Sniper Detection Using Wireless Sensor Networks
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1 Sniper Sniper Detection Using Detection Using Wireless Sensor Wireless Sensor Networks Networks Joe Brassard Joe Brassard Wing Siu Wing Siu EE-194WIR: Wireless Sensor EE-194WIR: Wireless Sensor Networks Networks Presentation #2: March 1st, Presentation #2: March 1st, 2005 2005
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Presentation “Bullet” Points To examine wireless sensor networks at an application level, as opposed to only low-level discussion To learn about the BBN “Boomerang” and “Bullet Ears” detection systems To introduce the “PinPtr” system by Vanderbilt University, including a system-level explanation of the sensor network Went over peer comments – our goal is to have an application-level overview of wireless sensor networks. We feel that this is important because we often do not cover applications in detail. Also, since many projects here are low level in nature, we feel it would be a good change of pace in this class. Our goal for this presentation is to give an introduction to two systems: BBN and their Boomerang and Bullet Ears systems PinPtr We will do more low level discussion in the third presentation, so stay tuned if you have questions on that
Transcript of Sniper Detection Using Wireless Sensor Networks
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Sniper Detection Sniper Detection Using Wireless Sensor Using Wireless Sensor
NetworksNetworksJoe BrassardJoe Brassard
Wing SiuWing SiuEE-194WIR: Wireless Sensor NetworksEE-194WIR: Wireless Sensor Networks
Presentation #2: March 1st, 2005Presentation #2: March 1st, 2005
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Presentation “Bullet” Points To examine wireless sensor networks at an
application level, as opposed to only low-level discussion
To learn about the BBN “Boomerang” and “Bullet Ears” detection systems
To introduce the “PinPtr” system by Vanderbilt University, including a system-level explanation of the sensor network
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Applications Numerous systems exist in various stages
of deployments BBN Boomerang system is currently
deployed in Iraq
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BBN Boomerang Uses Humvee-mounted tetrahedral arrays to
sense muzzle blast and shockwave Eventual system deployment will be fully wireless,
allowing every commander in Baghdad to be aware of any sniper attacks, anywhere in the city
Modified version of the “Bullet Ears” system
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“Bullet Ears” Developed in 1996 as
part of a DARPA contract
Several versions for multiple scenarios Hardwired RF Wearable
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Possible Scenarios
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BBN’s Issues Data
Might get too much or might not get enough Flexibility
Easy to reconfigure, upgrade, setup
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Data Solutions Spatially distributed system
Wider area of coverage Less bandwidth (< 8kHz bandwidth) Localized processing
Flexible algorithm If more data is received, more information can be
determined If not, determine as much as possible
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Flexibility Solutions Use all COTS
components Allows integration with
other components
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“PinPtr” By Vanderbilt Ad-Hoc Network Accuracy within 1m, Latency < 2 seconds
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PinPtr in Action Overhead sensor layout for shooter localization 3D model of same shooter location
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Technical Data 50 Mica2 motes with customized sensor
board Timestamp of
shockwave/muzzle blast sent to board
Motes send TOA data to base station
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Flooding Time Synch Protocol (FTSP) Requirements:
Sound travels at one foot per millisecond Time Synchronization error in entire network must be <
1msec Algorithm:
Each node has separate global and local time Simple integrated leader election Network global time is synchronized to leader’s local time Message is time stamped in the radio stack Receivers update global time and rebroadcast it Motes keep last 10 local and global time pairs and perform
linear regression If leader is lost, new leader is elected
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Flooding Time Synch Protocl (FTSP), Continued Performance:
Constant network load: 1 message per 30 seconds per mote
Topology change tolerate: motes can move at speeds less than 1 hop per 30 seconds
End-to-end accuracy: Average 1.6us per hop
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Directed Flood Routing Framework (DFRF) Requirements:
Acoustic events trigger many motes at once
All need to get data to base station with low latency
Mote bandwidth: 20-25 messages per second
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Directed Flood Routing Framework (DFRF), Continued Ad-hoc routing Automatic aggregation Implicit acknowledgements Configurable flooding policy
Defines gradient Controls retransmission
Converge cast to root Table/cache management Very low overhead When max distance from root is 5, base station receives ~15
measurements in the first second
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Directed Flood Routing Framework (DFRF), Continued Data Packet:
Fixed length Appid + “rank” = 3 bytes Must contain a unique part
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RITS: Routing Integrated Time Synch Combination of Time Synch
and Message Routing No extra messages “Stealth” operation Uses time stamping module
that has 1.4us average precision per hop
No clock skew estimation Precision depends on the hop
count of the route and on the total routing time
Plug-in replacement for the DFRF
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For Next Time In-depth, low-level analysis of Time
Synchronization (FTSP) and Message Routing (DFRF)
Detailed performance results and observations of the PinPtr sniper-detection system
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References Ledeczi, et. al. “Sensor Network Based Counter
Sniper System” (Vanderbilt) Ledeczi, et. al. “Network Embedded Systems
Technology (NEST) – Shooter Localization” (Vanderbilt)
Ledeczi, et. Al. “Pattern-Oriented Composition and Synthesis of Middleware Services for NEST” (Vanderbilt)
www.bbn.com (BBN Technologies, Inc.)
