Post on 23-Dec-2015
HW - Mica2 and Mica2Dot
HW - Mica2 and Mica2Dot
• ATMega 128L 8-bit, 8MHz, 4KB EEPROM, 4KB RAM, 128KB flash• Chipcon CC100 multi-channel radio (Manchester encoding, FSK).
From 10-20 ft. up to 500-1000ft.
Spec Mote (3/6/2003)Spec Mote (3/6/2003)
• Size: 2x2.5mm, AVR RISC core, 3KB memory, FSK radio (CC1000), encrypted communication hardware support
Mica2
Rockwell WINSRockwell WINS
• StrongARM SA 1100, 32-bit RISC processor, 1MB SRAM, 4MB flash
• 900MHz spread spectrum radio, with dedicated microcontroller: 32KB RAM, 1MB bootable flash
• 3.5”x3.5”x3” package size• acoustic sensor• magnetometer• accelerometer• seismic sensor
module
UCLA Medusa MK-2UCLA Medusa MK-2
• Radio-acoustic localization• ATMega 128L 8-bit, 8MHz, 4KB flash, 4KB SRAM
( interface w/ sensors & radio)
• ARM Thumb 32-bit, 40MHz, 1MB flash, 136KB RAM (more demanding processing)
• TR1000 radio Monolithics (OOK, ASK modulation)• Ultrasonic ranging system, light & temperature
Medusa MK-2Medusa MK-2
• Can attach to infrastructure via a high speed wire link
• Daisy chain motes
Acoustic Sensor Magnetometer
Medusa MK-2Medusa MK-2
• Can power down various parts independently to save power– Subsystems– Each sensor– Radio– CPU (might have multiple power saving
modes)
Specialized HardwareSpecialized Hardware
• Environmental Motes (Berkeley, UVA)
• Medical Motes (Harvard/UVA)– Wireless EKG– Pulse Oximeter
• Robotic nodes• New
microprocessors/microcontrollers– Use TI chips instead of Atmel
More Specialized HWMore Specialized HW
• CCDs• Special logging mote (using camera
memory card)• Stargates – heterogeneous WSNs
– Powerful– Energy consumption is a problem
• New devices appearing continuously
SensorsSensors
• Sensors must be small and low-power in order to reduce energy and fit form factor
• Packaging important• Robustness to weather needed
Sensors Sensors
• Example of sensors– Magnetic sensors
• Honeywell’s HMC/HMR magnetometers
– Photo sensors• Clairex: CL9P4L
– Temperature sensors• Panasonic ERT-J1VR103J
– Accelerometers• Analog Devices: ADXL202JE
– Motion sensors• Advantaca’s MIR sensors
– GPS– Cameras
ActuatorsActuators
• Examples of Actuators– Motor (for mobile nodes)– LEDs– Buzzer– Emit chemical
• In general, actuators may be powerful, large, and complicated– Can be outside of motes (e.g., turn on
lights, send a vehicle into system, …)
• What actuators should go on motes?
Properties of Sensors (14)
Properties of Sensors (14)
– Range• Example
– HMC1053: +/-6 Gauss
– Accuracy• Measure of error and uncertainty
– Repeatability• HMC1002: 0.05%
– Linearity• HMC1002: 0.1% (Best fit straight line +/- 1
Gauss)
Sensors Sensors
– Sensitivity• How output reflects input?
– Efficiency• Ratio of the output power to the input power
– Resolution• Temperature within ½ degree
Sensors Sensors
•Response time– How fast the output reaches a fraction of the
expected signal level
•Overshoot– How much does the output signal go beyond the
expected signal level
•Drift and stability– How the output signal varies slowly compared to
time
•Offset– The output when there is no input
Sensors Sensors
– Packaging• Example – HMC1053: 16-PIN LCC
packaging
– Property of the circuit• Load of the circuit• Power drain
– Initialization Time (important when nodes are asleep and awakened dynamically when an event occurs)
Sensors Sensors
• Signal Processing– Process the sensor reading to make it
useful to the application• Sensor fusion (heterogeneity possible)• False alarm processing (false positives and false
negatives)
– The complexity varies from a simple threshold algorithm to full-fledged signal processing and pattern recognition
• New solutions needed on minimal capacity devices
SensorsSensors
• Raw reading of an MIR sensor in a quiet environment– The beginning period represents
some unknown noise, possibly due to the positioning of the sensor
I ndoor test , qui et envi ronment wi thout mot i on
0
100
200
300
400
500
1 80 159 238 317 396 475 554 633 712 791 870 949 1028
7. I ndoorQui et
Sensors Sensors
• Raw reading of an MIR sensor as a person walked by– The all-zero period is due to unreliable UART
interface used to collect the reading and can be ignored.
39. 64Hz. Mi l ton. sb. MI R. DanWal k. 3
0
20
40
60
80
100
120
1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181 193 205 217 229 241 253 265 277
39. 64Hz. Mi l ton. sb. MI R. DanWal k. 3
Acoustic SensingAcoustic Sensing
Three Cars
Initial Calibration
No Detection
Detection whenEnergy Crosses
Standard Deviation
Programming with Sensors
Programming with Sensors
Sensor
Sensor
Sensor
ADC
ADC
ADC
Voltage Micro-Proc
Micro-Proc
Micro-Proc
AMP
AMP
Voltage
210
ADCADC
• MAX1245– 8 channels of analog input– Can sample up to 100,000 samples per
sec– Resolution of 12 bits– Interfaces with SPI and I2C buses– Can enter low power mode– Interface to Processor: processor issues
commands to read channel– Interfaces to sensors
Temperature SensorTemperature Sensor
• A22100– Output voltage: 22.5mV/C over
temperature range of -50C to 150C– Derive conversion equation (see spec
sheet)– Example: for 5 V power supply
• T = (V(out) – 1.375)/0.0225• If V(out) = 1.94V then T = 25.1C
A22100V(out)
GND
5V
Other SensorsOther Sensors
• Light– Add power and ground– Analog output voltage is proportional to
incident light– May need an amp to detect full range
• Accelerometer– Output voltage is proportional to acceleration
and power V(s)– V(out) = V(s)/2 – (sensitivity * V(s)/5 *
acceleration)– Sensitivity depends on particular
accelerometer
RFIDRFID
• RFID– Typical configuration
– Application: ID based intelligent control• Such as access control, baggage ID, object
tracking, inventory management, …
PlusMicrochipWith data
RFIDRFID
– What makes RFID useful?•Ubiquitous•Low-cost (pennies)
– Compare RFID with motes•Difference? Yes (today).•Will they merge to be the same
class of hardware as motes?– Active RFID tags exist (battery/sensors)
– Privacy and security issues
Intel WISP tagIntel WISP tag
• Essentially a battery-less sensor mote– Light, temperature,
3d- accelerometer– 10 feet range with
harvested RF power
• Requires RFID reader and (large) antennas
Activity recognition using WISP*
Activity recognition using WISP*
* Ubicomp 2009
Antenna layout in home
WISP tags on kitchen artifacts
WISP potentialWISP potential
• Battery-free solution to sensor networks
• Great potential for elderly activity inference and other smart home applications
Sensor and Data FusionSensor and Data Fusion
• Data Fusion – combine data from multiple sources (not only sensors)
• Sensor Fusion – combine data from multiple sensors
SignaturesSignatures
• Objects/phenomena generate signatures
• Type of energy (electromagnetic, acoustic, ultrasonic, seismic, etc.
• Active or passive sensors• Affected by weather, clutter,
countermeasures, etc.
Data FusionData Fusion
• Ad hoc• Classical• Bayesian• Dempster-Shafer• Fuzzy Logic• Pattern Recognition• ANN• Etc.
Multi-ModalMulti-Modal
• Robustness• Act synergistically in high clutter and
inclement weather
• Example: Weather satellites use microwave, millimeter wave, infrared and cameras
• Example: Fog at an airport• Example: Rain cools targets (PIR
sensors not as effective)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
front
floor
fridge
microwave
pantry
cook
top
sink flush
entrance
sink shower
motion
motion
motion
weight
light
light
light
pressur
e
bed room
kitchen
kitchen
kitchen
kitchen
kitchen
bath
room
bath
room
bath
room
bath
room
bed room
kitchen
bath
room
bed room
bed room
kitchen
bath
room
bed room
Personal location tracking
Kitchenvisits
bedroomvisits
bathroomvisits
eating toileting showering sleeping
Eating Level
ToiletingLevel
Sleeping Level
MovementLevel
LightLevel
WeightLevel
Diabetes Depression
Light Weight