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Miniaturized Wireless Sensing for Process Monitoring
Transcript of Miniaturized Wireless Sensing for Process Monitoring
Prof. Brian Otis, Prof. Babak ParvizUniversity of Washington
Electrical Engineering DepartmentSeattle, WA, USA
Miniaturized Wireless Sensing for Process Monitoring
Outline
⢠Motivation: inexpensive, microscale wireless process monitors
⢠Technical challenges
⢠New results: 500mg wireless temperature sensor
Goal: improved process observabilityusing distributed sensors
From the large scaleâŚ
⢠Example: Structural monitors, fluid conductivity, flow rate, temperature, etc, at arbitrary locations
⢠Unrealistic to position thousands of complete sensing and chemical analysis units
⢠Use large number of inexpensive wireless monitors
⢠Network density provides high spatial resolution and robustness
âŚto the micro scale
⢠Dense networks of interconnected wireless sensors⢠Allow fineâgrained measurement of process parameters⢠Subâmm device sizes
* Prof. Albert Folch, University of Washington
Challenges: cost, size, power
⢠Necessary to integrate many different technologies in a very small volume:
â Various sensors
â RF transceiver/antenna
â Microprocessor
â Battery/Power supply
â Passive components
⢠The resulting system:
â Too large for microscale sensing
â Prohibitively expensive for ubiquitous deployment
â Power is a huge problem
NI Data Acquisition Card
Mooreâs Law to the rescue..
The number of transistorson an IC doubles every 2 years
Resulting from advancements in IC fabrication and design automation
1960: 25um MOS process
Today: 0.032um MOS process
1. Computation and signal processing can now be performed in a few mm2
2. This computational power is growing exponentially
3. Scientists in many communities (wildlife tracking, process monitoring, neural engineering) are recognizing this and are eager to take advantage of this opportunity
4. Can enable previously impossible collection of data
Why is this important?
We can shrink the electronicsâŚ
But what about power?
Battery technology canât keep pace with Mooreâs law
Towards energy harvesting for autonomous sensors...
Good candidates for process monitors: RF, solar, thermal, vibrational.
Energy harvesting
Extract energy from the environment to power wireless sensors
S. Roundy, B. Otis, Y.H. Chee, J. Rabaey, P. Wright, IEEE ISLPED 2003
Thermal power
1cm
Battery replacement:
â 1cm3 footprintâ 10uW average powerâ Provide heat flow sensing?
Wireless power transfer
⢠Asymmetric link: shifts burden of power and complexity to the interrogator
⢠Allows very small, inexpensive sensing tags
sensor
Detect
Case study: a wireless temperature sensor
⢠Goal: miniaturized, batteryâfree, wireless sensor for monitoring temperature levels in chemical processes, pipelines, and storage tanks
⢠Also applicable to automotive, aviation, industrial, and medical monitoring
Wireless sensor architecture
+RFID circuitry
RFID + sensor âtagâ
RFID reader
Wireless power
Sensor ID, Data
1â10m
The power challenge
⢠Temperature sensing requires precision amplification and analog to digital conversion (ADC)
⢠Unstable power supply due to wireless power transfer
⢠Digital computation required for processing the RFID protocol
⢠The range and functionality of the system is limited by the amount of power that can be wirelessly transferred
Prototype electronics
Wireless sensor platform
⢠Power provided wirelessly from 900 MHz commercial RFIDâtag reader: 1m range
⢠Maintenance free
⢠Energy is stored on the board to power sensorâinterface
⢠Custom low noise IC
Initial deployment: wireless neural interface
⢠Use commercial 900MHz RFID reader
⢠Communication through EPC Gen2 protocol
⢠Singleâchannel far field neural recording device
⢠1m range
J. Holleman, D. Yeager, R. Prasad, J.R. Smith, and B. Otis, BioCAS, November 2008
⢠Returns spike count instead of electronic product code (EPC)
⢠Can digitize and transmit short bursts of data after triggering Wireless charging Sensing
(RF Off)Backscatter data
Example: wireless EMG recording on a hawkmoth
Spike detector
Low noise amp
Initial deployment: wireless neural interface
Current research: miniaturization
⢠Integration of RF, sensor interface, and computation onto a single integrated circuit
SoC WISP
⢠Assembly completed 7/22/2009
⢠Singleâchip wirelessly powered sensor interface
⢠0.13Οm CMOS⢠~ 100,000 transistors
⢠Dimensions: 1mm x 2mm x 0.15mm
⢠Designers: â Dan Yeager
â Azin Zarrasvand
â Helen Zhang
1mm x 2mm<10ÎźW power dissipation
SoC WISP
⢠2ÎźW chopper stabilized amplifier⢠8âbit analogâtoâdigital converter
⢠RF energy harvester
⢠Three voltage regulators (0.7V, 1.2V, 1.8V)
⢠Digital RFID Gen2 protocol
⢠Unique chip identification generator
⢠Supply/process independent 8MHz oscillator
RF Energy Harvesting Performance
⢠Sufficient operating voltage at an input RF power of â16dBm (~25ÎźW)
Wirelesslyâpowered temp sensor
⢠Connection to generic thermocouple allows wireless, batteryâfree temperature sensing
⢠~ 500mg including antenna
⢠Range: ~2m with standard commercial RFID reader
⢠Weâve developed a GUI allowing programmable averaging and data logging
Wirelesslyâpowered temp sensor
⢠Connection to generic thermocouple allows wireless, batteryâfree temperature sensing
⢠~ 500mg including antenna
⢠Range: ~2m with standard commercial RFID reader
⢠Weâve developed a GUI allowing programmable averaging and data logging
Wirelesslyâpowered temp sensor
⢠Connection to generic thermocouple allows wireless, batteryâfree temperature sensing
⢠~ 500mg including antenna
⢠Range: ~2m with standard commercial RFID reader
⢠Weâve developed a GUI allowing programmable averaging and data logging
~40 reads/second
Adjustable averaging
Real-time readout
Miniaturized flight recorder for hawkmoths
Longitudinal section of Manduca sexta
DLMâs
⢠Initial deployment: recording temperature inâflight from the Dorsolongitudinal (DLM) Muscles (main muscles that indirectly power the downstroke of the wings)
⢠Allows recording of previously impossible data
⢠Collaboration with Nicole George, Prof. Tom Daniel, UW Biology
Conclusions
1. Mooreâs law: exponential growth in computational power
2. Thereâs also a dramatic growth in performance of wireless sensing technologies
3. We have demonstrated early prototypes of a few key technologies
4. Recent results: batteryâfree wireless temperature sensor integrated circuit