thThe 14 World Conference on Earthquake Engineering
October 12-17, 2008, Beijing, China

Actual Application of Ubiquitous Structural Monitoring System using WirelessSensor Networks
1

2

3

Narito Kurata , Makoto Suzuki , Shunsuke Saruwatari and Hiroyuki Morikawa

4

1Supervisory Research Engineer, Kobori Research Complex, Kajima Corporation, Japan
Visiting Researcher, Research Center for Advanced Science and Technology, The University of Tokyo, Japan
2
Graduate Student, Research Center for Advanced Science and Technology, The University of Tokyo, Japan
3
Research Associate, Research Center for Advanced Science and Technology, The University of Tokyo, Japan
4
Professor, Research Center for Advanced Science and Technology, The University of Tokyo, Japan
Email: kuratan@kajima.com
ABSTRACT :Ubiquitous structural monitoring (USM) of buildings using wireless sensor networks is one of the mostpromising emerging technologies for mitigation of seismic hazard. This technology has the potential to change
fundamentally the traditional monitoring systems. This paper provides an introduction of wireless sensor
network technology for the USM, and reported research activity on development of sensor module. The sensor
board which is equipped with the MEMS acceleration sensor selected by the benchmark test was developed andtested. The sensor module which consists of the sensor board and wireless network module was tested byshaking table. It was confirmed that the developed sensor module had enough basic performance for the USM.
The USM system which consists of developed sensor modules and PC was installed in a high-rise building. The
building’s vibration by typhoon was monitored and basic performance of the USM system was verified.
KEYWORDS:

Ubiquitous Computing, Structural Health Monitoring, Wireless Sensor Networks,
Wind Observation, Earthquake Observation, Smart Sensor

1. INTRODUCTION
Risk of buildings and civil engineering structures from natural hazards is large and growing. The 1995 Kobe
earthquake in Japan killed over 6,400 people and the number of completely destroyed buildings and houses wasover 100,000. The 2004 and 2007 Niigata earthquake in Japan, tsunami by the 2004 Indian Ocean earthquake,and the 2005 Hurricane Katrina in New Orleans caused heavy damage. Wireless sensor network (WSN) is key
technology to realize the ubiquitous computing and networking environment [Morikawa 2005] and it isexpected that such an advanced technology will play an important roll for natural hazard mitigation [Kurata etal. 2005]. In this paper, research on ubiquitous structural monitoring (USM) of buildings by using wirelesssensor networks is introduced and actual application to high-rise building is described.
2. WIRELESS SENSOR NETWORK TECHNOLOGY
The general purpose of structural monitoring includes hazard mitigation, improvement of safety and reliabilityof the structural system, sustainability and life cycle cost reduction. The structural monitoring technology
consists of sensing, signal processing, health/damage evaluation, and system integration. In recent years a
number of conferences have been held in which structural health monitoring for buildings and civil engineering
structures has been presented. Some of this work has focused on wireless sensing technology. A wirelesssensing unit for real-time structural response measurements has been developed and a series of validation tests
have been conducted [Lynch 2002].
“Ubiquitous sensing and computing” is expected to be realized over the next ten years. The interest insensing technology for various uses has been growing, and new kinds of sensors have been developed by microelectro mechanical systems (MEMS) technology. Environmental information, such as brightness, temperature,sound, vibration, and a picture of a certain place in a building, is evaluated by the network to which a huge
number of microcomputer chips with sensors were connected [Morikawa 2005]. A wireless sensor networkth

The 14 World Conference on Earthquake Engineering
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plays an important role and can be connected to the internet so that this information can be used to monitor
structures. Wireless sensors are easy to install, remove, and replace at any location, and are expected to become
increasingly smaller (i.e., “smart dust”, [Pister et al. 1999]) by using MEMS technology. They will provide aubiquitous networked sensing environment in building and civil engineering structures. For example, theacceleration and strain at numerous locations on each structural members, temperature and light in each space,images and sounds in desired regions can be obtained by the “smart dust” sensors.
The requirement of a dense array of smart sensors using wireless technology for structural monitoring has
been investigated by using the Mote platform [Spencer et al. 2004, Ruiz-Sandoval 2004, Kurata et al. 2005,
Gao 2005, Nagayama 2007, Gnawali et al. 2006]. It is an open hardware and software platform for smart
sensing and supports large scale, self-configuring sensor networks. Ruiz-Sandoval developed an agent-based
framework which is a hardware or software-based computer system that enjoys the properties of autonomy,social ability, reactivity, and pro-activeness for structural health monitoring [Ruiz-Sandoval 2004]. A
distributed computing strategy for structural health monitoring was proposed which is suitable for
implementation on a network of densely distributed smart sensors [Gao 2005]. A scalable and autonomous
structural health monitoring system using smart sensors was developed and the damage detection capability andautonomous operation of the developed system were experimentally verified [Nagayama 2007]. Tenetarchitecture which simplifies application development for tiered sensor networks without significantly
sacrificing performance was proposed [Gnawali et al. 2006]. Its collections of tasklets support data acquisition,
processing, monitoring, and measurement functionality. A wireless sensor system using the Mote platform witha developed sensor board was tested on the 4200 ft long main span and the south tower of the Golden Gate
Bridge [Kim et al. 2007]. Reference [Lynch and Loh 2006] is a summary review of the collective experience
the structural engineering community has gained from the use of wireless sensors and sensor networks formonitoring structural performance and health.
3. UBIQUITOUS STRUCTURAL MONITORING SYSTEM
One of the main purposes of the structural health monitoring is a damage detection of the structure. Because thestructural damage is a local phenomenon, a Ubiquitous Structural Monitoring (USM), i.e., high density
distributed structural monitoring is essentially needed as shown in Figure 1 [Kurata et al. 2005, Kurata et al.
2006]. A wireless sensor network and a fiber optic network will exist together in future building and manykinds of sensors will connected to the network. From this point of view, the authors have conducted research on
wireless sensor network architecture for USM in the next generation, which includes a design of hardware anddevelopment of operating system [Saruwatari et al. 2005, Horie et al. 2004].
Wireless sensor network
acceleration/strain/temperature/light/
image/sound/etc.
Fiber optic network
acceleration/strain/etc.

Internet
Main server/base station

Figure 1 Ubiquitous structural monitoring in buildingth

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3.1. Sensor Module for Ubiquitous Structural Monitoring
Developed sensor module for USM consists of sensor board and wireless network module as shown in Figure 2.
The sensor board consists of MEMS acceleration sensor, low pass filter and 16 bit A/D converter. 2 MB SRAM
is also installed on the sensor board. A platform for wireless sensor networks called Pavenet [Saruwatari et al.
2005] was connected to the developed sensor board. Pavenet module is equipped with a CPU, Microchip
PIC18LF4620, and an RF module, Texas Instruments CC1000. Pavenet OS is a hard-realtime operating system
for Pavenet module. Required performance of sensor module for USM is listed as shown below.
Sensor board
x-axisMEMS
acceleration
y-axissensorz-axisLow pass filter
Low pass filter

16bit
A/D

Wireless
network
moduleLow pass filter

Figure 2 Sensor module for USM
3.1.1 Measurement
Required specifications for acceleration measurement are shown in Table 1. It shows a performance necessary
for general seismic observation and vibration measurement of buildings from the moderate earthquake to alarge earthquake and typhoon.
Table 1 Required specifications
Frequency range
0.1～20Hz
Measuring range±2000 Gal
Measuring resolution
1 Gal
A/D resolution
16 bitSampling frequency
100 Hz3.1.2 Time synchronization
Time synchronization among sensor modules is required to analyze the collected data for structural monitoring.
In this system, time synchronization within 1 ms will be sufficient for sampling period of 10 ms and target
frequency range of natural period of buildings and dominant period of earthquakes.
3.1.3 Detection of vibration
Sensor modules continuously observe acceleration and correct zero value by average of 1024 sampled data.
After the correction of zero value, RMS value of 256 sampled data is calculated for detection of vibration.
Though the selected MEMS acceleration sensor is influenced by fluctuation of temperature in environment, thisinfluence could be ignored for measurement during earthquake.
3.1.4 Data transmission
Data loss caused by wireless communication should be considered. Transmission of measured data stored in
SRAM on each sensor node is repeated after setting time of 50 ms. All of measured data by sensor modules iscollected without loss in this system.
3.2. Benchmark test of MEMS acceleration sensors
The MEMS acceleration sensor was examined for the development of the acceleration sensor board that can beconnected with such a wireless network module. Performance of various MEMS sensors is usually confirmed
only in the frequency range of 10 Hz or more, though the performance in the low frequency range from 0.1Hz
is important intended for the vibration measurement of high-rise building and the observation of long period
ground motion. Therefore, the benchmark test of the MEMS acceleration sensors carried out in this study.
Table 1 shows the specifications of the MEMS acceleration sensors. Analog Devices ADXL202 is low

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cost and used for the standard sensor board for the MICA Mote, however, noise density is large and sensitivity
is low as shown in Table 2. SILICON DESIGNS Model1221 is already investigated and tested for the structural
health monitoring [Ruiz-Sandoval 2004]. It is listed just as a reference in this case because of the higher cost
and the limitation of 1 axis measurement.
Table 1 Specifications of MEMS acceleration sensors
Name

Axis

H48C
MXS2200E
LIS3L02AQ

3
2
3

Max
G
3
1
2

JA30SA32-25B

3

1.5

Model1221

1

2

Noise
Density
1.8mg rms
0.2mG/√Hz
50µG/√Hz
0.049
Gal rms/√Hz
5µG/√HzADXL2022

2200µG/√Hz

Power
Supply2.2-3.6
2.7-5.25
2.4-3.6

Sensitivity(mV/G)
333
2000
660

4.75-5.25
4.75-5.25
3-5.25-25～75-40～85-40～85Size(mm)
4.8×4.8×1.5
5×5×2
7×7×1.8

1000-10～60

14×11×5

2000
167(3V)
312(5V)-55～85

3.5×3.5×1.05-40～855×5×2

Temperature

The MEMS acceleration sensors, Hitachi H48C, MEMSIC MXS2200E, ST Microelectronics LIS3L02AQ,
Japan Aviation Electronics Industry JA30SA32-25B, SILICON DESIGNS Model1221, and the traditional
acceleration sensor as a reference, were fixed on the shaking table and carried out the benchmark test. The
shaking table is 1.8m×1.5m and can be excited according to the sine wave and the external input wave. In thetest, the swept sine wave with 0.2 to 20 Hz was input to the shaking table. Fourier spectrum ratio of themeasurement result of each MEMS acceleration sensor and the reference sensor was shown in Figures 3 to 6.
H48C shows linear characteristics on amplitude and phase, however, noise performance is low. Though
MXA2200E has a good sensitivity, it shows strong non-linearity. LIS3L02AQ and JA30SA32-25B has a good
performance on amplitude, however, phase lag was observed in the results of JA30SA32-25B. Model1221
shows the best performance and LIS3L02AQ has an equivalent performance with Model1221. Finally,
LIS3L02AQ was selected as the MEMS acceleration sensor for the sensor board.

0

00
-45

5

10
10

15

2020

00

10
10

5

15

5

10
10

Figure 3 H48C

00

5

10
10
Frequency(Hz)
(Hz)

15

2020

45

00

-45

-90
00

00

10
10

15

20
20

10
10
15
Frequency(Hz)
(Hz)

20
20

5

Frequency(Hz)
(Hz)

90
90

Phase
(degree)PhaselagLag(degree)

Amplitude
ratio
Amplitude
Amplitude ratio

Amplitude ratio
Amplitude

Phase
lag
(degree)Phase
Lag(degree)

0

0

2020

22

90

11

15

Figure 4 MXA2200E

90

22

-45

Frequency(Hz)(Hz)

Frequency(Hz)(Hz)

Frequency(Hz)
(Hz)

00

-90

00

20
20

45

-90

0

-90

00

11

0

-90

0

Phase
lag (degree)
Phase Lag(degree)

45

Amplitude

Amplitude ratio

Phase Lag(degree)

Phase lag (degree)

Amplitude
Amplitude ratio

11

90
90

22

90
90

22

11

0
0

-90

10
10

5

Frequency(Hz)(Hz)

Figure 5 LIS3L02AQ

15

20
20

45
00

-45

-90

00

5

10
10

15

Frequency(Hz)
(Hz)

2020

-90

00

5

Figure 6 A30SA32-25B

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The 14 World Conference on Earthquake Engineering
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3.3. Developed sensor board and performance test
The authors developed sensor board equipped with selected MEMS acceleration sensor, low pass filter, 16 bit
A/D converter and 2MB SRAM (see Photograph 1). Shaking table test was carried out to recognize theperformance of developed sensor board. Ten sensor boards and reference acceleration sensor were fixed on the
shaking table as shown in Photograph 2. In the test, the swept sine wave with 0.2 to 20 Hz was input to theshaking table. Fourier amplitude spectrum ratio of the measurement result of each developed sensor board andthe reference sensor was shown in Figure 7. The measurement result by the sensor board is corresponding to theresult by the reference sensor well.

Amplitude ratio

2
1.5
1
0.5
0
0

Photograph 1 MEMS acceleration sensors

10

20 (Hz)Figure 7 Fourier amplitude spectrum ratio

3.4. Ubiquitous Structural Monitoring System
The USM system consists of a sink node with a PC and sensor nodes as shown in Figure 8. The sink nodemanages time synchronization among the sensor nodes, detection of vibration and data transmission. It
broadcasts time information periodically, and sensor nodes adjust their local clock according with received
information. The sensor nodes continue to measure acceleration and store the data in SRAM on them. When thesink node detects the vibration and recognizes the end of it, then, the sensor nodes begin to send measured data
to the sink node wirelessly. Finally, the sink node stores the received data to the PC.

Sink nodeSensor nodes

Figure 8 Ubiquitous Structural Monitoring System
Shaking table test was carried out to recognize the performance of developed USM system. A sink nodeconnected to PC, ten sensor nodes, and traditional acceleration sensor as a reference, were fixed on the shaking
table. In the test, the swept sine wave with 0.2 to 20 Hz was input to the shaking table. Figure 9 shows
comparison between measurement results of developed sensor node and reference sensor. The result of sensor
node gave good agreement with the one of reference sensor. Accurate sampling frequency of 100 Hz was
realized. Fourier amplitude spectrum ratio of the measurement result of each developed sensor nodes and thereference sensor was shown in Figure 10. The amplitude characteristic of all sensor nodes is almost equal to thereference sensor. Figure 11 shows Fourier phase spectrum ratio of the sensor nodes and the sink node. No phaselag was recognized and time synchronization among sensor nodes was less than 1 ms.

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October 12-17, 2008, Beijing, China(cm/sec2）

150100

比較用センサReference

センサノードSensor
node

50
0
-50
-100
-150
0.50

0.55

0.60

0.65

0.70

0.75

0.80 (sec)

2

Phase
lag (degree)
位相遅れ(degree)

振幅比

Amplitude ratio

Figure 9 Comparison between developed sensor node and reference

1.5
1
0.5
0
0

10

180
90
0
-90
-180
0

20 (Hz)Figure 10 Fourier amplitude spectrum ratio

10

20 (Hz)Figure 11 Fourier phase spectrum ratio

4. ACTUAL APPLICATION OF UBIQUITOUS STRUCTURAL MONITORING SYSTEM
4.1. Applied high-rise building
We applied the USM system which consists of a sink node and sensor nodes to actual high-rise building forverification of performance of the system in real apace. Applied 31-story office building is located in front of
Akihabara station in Tokyo and is expected to be a new focal point for the Akihabara district, holding areas for
Industry-Academia Collaboration, information networking, and attractions for visitors. We installed the USM
system in rooms on the 13th and 6th floors in this building as shown in Figure 12.

①②(a) General view(b) Plan on 13th and 6th floor(c) Installation of sensor node

Figure 12 Applied high-rise building and installation of sensor node
4.2. Vibration detection test by sink node during typhoon
Vibration detection test by the sink node had been carried out in the room ① on the 13th floor in 2007. The
vibration of the building during typhoon No. 20 was monitored by installed sink node on October 27th in 2007.
The sink node detected the small vibration caused by the typhoon and collected the acceleration data. Figure 13
shows x and y axes acceleration record measured by the sink node and their orbit. Their Fourier amplitudeth

The 14 World Conference on Earthquake Engineering
October 12-17, 2008, Beijing, China

2 2 (a) x-axis
1

00

20

-1

-2 0 01010
2 2 (b) y-axis
-2

20
20

30
30

40
40

50
50

2000

x direction

1800

60 (s)
60

1600

1

00

1400

-1

-2 0 0
-2

10
10

20
20

30
30

40
40

50
50

60 (s)
60221.5(c) x-y axis orbit(cm/sec)y-axis acceleration(cm/sec2)(cm/sec2)(cm/sec2)

spectrum was shown in Figure 14. In this case, the direction of main vibration of this building was x-direction.
Such small vibration, ±2 cm/sec2, in low frequency domain, could be detected and monitored by the sinknode. Peaks of the first mode in x and y axis were 0.3 Hz and 0.34 Hz, respectively.

y direction

1200

10 1000
800

1
0.5

600

00
400

-0.5
-1

200

-1.5

-2

-2
-4

-4

-3

-2

-2

-1

0

0

1

2

x-axis acceleration (cm/sec2)

3

2

0 00
0

4

4

Figure 13 Acceleration record and orbit

0.1

0.2

0.3

0.4

0.5

0.5

0.6

0.7

0.8

0.9

1

1.0 (Hz)

Figure 14 Fourier amplitude spectrum

5

2.5

-5
5

(c) y-axis of sensor node

0-5

(cm/sec2)(a) Applied room

(cm/sec2)

0

Floor

Story drift angle of 1/2000(b) x-axis of sensor node

0

20

5

40

60

80

100 (s)(d) x-axis of sink node0-55(e) y-axis of sink nodey-axis story drift (mm)(cm/sec2)

Ceiling(cm/sec2)

4.3. Story drift based structural monitoring for earthquake
Story drift based structural monitoring has been carried out in the room ② on the 6th floor. The sink node andsensor node were installed on the floor as shown in the Figure 12(c) and on the ceiling, respectively. The
vibration of the building during earthquake occurred on August 8th in 2008 was monitored. The sink noderealized the time synchronization with the sensor node. The sink node detected the vibration caused by theearthquake and collected the acceleration data from the sensor node after the vibration without data loss. That
was minimum system configuration, however, basic function of applied USM system described 3.4 wasrecognized. Figure 15 shows x and y axes acceleration data measured by the sink node and the sensor node.
Displacement data was evaluated by double integral of acceleration data and story drift was calculated bydifference between displacement data of the sink node and the sensor node. Orbit of story drift was shown in
Figure 16. According to the Japanese design code for high-rise building, structural members are expected toremain within elastic range for story drift angle of 1/200 or less. It was recognized that the story drift angle
during the earthquake remained within 1/2000, therefore, in this case, no damage was evaluated in this space.

0

-2.5
-2.5

0

0

2.5

x-axis story drift (mm)

-5
0

20

40

Figure 15 Acceleration data60

80

100 (s)Figure 16 Orbit of story drift

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The 14 World Conference on Earthquake Engineering
October 12-17, 2008, Beijing, China

5. CONCLUSIONSThis paper reported research activity on development of sensor module. The sensor board which is equippedwith the MEMS acceleration sensor selected by the benchmark test was developed and tested. The sensor
module which consists of the sensor board and wireless network module was tested by shaking table. It was
confirmed that the developed sensor module had enough basic performance for the USM. The USM system
which consists of developed sensor modules and PC was installed in a high-rise building. The building’s
vibration during earthquake was monitored and basic performance of the USM system was verified.
ACKNOWLEDGMENT
The authors gratefully acknowledge the partial support of this research by the Ministry of Internal Affairs andCommunications. The authors would like to express their gratitude to Mr. N. Adachi of Kajima TechnicalResearch Institute for implementing the shaking table tests.
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October 12-17, 2008, Beijing, China