001800020000Probe Spacing (m) Transmit Power Required (W) Transmit Power Required for 0.1 pW at Receiver10 GHzAntenna Gain = 3
28. Network Scaling
•Message traffic limited near gateway
•Next step: event-based reporting (1-way communication)
•Beyond: local event-based subnet formation & reporting –any mote becomes a gatewayLots of message traffic near gatewayMotes near event “wake up”and report
29. Optimization: Trade-offs
↓SIZE
+Min Environmental Impact
+Slow descent
-Decreased power storage
-Decrease SNR
↓POWER
+Smaller power supply required
-Decrease transmission distance & sampling frequency
-Shorter mote life
↑# PROBES
+Improved network localization
+Improved forecast
-Increased message traffic
31. Cost / Benefit Analysis•Cost issues–Per unit cost–Deployment / O&M cost–Global versus regional (targeted) observations–Estimates for future observing systems (in situ v. remote) •Benefit issues–$3 trillion dollars of U.S. economy has weather / climate sensitivity –How much can we reduce sensitivity with improved observations / forecasts? –Example (hurricane track forecasts) •72-h track forecast error ≈200 mi•Evacuation cost = $0.5M per linear mile•Potential savings with 10% error reduction = $10M for storms affecting populated areas
32. Summary
•Advanced concept description
–Mobile network of wireless, airborne probes for environmental monitoring
•Phase I results
–Define major feasibility issues
–Validate viability of the concept
•Phase II plans
–Study feasibility issues
–Cost-benefit
–Generate technology roadmap including pathways for development / integration with NASA missions
33. Acknowledgments
•Universities Space Research Association
NASA Institute for Advanced Concepts
–Phase I funding
–Phase II funding
•Charles Stark Draper Laboratory
–James Bickford
–Sean George
