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Wireless Sensor Network Research and Application Ning “Martin” Xu.

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Presentation on theme: "Wireless Sensor Network Research and Application Ning “Martin” Xu."— Presentation transcript:

1 Wireless Sensor Network Research and Application Ning “Martin” Xu

2 Content Introduction Comparison of WSN Projects – Hardware – Software – Highlights Reference

3 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

4 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

5 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

6 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

7 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

8 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

9 OPM / UMMS Increasing interest in the environment enable localized data monitoring using low- cost sensing individuals to acquire data about local smog (air pollution) conditions

10 Hardware Sensor Nodes / Boards BlueCodeExScalAlarm-NetOPM/UMMS Pulse oximeter ( Mica2 / MicaZ); EKG (Mica2 / MicaZ, Telos); Motion analysis sensor board (Telos); ** Pluto (based on Tmote Sky); MicaZ; ** eXtreme Scale Mote (XSM); ** eXtreme Scale Stargate (XSS); Mica2 MicaZ; Telos Sky; ** SeeMote; Satire body network (MicaZ, MTS310 sensor board); --

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14 Hardware (cont’d) Sensed Parameters/Sensors Battery BlueCodeExScalAlarm-NetOPM/UMMS heart rate (HR) oxygen saturation (SpO2) EKG data limb movements muscle activity Magnetic detector Acoustic detector PIR detector Pulse SpO2 EKG BP Weight Motions temperature; humidity; pressure; carbon monoxide(CO); ozone(O3); BlueCodeExScalAlarm-NetOPM/UMMS Rechargable 120mAh lithium polymer battery 2x AA alkaline batteries Lead-acid battery --Solar panel Ni-Cad rechargeable battery

15 Hardware (cont’d) Microprocessor Radio BlueCodeExScalAlarm-NetOPM/UMMS TI MSP430Atmel Atmega128L --ColdFire BlueCodeExScalAlarm-NetOPM/UMMS ChipCon CC2420ChipCon CC1000ChipCon CC2420-- 802.11 or GSM

16 Software O.S. and Routing BlueCodeExScalAlarm-NetOPM/UMMS TinyOSLinuxArm-LinuxWildFireMod Publish/subscribe routing layer; Adaptive Demand-Driven Multicast Routing (ADMR); Discovery protocol; Grid routing; Low power listening; Refer to BlueCode --

17 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

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19 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

20 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

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22 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

23 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

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26 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. Fulford- Jones, 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.ohio- state.edu/exscal/content/Requirements/Cleanpoint-2004-11-05.pdf

27 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.

28 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

29 The End THANK YOU!


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