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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
A Wireless Sensor Network For Structural
Monitoring
(Wisden)
Sumit Rangwala
Collaborators: Ning Xu, Krishna Kant Chintalapudi, Deepak
Ganesan, Alan Broad, Ramesh Govindan, Deborah Estrin,
Jeongyeup Paek, Nupur Kothari
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Background
• Structural health monitoring (SHM)
– Detection and localization of damages in structures
» Structural response
• Ambient vibration (earthquake, wind etc)
• Forced vibration (large shaker)
• Current SHM systems
– Sensors (accelerometers) placed at different structure location
– Connected to the centralized location
» Wires (cables)
» Single hop wireless links
– Wired or single hop wireless data acquisition system
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Motivation
• Are wireless sensor
networks an alternative?
• Why WSN?
– Scalable
» Finer spatial sampling
– Rapid deployment
• Wisden
– Wireless multi-hop data
acquisition system
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Challenges
• Reliable data delivery
– SHM intolerant to data losses
• High aggregate data rate
– Each node sampling at 100 Hz or above
» About 48Kb/sec (10 node,16-bit sample, 100Hz, 3 axes)
• Data synchronization
– Synchronizing samples from different sources at the base station
• Resource constraints
– Limited bandwidth and memory
• Energy efficiency
– Future work
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Wisden Architecture
Challenges
Architectural
Component
Description
Reliable data
delivery
Reliable Data
Transport
Hybrid hop-by-hop
and end-to-end
error recovery
High data rate
Compression
Silence suppression
Wavelet based
compression
Data
Synchronization
Data
Synchronization
Residence time
calculation in the
network
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Reliable Data Transport
• Routing
Retransmission
– Nodes self-organize in a
routing tree rooted at the
base station
– Used Woo et al.’s work on
routing tree construction
• Reliability
– Hop-by-hop recovery
NACK
Retransmission
Retransmission
NACK
NACK
» How ?
• NACK based
• Piggybacking and
overhearing
» Why hop by hop?
• High packet loss
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Reliable Data Transport (cont.)
– End to End packet recovery
» How ?
• Initiated by the base station (PC)
• Same mechanism as hop-by-hop NACK
» Why ?
• Topology changes leads to loss of missing packet information
• Missing packet information may exceed the available memory
– Data Transmission rate
» Rate at which a node inject data
• Currently pre-configured for each node at R/N
– R = nominal radio bandwidth
– N = total number of nodes
» Adaptive rate allocation part of future work.
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Compression
• Sampled data significant
fraction of radio bandwidth
• Event based compression
Quiescent
Period
Event
Quiescent
Period
– Detect Event
» Based on maximum
difference in sample value
over a variable window size
– Quiescent period
» Run length encoding
– Non-quiescent period
» No compression
– Saving proportional to dutycycle of vibration
• Drawback
Compression
No
Compression
Compression
– High latency
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Compression For Low Latency
• Progressive storage and
transmission
Event
– Event detection
– Wavelet decomposition and
local storage
– Compression
» Low – resolution components
are transmitted
– Raw data, if required available
from local storage
• Current Status
– Evaluated on standalone
implementation
– To be integrated into Wisden
Flash
Storage
Wavelet
Decomposition
To sink on
demand
Quantization,
Thresholding,
Run length
coding
Sink
Low resolution
components
Reliable
Data
Transport
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Data Synchronization
•
Synchronize data samples at the
base station
TA=T-(qA + qB)
– Generation time of each sample in
terms of base station clock
– Network wide clock
synchronization not necessary
•
B
S
TC=T-(qC + qD)
D
Light-weight approach
– As each packet travels through the
network
A
C
» Time spent at each node
calculated using local clock and
added to the field “residence time”
» Base station subtracts residence
time from current time to get
sample generation time.
– Time spent in the network defines
the level of accuracy
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Implementation
• Hardware
– Mica2 motes
– Vibration card (MDA400CA
from Crossbow)
» High frequency sampling (up
to 20KHz)
» 16 bit samples
» Programmable anti-aliasing
filter
• Software
– TinyOS
– Additional software
» 64-bit clock component
» Modified vibration card
firmware
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Embedded Networks
Laboratory
UNIVERSITY OF
SOUTHERN CALIFORNIA
Deployment Scenario
1
• Seismic test structure
– Full scale model of an
actual hospital ceiling
structure
• Four Seasons building
– Damaged four-storey office
building subjected to
forced-vibration
1
Not presented in the paper
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Seismic Test Structure Setup
• Setup
– 10 node deployment
– Sampling at 50 Hz along three
axes
– Transmission rate at 0.5
packets/sec
– Impulse excitation using
hydraulic actuators
• For validation
– A node sending data to PC
over serial port (Wired node)
– A co-located node sending data
to the PC over the wireless
multihop network (Wisden
node)
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Results: Frequency Response
Power spectral density: Wisden node
•
•
Power spectral density: Wired node
Low frequency modes captured
High frequency modes lost
– Artifact of compression scheme we used
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Results: Packet Reception and Latency
• Packet reception
– 99.87 % (cumulative over
all nodes)
– 100 %, if we had waited
longer
• Latency
– 7 minutes to collect data for
1 minute of vibration
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Four Seasons Building
• Setup
– 10 node deployment
– Sampling at 50 Hz along
three axes
– Transmission rate at 0.5
packets/sec
– Excitation using eccentric
mass shakers
• For validation
– Wisden nodes places
alongside floor mounted
force-balance accelerometer
(Wired node)
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Results: Frequency Response
Power spectral density: Wisden Node
•
•
Power spectral density: Wired Node
Dominant frequency captured
Noise
– Sampling differences, force balanced accelerometer much more sophisticated,
packet losses
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Results: Packet Reception
• Packet reception
– High data loss
» Due to a bug
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UNIVERSITY OF
SOUTHERN CALIFORNIA
Embedded Networks
Laboratory
Conclusions and Future Work
• Wisden – A wireless data acquisition system that provides
– Reliable data collection
– Supports high sampling rate
– Data synchronization
• Future work
– Adaptive rate allocation scheme
– Integrating wavelet based compression
– Power efficiency
• Wisden version 0.1 available at
http://enl.usc.edu/
Thank you
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