Wireless Sensor Network
Research and Application
Ning “Martin” Xu
Content
• Introduction
• Comparison of WSN Projects
– Hardware
– Software
– Highlights
• Reference
Introduction
• Wireless Sensor Network (WSN)
– Spatially distributed autonomous devices using
sensors to cooperatively monitor physical or
environmental conditions at different locations
• Applications
– monitoring space
– monitoring things
– monitoring the interactions of things with each
other and the encompassing space
Introduction (cont’d)
– Monitoring space
• Environmental/habitat monitoring,precision agriculture, indoor
climate control,surveillance,treaty verification,intelligent alarm
– Monitoring things
• structural monitoring,ecophysiology,condition-based equipment
maintenance,medical diagnostics,urban terrain mapping
– Monitoring the interactions of things with each other and
the encompassing space
• wildlife habitats, disaster management, emergency response,
ubiquitous computing environments, asset tracking, healthcare, and
manufacturing process flow
Comparison of WSN Projects
• CodeBlue (Harvard)
– http://www.eecs.harvard.edu/~mdw/proj/codeblue/
• ExScal (OSU)
– http://cast.cse.ohio-state.edu/exscal/index.php?page=main.xml
• Alarm-Net (UVA)
– http://www.cs.virginia.edu/wsn/medical/index.html
• Opportunistic Pollution Monitor a.k.a Urban
Microclimate Monitoring System (BU)
– http://hulk.bu.edu/projects/ecomon/summary.html
CodeBlue
• Medical care, emergency/disaster scenario
• High date rate, reliable communication, and
multiple receivers
• indoor testbed of 30 MicaZ motes, distributed
over 3 floors CS BLDG, 1-10 senders, 3 receivers
ExScal
• Detect, track, and classify multiple intruders of
different types
• Protection of pipelines, borders, critical areas
• 1000+ XSMs and 200+ XSSs
deployed over a 1km by
300m opening in a forest
in Florida
Alarm-Net
• Assisted-Living and Residential Monitoring
• Home Health Care, (Large Scale) Assisted Living Facilities
• seven-room assisted-living residential unit, with a motion
sensor on each wall, a PC running the back-end, and a
stargate with the AlarmGate application
OPM / UMMS
• Increasing interest in
the environment
• enable localized data
monitoring using lowcost sensing
• individuals to acquire
data about local smog
(air pollution)
conditions
Hardware
• Sensor Nodes / Boards
BlueCode
Pulse oximeter (
Mica2 / MicaZ);
EKG (Mica2 /
MicaZ, Telos);
Motion analysis
sensor board
(Telos);
** Pluto (based
on Tmote Sky);
MicaZ;
ExScal
** eXtreme Scale
Mote (XSM);
** eXtreme Scale
Stargate (XSS);
Mica2
Alarm-Net
MicaZ;
Telos Sky;
** SeeMote;
Satire body
network (MicaZ,
MTS310 sensor
board);
OPM/UMMS
--
Hardware (cont’d)
• Sensed Parameters/Sensors
BlueCode
ExScal
heart rate (HR)
oxygen saturation
(SpO2)
EKG data
limb movements
muscle activity
Magnetic
detector
Acoustic detector
PIR detector
Alarm-Net
Pulse
SpO2
EKG
BP
Weight
Motions
OPM/UMMS
temperature;
humidity;
pressure;
carbon
monoxide(CO);
ozone(O3);
• Battery
BlueCode
Rechargable
120mAh lithium
polymer battery
ExScal
2x AA alkaline
batteries
Lead-acid battery
Alarm-Net
--
OPM/UMMS
Solar panel
Ni-Cad rechargeable
battery
Hardware (cont’d)
• Microprocessor
BlueCode
TI MSP430
ExScal
Atmel
Atmega128L
Alarm-Net
--
OPM/UMMS
ColdFire
• Radio
BlueCode
ExScal
Alarm-Net
ChipCon CC2420
ChipCon CC1000
ChipCon CC2420
OPM/UMMS
-802.11 or GSM
Software
• O.S. and Routing
BlueCode
TinyOS
ExScal
Linux
Publish/subscribe Grid routing;
routing layer;
Low power
Adaptive
listening;
Demand-Driven
Multicast Routing
(ADMR);
Discovery
protocol;
Alarm-Net
OPM/UMMS
Arm-Linux
WildFireMod
Refer to
BlueCode
--
Highlights
• Pluto: a wearable sensor design (BlueCode)
–
–
–
–
–
–
–
based on the Tmote Sky design
TI MSP430 microprocessor
ChipCon CC2420 radio
gigaAnt surface-mount antenna (inverted-F used on the Telos)
tiny rechargeable 120 mAh lithium polymer battery
Mini-B USB connector
100% compatible with Telos
Highlights (cont’d)
• Topology (ExScal)
– its networks are the
largest ones of either
type fielded to date
(Dec 2004)
– barrier coverage is
sufficient
– deploy sensors more
densely at the boundary
of the region than in its
interior
– detection criteria
– XSM & XSS
Highlights (cont’d)
• Atmel ATmega128L
microcontroller
• Chipcon CC1000 radio
• 4Mbit serial flash memory
• quad infrared, dual-axis
magnetic, and acoustic sensors
• weatherproof packaging
• Intel 400 MHz XScale
processor(PXA255)
• 2532W-B IEEE 802.11b card
• 64 MB SDRAM, 32 MB FLASH
• type II PCMCIA slot
• USB port, and 51-pin mote
connector;
• watertight packaging
Highlights (cont’d)
• SeeMote (Alarm-Net)
– Color display
– Removable data storage
(SD/MMC)
– Power consumption
meter
– Compatible with MICAz
and MICA2 motes
– Small size, lightweight
and low power
Highlights (cont’d)
• OPM/UMMS
– measure a variety of environmental factors from
multiple units, data can also be downloaded for users
to make their own calculations (i.e. MATLAB
integration).
– requires little maintenance: self-powering, hibernate
and wakeup mechanism, calibrated sensors can
function without replacement for at least two years
– allows for many administrative features; combination
of the Apache webserver, MySQL database, php code,
and python code, high performance data driven
applications
Reference
[1] Römer, Kay; Friedemann Mattern (December 2004). "The Design Space of
Wireless Sensor Networks". IEEE Wireless Communications 11 (6): 54-61. [2]Thomas Haenselmann (2006-04-05). "Sensornetworks". GFDL Wireless
Sensor Network textbook. Retrieved on 2006-08-29.
[3] Culler, D.; Estrin, D.; Srivastava, M., "Guest Editors' Introduction: Overview
of Sensor Networks," Computer , vol.37, no.8, pp. 41-49, Aug. 2004
[4] Victor Shnayder, Bor-rong Chen, Konrad Lorincz, Thaddeus R. F. FulfordJones, and Matt Welsh. Sensor Networks for Medical Care. Harvard
University Technical Report TR-08-05, April 2005.
[5] Specification of the ExScal Clean Point. http://cast.cse.ohiostate.edu/exscal/content/Requirements/Cleanpoint-2004-11-05.pdf
Reference (cont’d)
[6] Arora, A.; Ramnath, R.; Ertin, E.; Sinha, P.; Bapat, S.; Naik, V.; Kulathumani,
V.; Hongwei Zhang; Hui Cao; Sridharan, M.; Kumar, S.; Seddon, N.;
Anderson, C.; Herman, T.; Trivedi, N.; Nesterenko, M.; Shah, R.; Kulkami, S.;
Aramugam, M.; Limin Wang; Gouda, M.; Young-ri Choi; Culler, D.; Dutta, P.;
Sharp, C.; Tolle, G.; Grimmer, M.; Ferriera, B.; Parker, K., "ExScal: elements
of an extreme scale wireless sensor network," Embedded and Real-Time
Computing Systems and Applications, 2005. Proceedings. 11th IEEE
International Conference on , vol., no., pp. 102-108, 17-19 Aug. 2005
[7] Selavo, L., Wood, A., Cao, Q., Sookoor, T., Liu, H., Srinivasan, A., Wu, Y.,
Kang, W., Stankovic, J., Young, D., and Porter, J. 2007. LUSTER: wireless
sensor network for environmental research. In Proceedings of the 5th
international Conference on Embedded Networked Sensor Systems
(Sydney, Australia, November 06 - 09, 2007). SenSys '07. ACM, New York,
NY, 103-116.
Reference (cont’d)
[8] John A. Stankovic, “Dust to Doctors: WSN for Medical Applications,”
plenary speech, Tokyo, Japan, 2007.
http://www.cs.virginia.edu/wsn/medical/pubs/Tokyo-Plenary07.ppt
[9] George Bishop, Peter Dib, Brandi Pitta, and Noam Yemini, Opportunistic
Pollution Monitor (AKA: Urban Microclimate Monitoring System) MCL
Technical Report: TR-05-01-2007.
http://hulk.bu.edu/pubs/papers/2007/TR-05-01-2007.doc
The End
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