ShakeNet: A Portable Wireless Sensor Network for 

Instrumenting Large Civil Structures

By Monica D. Kohler, Shuai Hao, Nilesh Mishra, Ramesh Govindan, and Robert Nigbor

Open-File Report 2015–1134

U.S. Department of the Interior 

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

For more information on the USGS—the Federal source for science about the Earth,

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Although this information product, for the most part, is in the public domain, it also may

contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items

must be secured from the copyright owner.

Suggested citation:

Kohler, M.D., Hao, S., Mishra, N., Govindan, R., and Nigbor, R., 2015, ShakeNet—A portable wireless sensor 

network for instrumenting large civil structures: U.S. Geological Survey Open-File Report 2015–1134, 31 p., 

http://dx.doi.org/10.3133/ofr20151134.

ISSN 2331-1258 (online)
iii

Acknowledgments

This work was funded by U.S. Geological Survey National Earthquakes Hazards Reduction Program Award 

Numbers G09AP00101 and G09AP00102. We acknowledge intellectual support from the Reftek engineers who 

were involved at every level of these development efforts. We are also grateful for reviews from John Evans and 

Tat Fu and editing by Jessica Dyke that greatly strengthened this report.
iv

Contents

Executive Summary.................................................................................................................................................... 1

Introduction................................................................................................................................................................. 1

ShakeNet Overview ................................................................................................................................................ 1

ShakeNet Design .................................................................................................................................................... 2

Deployment Environment........................................................................................................................................ 4

System Description..................................................................................................................................................... 5

ShakeNet Software: Tenet...................................................................................................................................... 5

ShakeNet Hardware: ShakeBox.............................................................................................................................. 8

Laboratory Testing and Experiments .......................................................................................................................... 9

FFT (Fast Fourier Transform) and Channel Analysis With Function Generator ...................................................... 9

Shake Table Test.................................................................................................................................................. 10

Millikan Library Test .............................................................................................................................................. 14

Prototype Deployments in Structures ....................................................................................................................... 18

Deployment of Instruments During Early Development......................................................................................... 18

ShakeNet Prototype Deployments ........................................................................................................................ 19

1100 Wilshire Boulevard Building...................................................................................................................... 22

Seven Oaks Dam.............................................................................................................................................. 27

Summary and Conclusions....................................................................................................................................... 30

References Cited...................................................................................................................................................... 30

Figures

 1. ShakeBox hardware block diagram. ADC, Analog-to-Digital Converter. I2C, Inter-Integrate Circuit. The 

imote-2 is also referred to as the Imote2 in the text....................................................................................... 3

 2. Schematic illustrating Tenet architecture. A lower tier consists of motes and an upper tier consists of 

masters. MAC, medium access control. Tenet incorporates the Flooding Time Synchronization Protocol 

(FTSP) for time synchronization. ................................................................................................................... 5

 3. Photographs of the ShakeBox components. A, ShakeBox with weatherproof enclosure; six-inch ruler 

shown for scale. B, Placement of modules with 6-inch ruler shown for scale. C, Connection between 

individual modules: a, Central Processing Unit (CPU) module with Imote2; b, power module; c, Analog-toDigital Converter (ADC) module. ................................................................................................................... 8

 4. Graphs showing FFT (Fast Fourier Transform) analysis of input function generator frequency sweep from 

0.2 to 125 Hz (hertz) with 1 Vpp (volt peak-to-peak) amplitude. Negative frequencies are also plotted by 

default.......................................................................................................................................................... 10

 5. Photographs showing shake table equipment and instrumentation setup. A, Shake table top showing 

mounted steel plate with Dytran piezoelectric and Colibrys MEMS accelerometers, and additional 

ShakeBox components on chair. B, Closeup of mounted plate with accelerometers. C, 24-bit digitizer and 

PC recording setup for Dytran accelerometers............................................................................................ 11

 6. A, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with Dytran piezoelectric 

accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the Colibrys 

Channel 2 direction with 1 Hz sine wave input............................................................................................. 12

 6. B, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with Dytran piezoelectric 

accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the Colibrys 

Channel 2 direction with 5 Hz sine wave input............................................................................................. 13
v

 6. C, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with Dytran piezoelectric 

accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the Colibrys 

Channel 2 direction with 25 Hz sine wave input........................................................................................... 14

 7. Photographs showing Robert A. Millikan Memorial Library, shaker, and sensors that were tested. A, Robert 

A. Millikan Memorial Library on the Caltech campus, viewed from the northeast. B, Kinemetrics VG-1 

eccentric-mass shaker located on the roof of Millikan Library. The counter-rotating buckets, shown empty, 

can be loaded with different configurations of lead weights to impart different forces on the building. C, 

Accelerometers located in the basement that were recording during the Millikan shake test. The ShakeBox 

is the small black box with the orange triangle symbol on top, behind the blue box. ................................... 16

 8. A, Graphs showing acceleration responses due to forced vibrations recorded by the ShakeNet 

ShakeBoxes collocated with an Episensor in the basement of Millikan Library, California Institute of 

Technology.................................................................................................................................................. 17

 8. B, Graphs showing acceleration responses due to forced vibrations recorded by the ShakeBoxes 

collocated with an Episensor on the 9th floor of Millikan Library, California Institute of Technology............. 18

 9. A, Vincent Thomas Bridge, Los Angeles Harbor, California. B, ShakeNet prototype deployment across part 

of the bridge deck. ....................................................................................................................................... 20

10. Graph showing accelerations recorded during the deployment at Vincent Thomas Bridge, Los Angeles, 

California, in July 2006. Vertical accelerations have been bandpass filtered for frequencies between 0.2 

and 5.0 Hz. .................................................................................................................................................. 21

10. Graph showing spectra of accelerations recorded during the deployment at the Vincent Thomas Bridge, 

Los Angeles, California, in July 2006........................................................................................................... 22

11. Photo and SketchUp diagram of the 1100 Wilshire Boulevard building in Los Angeles, California.......... 23

12. A, Spectra from a 1-hour section of horizontal component waveforms from 30 ShakeBoxes deployed in 

stairwells on various floors arranged from bottom to top of building (bottom to top of figure) at 1100 Wilshire 

Boulevard, Los Angeles, California. Numbers overwriting file name in left-hand column indicate amplitude 

normalization factor. .................................................................................................................................... 25

12. B, Spectrogram from a section of horizontal component data recorded by a ShakeBox deployed on the 36th

floor, from the test deployment in the building at 1100 Wilshire Boulevard, Los Angeles, California........... 26

13. Seven Oaks Dam in Highland, California. A, Aerial view. Picture taken on February 8, 2005, by Steve 

Schumaker. B, Example ShakeBoxes deployed on crest of dam. C, Network configuration showing 

locations (red squares) of the 31 seismometers. ......................................................................................... 27

14. Ambient vibration spectra from transverse direction (channel 2, north-south orientation) produced from 

several hours of acceleration data recorded during one of the deployment days at Seven Oaks Dam in 

Highland, California. Numbers overwriting file name in left-hand column indicate amplitude normalization 

factor............................................................................................................................................................ 29

Tables

1. Floors with sensors in the 1100 Wilshire Boulevard building deployment, Los Angeles, California. ............ 24

2. Locations of sensors and associated clusters during Seven Oaks Dam deployment. Sensors on crest road 

are listed in increasing distance order from westernmost to easternmost end and are approximately 120 

feet apart. See also figure 13....................................................................................................................... 28
vi

Abbreviations

ADC Analog-to-Digital Converter

ANSS Advanced National Seismic System

BOINC Berkeley Open Infrastructure for Network Computing

CPU Central Processing Unit

CSN Community Seismic Network

EEPROM Electrically Erasable Programmable Read-Only Memory

FPGA Field-Programmable Gate Array

FTSP Flooding Time Synchronization Protocol

GPS Global Positioning System

JTAG Joint Test Action Group

LED Light Emitting Diode

MAC Medium Access Control

MDA Mono Class D Amplifier

MEMS Micro-electroMechanical Systems

NTP Network Time Protocol

QCN Quake-Catcher Network

Reftek Refraction Technology, Inc.

SDRAM Synchronous Dynamic Random Access Memory

SEL Module Selection

SPI Serial Peripheral Interface

USB Universal Serial Board

USGS U.S. Geological Survey
ShakeNet: A Portable Wireless Sensor Network for 

Instrumenting Large Civil Structures

By Monica D. Kohler,1 Shuai Hao,2 Nilesh Mishra,

2 Ramesh Govindan,2 and Robert Nigbor3

Executive Summary

We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards 

Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up 

to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to 

record ambient vibrations for several days from USGS-instrumented structures. Structural health

monitoring has important applications in fields like civil engineering and the study of earthquakes. The 

emergence of wireless sensor networks provides a promising means to such applications. However, 

while most wireless sensor networks are still in the experimentation stage, very few take into 

consideration the realistic earthquake engineering application requirements. To collect comprehensive 

data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient 

sampling rates should be adopted, which makes it challenging for current wireless sensor network 

technology in the following ways: processing capabilities, storage limit, and communication bandwidth. 

The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the 

structural health monitoring community. For this project, we built and tested an application-realistic, 

commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large 

civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can 

deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the 

building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform 

(ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments 

reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped 

to refine both hardware and software.

Introduction

ShakeNet Overview

ShakeNet is a multi-tier, portable, vibration sensing system of tens of wireless nodes that can be 

rapidly deployed by two to three people on large civil structures, for example, tens of floors of a large 

building or tens of locations on a long bridge. It was designed to collect structural vibration 

measurements for up to a week from each node within the network. This portable system can be used to 

quickly (within 3−5 hours) instrument large structures immediately after an earthquake to capture 

 1

California Institute of Technology

2

University of Southern California

3

University of California, Los Angeles
2

aftershock and ambient motions. Because ShakeNet is portable, it can also be used at other times to 

understand the structural properties of different classes of structures (steel-frame versus reinforcedconcrete buildings). Each of the wireless sensor nodes (called ShakeBoxes) is equipped with a 24-bit 

analog-to-digital conversion board supporting high dynamic range triaxial accelerometers suitable for 

Advanced National Seismic System (ANSS) Class A (Advanced National Seismic System Structural 

Instrumentation Guideline Committee, 2005; Advanced National Seismic System Technical Integration 

Committee, 2007) seismic strong-motion sensing. The system comes preloaded with sensing software as 

well as deployment tools that enable structural engineers to rapidly deploy the network. In addition to 

the sensors, the system contains 10 to 15 master-tier nodes (embedded single-board computers) that 

provide more robust communications capacity. This wireless strong-motion network was specifically 

designed to deploy in structures with no existing power or communications infrastructure. It conforms 

to most ANSS Class A strong-motion design specifications, the most accurate and advanced class of 

structural measurement systems.

To test ShakeNet, we performed large-scale deployments on two USGS-instrumented structures: 

(1) the 1100 Wilshire Boulevard building in downtown Los Angeles, California, and (2) Seven Oaks 

Dam in Redlands, California. These large-scale deployments assisted with the development and tuning 

of the hardware and software in ShakeNet, and also demonstrated the strengths and weakness of such a 

wireless quick-deployment system.

Experience with these two dense structural arrays illustrates the value of collecting a large 

database of pre-event data on structures to use in future analyses of large-magnitude earthquake shaking 

data. While the responses of large structures in normal conditions are close to noise levels, even ambient 

vibrations and small earthquakes can provoke sufficient structural responses to detect traveling wave 

and modal structural properties useful for system identification purposes, for example, in the steel 

moment-frame UCLA (University of California, Los Angeles) Factor building (Kohler and others, 2005, 

2006, 2007). The Millikan Library on the California Institute of Technology (Caltech) campus exhibits 

changes in modal parameters through time as a result of large ground shaking; Clinton and others (2006) 

report deviations in natural frequencies from the study of continuous monitoring of the 9th floor of 

Millikan Library. These studies illustrate the importance of understanding and documenting the 

dynamic properties of different classes of structures (steel-frame versus reinforced-concrete buildings) 

within the linear response regime before nonlinear response might occur.

ShakeNet Design

ShakeNet was motivated by earlier work on instrumenting a long-span suspension bridge, the 

Vincent Thomas Bridge at the entrance to the Los Angeles Harbor, with wireless sensors. For the 

experiment, twenty wireless sensors were deployed on the bridge, and the sensor network acquired 

vibration samples continuously from each sensor for 24 hours. Although the results from the experiment 

were encouraging in terms of quick deployment in a matter of hours, and the structural characteristics 

derived from the collected data were consistent with previously published results, a few shortcomings 

were evident. The mono (single-channel) amplifier MDA-400 vibration card with 16-bit analog-todigital converter (ADC) used for recording the vibrations was not suitable for capturing low (sub-1 hertz 

[Hz]) fundamental frequencies of large structures. As structure (buildings, bridges) sizes increase, we 

wish to record lower fundamental frequencies associated with their natural frequencies of vibration 

because such low-frequency responses are of interest for structural analysis. In addition, the offsite 

development and preparation time required for the Vincent Thomas Bridge deployment was substantial.

Although we were able to extract macroscopic structural properties such as the modal 

frequencies, the specific board we used (the MDA-400 from Crossbow) had several shortcomings. It 
3

had only 16-bit resolution; this resolution is inadequate for monitoring ambient vibrations in large 

structures. It was originally designed for high-frequency sensing in the kHz (kilohertz) range, so its 

response at the sub-1 Hz modal frequencies of large structures was poor. It had a hardware fault which 

resulted in a signal offset that caused signal clipping at high amplitudes. Finally, the board was designed 

to interface only with a limited set of accelerometers, none of which was well-suited to structural 

sensing. A better accelerometer with higher signal-to-noise ratio and sensitivity was needed for 

structural health monitoring.

ShakeNet development addressed the shortcomings of the earlier system which was based on 

more industrial components. Although much of ShakeNet hardware was constructed using commercial 

off-the-shelf components (sensor network nodes known as motes and embedded single-board computers

known as masters), a renewed focus was placed on the specific requirements for earthquake and ambient 

vibrations in large civil structures. What made ShakeNet application-realistic was our careful attention 

to the design of its data-acquisition hardware, the ShakeBoard (fig. 1). The ShakeBoard is a highresolution (24-bit) acceleration data acquisition system that uses commercial low-noise MicroelectroMechanical Systems (MEMS) accelerometers and conforms to Class A resolution specifications 

established by the U.S. Geological Survey for their Advanced National Seismic System (Advanced 

National Seismic System, 2005, 2007). To our knowledge, no comparable device exists on the market 

today.

Figure 1. ShakeBox hardware block diagram. ADC, Analog-to-Digital Converter. I2C, Inter-Integrate Circuit. The 

imote-2 is also referred to as the Imote2 in the text.

ShakeNet can be rapidly deployed on several floors of a large building or multiple locations on a 

large bridge or dam with no dependence on existing power or communications infrastructure. It was

designed to collect structural vibration measurements for up to a week from each node within the 

network. This portable system can be used to instrument large structures within hours after an 

earthquake. Since there will be a need to deploy multiple dense structural networks rapidly after a large 

earthquake has occurred, this network uses innovative hardware and software design to accommodate 

fast deployment by only two or three people. The network consists of two levels of complexity that 

make network reconfiguration based on suspected damage locations easier (Gnawali and others, 2006). 

The higher-level nodes include a processor on which the algorithms run continuously, reporting back to 

a central processing unit, for example the engineer’s office computer (master nodes). Lower, more 

primitive nodes consist of the sensor and digitizer (motes), but these are in constant communication 

with at least one higher-level node. The results of the networking software are used to redeploy nodes 

during aftershock sequences in areas where significant damage is suspected.

The ShakeBoard hardware consists of a low-power analog-to-digital converter (ADC) board 

developed by RefTek (http://www.reftek.com). This board provides a 24-bit delta-sigma modulator at 

250 sps (samples per second). Internally, the board uses a Cirrus Logic analog modulator, together with 

a digital filter. The sample rate and filter coefficients are all programmable. This board interfaces with 

three Si-Flex 150 accelerometers from Colibrys Inc. and talks to a Crossbow Imote2 over the Serial 
4

Peripheral Interface (SPI) bus. The accelerometers are among the most accurate, low-noise MEMS 

devices on the market. They provide full-scale ±3 g (units of gravitational acceleration) measurements 

with a dynamic range exceeding 120 dB (decibels). The Imote2 has a 32-bit Intel processor, 32 MB 

(megabytes) of SDRAM (Synchronous Dynamic Random Access Memory), and 32 MB of flash. It uses 

an 802.15.4-compliant radio with a nominal data rate of 250 Kbps (kilobits per second). The total power 

consumption of the unit is about 750 mW (milliwatts). All ShakeNet hardware conforms to ANSS Class 

A strong-motion design specifications for amplitude and timing resolution (Advanced National Seismic 

System Structural Instrumentation Guideline Committee, 2005; Advanced National Seismic System

Technical Integration Committee, 2007).

The master level nodes (masters) consist of an embedded single board computer running on the 

Linux operating system and store data on an 8 GB (gigabytes) compact flash drive. The masters 

communicate to the ShakeBoxes via a Crossbow Tmote sensor network mote connected to one of the 

master’s USB (Universal Serial Board) ports. The Tmote acts as a modem which transmits packets 

coming from the master node over the 802.15.4 radio. Similarly, it sends packets received from the

ShakeBoxes to the master over USB. For our deployments, we used two different makes of masters: 

Eboxes and Habey.

ShakeNet’s software was built upon Tenet (Gnawali and others, 2006). Tenet is a programmable 

wireless sensing software algorithm designed for multi-tier sensor networks. In Tenet, applications run 

on a tier of more capable nodes (the masters) and task low-power sensor nodes to collect and conduct 

elementary processing of data. Tenet simplifies the development of sensing applications and can run 

multiple applications concurrently. Prior to our work, the Tenet research prototype was not robust 

enough for week-long deployments and did not include tools for rapid deployment. The experience from 

our deployments helped us develop a production-quality version of Tenet for ShakeNet. We also added 

tools to support rapid ShakeNet deployment. To this end, we developed (1) lightweight network 

monitoring tools that troubleshoot network topology and routing, or deduce the network capacity of a 

particular deployment; (2) mobile, handheld management consoles that simplified the task of iteratively

deploying nodes; and (3) remote-monitoring tools that were used to detect sensor or network failures 

postdeployment. 

Deployment Environment

ShakeNet deployment requires placing the nodes in difficult radio environments, either inside 

large structures with non-radio-transparent structural material or on large outdoor structures with large 

transmission distances, often on radio-reflective structural materials. ShakeNet requires the 

communication protocol to take care of packet drops and find a route to the data collection node. 

Development of robust, working protocols for these operations from scratch required considerable time 

and expertise. We do not envision the end users of ShakeNet to write wireless sensor network data 

collection and communication protocols. Use of existing wireless sensor network software and 

modifying it for ShakeNet’s requirements reduces the development time. Use of multiple masters to 

handle relatively small numbers of nodes also helps with slow networks that may saturate easily with 

overhead associated with larger numbers of nodes. We also needed a wireless sensor network that could 

be tasked to operate a number of applications. It needed to have tools that could help in rapid 

application development as well as for rapid deployment in the field. The Tenet software, discussed

below, fulfilled a number of these requirements and, thus, was used to develop the software suite 

required to run ShakeNet over the ShakeBoxes.
5

System Description

ShakeNet Software: Tenet

The software for running ShakeNet was built using the Tenet architecture for tiered embedded 

networks. Tenet is based on the observation that for scalability, modern sensor network deployments 

ideally have two tiers: a lower tier consisting of motes that enable flexible deployment of dense 

instrumentation and an upper tier containing fewer, relatively less-constrained 32-bit nodes with higherbandwidth radios, called masters (fig. 2). Tenet constrains the placement of application functionality in 

a sensor network according to the principle that multi-node data fusion functionality and multi-node 

application logic should be implemented only in the master tier. The cost and complexity of 

implementing this functionality in a fully distributed fashion in the motes outweighs the performance 

benefits of doing so. This tiered design is fundamental to scaling the size and spatial extent of sensor 

networks because the masters collectively have greater network capacity and a larger spatial reach than 

a flat (non-tiered) field of motes. We ported the Tenet software suite for running over the Imote2 (the 

mote used in the ShakeBoxes; sometimes referred to as an imote-2) and added additional features to run 

ShakeNet.

Figure 2. Schematic illustrating Tenet architecture. A lower tier consists of motes and an upper tier consists of 

masters. MAC, medium access control. Tenet incorporates the Flooding Time Synchronization Protocol (FTSP) for 

time synchronization.

Because the computation and storage capabilities of masters are likely to be at least an order of 

magnitude higher than the motes at any point in the technology curve, masters are the more natural 

candidates for data fusion and higher-level analysis. The principle allows motes to process locally

generated sensor data (that is, data collected at the mote) such as decimation by the ADC; this can result 

in significant communication energy savings. This architectural principle simplifies application 
6

development, resulting in a generic mote-tier networking subsystem that only needs to be implemented 

once. It can be reused for a variety of applications, simplifying mote functionality, thereby enabling 

energy-efficient mote operation, all without significant loss, and with significant gains in overall system 

efficiency.

In Tenet, applications run on one or more master nodes. They task motes to sense and locally 

process data. Conceptually, a task is a small program written in a domain-specific language. The results 

of mote tasks are delivered by the Tenet system to the application program. This program can then fuse 

the returned results and either retask the motes or trigger other sensing modalities. More than one 

application can run concurrently on Tenet. Our Tenet system adheres to the Tenet architectural principle 

by constraining mote functionality. In our system, all communication from an application to the mote 

tier must be in the form of tasks, and applications have no way of expressing multi-node fusion 

computation to be performed in the mote tier.

ShakeNet data collection happens using the Tenet hierarchical architecture. We have a higher 

tier of master nodes, which task the nodes and collect the data responses coming from them. The current 

prototype is able to collect data from two ShakeBoxes sampling data at 125 sps under each master, at 

which point we saturate the available radio bandwidth and cannot add any more ShakeBoxes under this 

master. To overcome this limitation, we implemented the Steim2 algorithm for compressing data on 

each ShakeBox prior to sending it to the master. 

Tenet is quite stable for a research prototype, largely because we have invested several personmonths testing the code in preparation for a bridge deployment. However, that deployment was 

restricted in two important ways. First, we were not confident of the dynamic routing protocols both on 

the master and mote tiers. We did not use dynamic routing software because it was not reliable at the 

time of deployment. In laboratory experiments prior to deployment, we noticed routing pathologies and 

decided to instead use static routing in our deployment. Although we were lucky not to have had node 

failures during our one-day experiment, we cannot rely on the same design for a week-long deployment. 

Second, our deployment did not use Tenet’s time synchronization. Tenet incorporates the Flooding 

Time Synchronization Protocol (FTSP) (Maroti and others, 2004) implementation because we observed 

problems similar to those described in Werner-Allen and others (2006) during laboratory tests. FTSP is 

a time synchronization protocol optimized for wireless environments and outperforms Network Time 

Protocol (NTP) in these environments. FTSP results in high-precision time on resource-limited wireless 

networks by using periodic flooding of time synchronization messages. 

The overall goals for ShakeNet included the following requirements of the ShakeBox:

• Resolution: We required that the ShakeBox conform to the specifications of a Class A strongmotion accelerometer system (Advanced National Seismic System Structural Instrumentation 

Guideline Committee, 2005; Advanced National Seismic System Technical Integration 

Committee, 2007). A Class A device is defined to have a resolution of greater than 111 dB or, 

noise equivalently, less than 6.7 μg (micro-g where g is units of gravitational acceleration).

These specifications translate to a 24-bit device that provides at least 20 bits of usable resolution

over ±4 g of acceleration. The Class A device is the most accurate strong-motion accelerometer 

defined by the ANSS standards.

• Form Factor: We required that the form factor of the sensor node (together with the ShakeBox) 

be such that 75 of them will fit in a small number (say 5−7) of commercially available mobile 

work boxes. This requirement enables a small number of people (two to three) to quickly 

transport these devices and install them in a building. We placed no form factor requirement on 

the master tier nodes. We assume that these nodes can be placed conveniently in locations where 

there is building power (because these nodes will not have attached sensors, there is greater 
7

leeway in their placement); without batteries, most embedded 32-bit devices have a form factor

comparable to a netbook. Alternatively, we conducted a multiple-day deployment in an external 

environment with master tier node power supplied by car batteries. 

• Energy Efficiency: We required that each node be able to sustain a week-long deployment with 

continuous sensing at up to 100 sps of three-axis measurements. As we have discussed 

previously, this requirement is motivated by the expected duration of major aftershocks. Clearly, 

there is a trade-off between form factor and duration of recording: A longer lifetime requirement 

may necessitate larger devices. We discuss below a preliminary design that represents an 

acceptable compromise between lifetime and form factor.

• ShakeBox Hardware: The ShakeBox hardware was developed by a commercial entity, 

Refraction Technology Inc. (Reftek). At the core of the ShakeBox is an analog-to-digital

converter (ADC) board called the RT505, a proprietary low-power ADC developed by Reftek. 

This board provides a 24-bit delta-sigma modulator at 250 sps. Internally, the board uses a 

Cirrus Logic CS5372 analog modulator, together with a CS5322 digital filter. The sampling rate 

and filter coefficients are all programmable. This board interfaces with three Si-Flex 150 

accelerometers from Colibrys Inc. and talks to a Crossbow Imote2 over the SPI bus. The 

accelerometers are among the most accurate and low-noise MEMS devices on the market. They 

provide full-scale ±3 g measurements with a dynamic range of 120 dB. The Imote2 is a highperformance sensor device whose design was originally motivated by high-frequency sensing 

applications (Nagayama and others, 2007). It has an Intel PXA271 processor, 32 MB of 

SDRAM, and 32 MB of flash memory. Finally, it uses the CC2420 802.15.4-compliant radio 

with a nominal data rate of 250 Kbps.

• The Driver: The communication protocol defines how each module should behave for 

information exchange. The driver implements the protocol according to the specifications. With 

the driver, the CPU (Central Processing Unit) module can turn the power and sensor module on 

and off, and configure them. The driver supports the following functionalities: (1) select a 

specified device on any of the modules, (2) read from and write to FPGA (Field-Programmable 

Gate Array) registers and the EEPROM (Electrically Erasable Programmable Read-Only 

Memory) on any of the modules, and (3) collect sample data from the sensor, and auxiliary data 

from the power and ADC modules.

• Steim Compression and SDRAM Support: ShakeNet data collection uses the Tenet hierarchical 

architecture (Gnawali and others, 2006). We have a higher tier of master nodes that task the 

lower-tier nodes and collect the data responses coming from them. However, total data 

collection capability is capped by the limited wireless radio bandwidth. To overcome this 

limitation, we implemented the Steim2 algorithm (SEED Reference Manual, 1993) for 

compressing data aboard each ShakeBox prior to sending it to the master. In addition, wireless 

links are well known for their intermittent behavior. To better adapt to such conditions, we 

added 32 MB SDRAM support in the ShakeBox so that up to 14 hours of data (at 100 sps) can 

be buffered temporarily and then sent out whenever the link quality improves.

• GPS Time Sync: Time synchronization is required for correlation of data collected across

multiple ShakeBoxes. Since ShakeBoxes will be placed inside a building or other structure with 

limited or no access to the open sky, using GPS for continuous time synchronization is not

feasible. We developed a method to time-synchronize the mote and master cloud over USB but

found it was not adequate, owing to the requirement of only a few millisecond error margin for 

time synchronization imposed by ANSS Class A requirements. The millisecond accuracy 

requirement also sometimes made using Flooding Time Synchronization Protocol (FTSP)
8

infeasible because we were not able to estimate clock drift between master tier and sensor motes

with millisecond accuracy. To overcome this, we alternatively use GPS to record the value of 

each ShakeBox’s internal clock at the beginning and end of data collection. This assumes linear 

drift between the two recording times, which may not always true. Before deployment to the site 

we capture the sensor mote’s internal clock against the GPS time under open sky. This is 

repeated after the end of the deployment but before turning off the ShakeBoxes. The two GPS 

time stamps at the start and end are used to calculate the drift in internal clock. We compensated

the recorded internal clock time values during postprocessing of the data.

ShakeNet Hardware: ShakeBox

In collaboration with RefTek, we adopted a modular design for the ShakeBox (fig. 3A, B), which 

consists of four independent modules: CPU, power, analog-to-digital (ADC), and sensor, connected via

standard S bus. Figure 3C shows the CPU, power, and ADC modules. These modules are housed in a 

custom-made weatherproof casing used in a number of RefTek instruments as shown in figure 3A. 

 

Figure 3. Photographs of the ShakeBox components. A, ShakeBox with weatherproof enclosure; six-inch ruler 

shown for scale. B, Placement of modules with 6-inch ruler shown for scale. C, Connection between individual 

modules: a, Central Processing Unit (CPU) module with Imote2; b, power module; c, Analog-to-Digital Converter 

(ADC) module.

The CPU module contains the system processor (a Crossbow Imote2) and the RT617 board; it

controls all system operations. The Imote2 controls communication with the other three modules via 

two SPI interfaces. The RT617 board consists of an FPGA, precision oscillator, battery-backed real-time 

clock, SD memory card slot, Global Positioning System (GPS) interface, and a board ID EEPROM. It 

also provides the timing for the power and ADC modules. The Imote2 is an advanced sensor network 

platform and consists of a PXA271A 32-bit microcontroller and CC2420 radio. It has multiple 

communication interfaces; prominent among those are the SPI, USB host and USB slave, JTAG (Joint 

Test Action Group), and AC97 audio codec. The CC2420 is an 802.15.4-compliant 2.4 GHz (gigahertz) 

radio, which can produce up to 256 Kbps data rate. Dynamic scaling of the core frequency of the 

PAX271 microcontroller, ranging from 13 MHz (megahertz) to 208 MHz, provides a varied range of 

options for balancing processing power with energy usage.

The power module provides the power requirements of the different components, and consists of 

the RT618 FPGA board and RT620 power board. The RT618 provides communication with the CPU 

A B

C
9

module, an internal clock, control of the voltage monitor ADC converter, control of analog power 

supplies, and board ID EEPROM. The RT620 provides an input power controller, switching supplies at 

different voltage levels, a 16-bit ADC monitor for supply voltages and input currents, and a board ID 

EEPROM.

The analog-to-digital module takes the analog sensor inputs and provides a time-stamped 24-bit 

digital output. It consists of the RT618 FPGA board and RT614 analog board. The RT618 provides 

communication with the CPU module, a clock for time stamping sampling data, control of the ADC

chips, test-signal generator for debugging, relay control, a board ID EEPROM, and sensor ID interface. 

The RT614 provides scaling of sensor signal voltages, three 24-bit ADC converters, replays to connect 

test signals to internal analog inputs, a board ID EEPROM, and voltage regulators.

The sensor module consists of three Colibyrs SiFlex 1500 accelerometers, which are interfaced 

to the RT614 board in the ADC module. The SiFlex 1500 operates from a bipolar power supply voltage 

that can range from ±6 to ±15 V (volts) with a typical current consumption of 12 mA (milliamps) at ±6

V. The linear full acceleration range is ±3 g with a corresponding sensitivity of 1.2 V/g.

The weatherproof casing houses all the modules. Each module is electronically shielded to 

protect against electromagnetic disturbance. The lead acid battery used in the ShakeBox is placed in a 

separate sealed compartment to isolate it from the electronics in case of battery leakage. The box 

provides serial connectors, connector for GPS, LEDs (Light Emitting Diodes) for display and feedback,

and antenna connector for a high gain external antenna used by the Imote2’s radio. The instrument case

has three screws and a spirit level for leveling. The prototype box shown in figure 3A is made of a 

strong thermoplastic resin plastic.

Communication between modules in the ShakeBox is achieved with three buses: the module 

selection (SEL) bus whose purpose is to enable specific modules, the SPI command and control bus, 

and the AD data bus. While the SEL bus is used by the Imote2 to select a specific component in a 

module, the SPI command and control bus (the SPI1 port on the Imote2) is used to communicate with 

that component. The AD data bus is used for the Imote2 to collect data from the ADC module, along 

with auxiliary data from the power module. During development, we required debugging features to 

upload driver code and FPGA images to the boards, and to perform diagnostics. Thus, the board 

modules exposed the JTAG port for FPGA programming, and the Imote2 was programmed and 

debugged using the USB slave port.

Laboratory Testing and Experiments

FFT (Fast Fourier Transform) and Channel Analysis With Function Generator

We conducted a series of experiments to test the accuracy of the ADC in the ShakeBox. The 

goal of the laboratory testing was to assess the fidelity and integrity of the various sensing hardware 

components. The equipment we used included an HP33120A Function Generator which accepts user 

parameters to generate an analog wave signal. We fed the input signal to the ShakeBox, collected the 

response from the ADC, and performed numerical analyses such as FFT (Fast Fourier Transform), and 

coherence and cross correlation between channels. We varied the frequency range from 0.2–125 Hz, 

which covers most frequencies of interest in earthquake engineering analysis, and the amplitude range 

from 1–19 Vpp (volts peak-to-peak). We also measured the noise characteristics of each ADC channel, 

with and without the function generator connected. The tests were conducted with and without the 

sensor, at 125, 250, and 500 sps. The tests were also conducted comparing battery to AC power. With 

the sensor attached, tilt tests were conducted to measure response. Because of space limitations, we only 
10

present one set of results here—a sine-wave frequency sweep from 0.2 to 125 Hz with 1 Vpp amplitude

(fig. 4).

Figure 4 shows the FFT analysis for a sine-wave frequency sweep from 0.2 to 125 Hz. It is 

readily apparent that the ADC has a reasonable response up to about 100 Hz, and then the response 

drops dramatically from 100 to 125 Hz. This is expected behavior according to the ADC datasheet.

Figure 4. Graphs showing FFT (Fast Fourier Transform) analysis of input function generator frequency sweep 

from 0.2 to 125 Hz (hertz) with 1 Vpp (volt peak-to-peak) amplitude. Negative frequencies are also plotted by 

default.

Shake Table Test

We conducted a unidirectional electrodynamic shake table test of the ShakeBox in the

Department of Mechanical and Civil Engineering at Caltech. The shake table input was fixed at

frequencies between 0.1 and 90.0 Hz, and the ShakeBox response was compared with collocated Dytran 

piezoelectric accelerometers. Figure 5 shows the shake table test equipment and setup. Halfway through 

the test, the sensors were rotated to test both orthogonal horizontal directions.

We ran the unidirectional shaker at 0.1, 0.5, 0.8, 1.0, 1.2, 1.5, 2.0, 5.0, 10.0, 25.0, 49.0, 50.0, and 

90.0 Hz for between 10 seconds and two minutes using a sinusoidal wave as input. A 2-minute ambient 

vibration test was conducted at the end of the test. Nine Dytran piezoelectric accelerometers were 

attached to the sides and top of a mounting plate (three in each direction). These were connected to a 24-

bit Granite digitizer with GPS antenna. The Dytran accelerometers have flat response for 1−2,000 Hz 

with a range of ±50 g and were calibrated at the factory in early 2009. During the tests, we compared the
11

Dytran-Granite versus ShakeBox performance in near-real time and observed strong similarities in 

waveform shape and amplitudes. Though the input was a sine wave, the shaker appeared to give a little 

kick at each end of its travel distance. This kick produced additional peaks in the output seen on both the 

Dytran and Colibrys sensors. Because we observed the response to these kicks on both sets of 

accelerometers, we concluded that it was not caused by a fault in accelerometer response. Even though 

the channels were lined up parallel to and perpendicular to the direction of shaker motion (fig. 5, A and 

B), the motion was not perfectly one-dimensional; a response was also observed in the other orthogonal 

channels but at lower amplitudes. This is partly due to shake table imperfections, but it may also be due 

to cross-axis misalignments between the sensors’ indicated and true axes. Dytran-Granite timing was 

based on GPS time stamps, and the ShakeBox timing was based on time stamps from the PC clock. The 

Dytran-Granite GPS time stamps were used as the reference start times.

 

Figure 5. Photographs showing shake table equipment and instrumentation setup. A, Shake table top showing 

mounted steel plate with Dytran piezoelectric and Colibrys MEMS accelerometers, and additional ShakeBox 

components on chair. B, Closeup of mounted plate with accelerometers. C, 24-bit digitizer and PC recording setup 

for Dytran accelerometers.

For each frequency, we compared waveform shapes between Dytran-Granite and ShakeBox 

performance, expecting differences to be indications of questionable or faulty performance in the 

Colibrys. Examination of absolute amplitudes showed that they were within 10 percent or better of each 

other (fig. 6). The observed spectral peaks in the FFTs computed from the acceleration time series of 

both types of sensors also showed good agreement between the two systems.

A B C
12

 

Figure 6. A, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with Dytran 

piezoelectric accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the Colibrys 

Channel 2 direction with 1 Hz sine wave input.

A
13

 

Figure 6.—Continued B, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with 

Dytran piezoelectric accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the

Colibrys Channel 2 direction with 5 Hz sine wave input.

B
14

 

Figure 6.—Continued C, Shake table test results comparing ShakeBox (Colibrys MEMS: black curves) with 

Dytran piezoelectric accelerometer response (red curves), recorded at 100 sps. Shaking was performed in the

Colibrys Channel 2 direction with 25 Hz sine wave input.

Millikan Library Test

We conducted a ShakeBox performance test at Millikan Library on the Caltech campus (fig. 7). 

The objective was to compare the ShakeBox performance versus the permanent Episensor 

accelerometers’ performance during several forced vibration tests. The Episensor is a broadband forcebalance accelerometer used in permanent, wired, structural arrays and has reliable, low-noise 

C
15

performance. An eccentric-mass shaker is located on the Millikan Library roof and provided the 

excitation in a single horizontal direction during any one shaking test (fig. 7). Although the building 

responds in other axes as well, our comparison of collocated sensors obviates any issues arising from 

such responses and are useful, as described below. Two Shakeboxes were collocated with threecomponent Episensor accelerometers on the 9th floor and in the basement (fig. 7). Millikan Library is a 

nine-story reinforced concrete building consisting of both shear walls and moment frames. Shear walls 

dominate the east and west faces of the building and also line the elevator core in the center of the 

building. The shaker was run at frequencies between 1.0 and 9.5 Hz, and each ShakeBox response was 

compared with the collocated Episensor accelerometers. 

The forced vibration tests consisted of an initial empty-buckets test (no weights added resulting 

in minimum applied force), a full-buckets test (all weights added resulting in maximum applied force) in 

the east-west direction, and a full-buckets test in the north-south direction. The empty-buckets shake 

spanned frequencies from 1.0 to 9.5 Hz gradually over the course of approximately 40 minutes. The rate 

changed over the course of the sweep. The lowest frequencies progressed at 0.05-Hz intervals every 20 s

(seconds), from 2.5 to 5 Hz progressing at 0.05 Hz intervals every 15 s, and from 5 to 9.5 Hz 

progressing at 0.05 Hz intervals every 10 s. This frequency range covers the building’s first east-west

mode frequency of 1.2 Hz (ambient), the first north-south mode frequency of 1.7 Hz (ambient), and the 

first torsional mode frequency of 2.4 Hz (ambient). The second test consisted of a full-buckets shake 

(full set of weights for increased force, resulting in temporary nonlinear building response) for 

frequencies between 1.0 and 2.5 Hz, particularly to excite the first east-west frequency at 1.15 Hz 

(nonlinear response due to maximum force applied). The sweep up to 2.5 Hz and back down to the 

starting frequency of 1.0 Hz took approximately 30 minutes. The east-west full-buckets test also excited 

the torsional mode (2.3 Hz, nonlinear) in a narrow band around the mode progressing at a rate of 0.2 Hz 

intervals every 45 s. At the end of this test, we paused near the peak resonance for around a minute at 

both the first east-west and torsional mode frequencies. 

The first east-west frequency shake shows up primarily in the east-west components of the 

accelerometers, and the first torsional shake shows up clearly in both the east-west and north-south 

components. The third test consisted of a full-buckets frequency sweep in the north-south direction for 

frequencies between 1.0 and 1.8 Hz, particularly to excite the first north-south frequency at 1.6 Hz 

(nonlinear). The north-south full-buckets test excited the first north-south frequency in a narrow band 

around the mode progressing at a rate of 0.2 Hz intervals every 45 s. At the end of the test, we paused 

again at resonance on our way back to 0 Hz. As the shaker frequency intersected these modes, we 

observed increased response resulting in increased amplitudes.

The recorded accelerations for both types of instruments in the basement and 9th floor locations 

are shown in figure 8, plotted in the same units (mg) (milli-g where g is units of gravitational 

acceleration). Note that the amplitude scales are different for each component. Overall, the response of 

the ShakeBox (Colibrys) is quite similar to that of the Episensor-Granite except that the ShakeBox 

amplitudes are usually about 10–20 percent larger. This may be due to the lack of robust physical 

coupling of the ShakeBox with the floor slab in both locations (we placed our boxes on the floor,

whereas the Episensors are bolted into floor slabs or walls). The amplitude difference is larger at the 9th

floor where the shaking was stronger than in the basement.
16

 

Figure 7. Photographs showing Robert A. Millikan Memorial Library, shaker, and sensors that were tested. A,

Robert A. Millikan Memorial Library on the Caltech campus, viewed from the northeast. B, Kinemetrics VG-1 

eccentric-mass shaker located on the roof of Millikan Library. The counter-rotating buckets, shown empty, can be 

loaded with different configurations of lead weights to impart different forces on the building. C, Accelerometers

located in the basement that were recording during the Millikan shake test. The ShakeBox is the small black box 

with the orange triangle symbol on top, behind the blue box.

B

A C
17

 

Figure 8. A, Graphs showing acceleration responses due to forced vibrations recorded by the ShakeNet 

ShakeBoxes collocated with an Episensor in the basement of Millikan Library, California Institute of Technology.

A
18

Figure 8.—Continued B, Graphs showing acceleration responses due to forced vibrations recorded by the 

ShakeBoxes collocated with an Episensor on the 9th floor of Millikan Library, California Institute of Technology.

Prototype Deployments in Structures

Deployment of Instruments During Early Development

In 2006, coauthor Govindan’s group deployed a 20-node, wireless, ShakeNet prototype network 

on the Vincent Thomas Bridge in San Pedro, Calif. (Paek and others, 2006) (fig. 9). One day of ambient 

vibration recordings from this deployment illustrates the ability to record coherent signals, most likely 

produced by passing truck traffic (fig. 10). Figure 10 shows the consistent spectra across sensors for this 

B
19

type of stand-alone deployment, exhibiting frequencies of bridge vibration that are in agreement with 

previous, longer deployments that recorded earthquake data with a traditional wired seismic array

(Smyth and others, 2003). 

The ShakeNet prototype was also tested on the steel, moment-frame, UCLA Factor building,

which has an embedded, wired, 72-channel array. In 2006, we tested several motes on the 13th−15th and 

1st

−3rd floors, revealing the strengths and weakness of the instrument design, eventually leading to the 

current data acquisition board and MEMS accelerometer layout described earlier in this report.

ShakeNet Prototype Deployments

Our wireless ShakeNet strong-motion network was specifically designed to be deployed in 

structures with no existing power or communications infrastructure. We chose two test structures to 

collect information representing a range of environmental conditions. They included the building at 

1100 Wilshire Boulevard in downtown Los Angeles, Calif., and the Seven Oaks Dam in Highland, 

Calif. The building at 1100 Wilshire Boulevard consists of a large, square-plan, 15-story, reinforced 

concrete base structure that holds a 700-space parking structure. A 21-story, steel moment-frame, 

triangular prismatic pentahedron sits on top of this base structure. The Seven Oaks Dam sits within 1

km of the San Andreas Fault and is located in a region of alluvial sediments in the southern foothills of

the San Bernardino Mountains. It is a 550-ft-high, 2,980-ft-long (168 by 908 m), earth-and-rock- fill 

dam designed to provide flood protection to Orange County, Calif. 
20

A

B

Figure 9. A, Vincent Thomas Bridge, Los Angeles Harbor, California. B, ShakeNet prototype deployment across 

part of the bridge deck.
21

Figure 10. Graph showing accelerations recorded during the deployment at Vincent Thomas Bridge, Los 

Angeles, California, in July 2006. Vertical accelerations have been bandpass filtered for frequencies between 0.2 

and 5.0 Hz.
22

Figure 10.—Continued Graph showing spectra of accelerations recorded during the deployment at the Vincent 

Thomas Bridge, Los Angeles, California, in July 2006.

1100 Wilshire Boulevard Building

In June 2011, we conducted our first ambient vibration deployment at the 1100 Wilshire 

Boulevard building. The 1100 Wilshire Boulevard building consists of a massive 15-story concrete cube 

that holds a 700-space parking structure. The building is 483 ft (147 m) tall. A 21-story steel momentframe, triangular prismatic pentahedron sits on top of the cube (fig. 11).
23

 

Figure 11. Photo and SketchUp diagram of the 1100 Wilshire Boulevard building in Los Angeles, California.

For three days, we operated 30 triaxial ShakeBoxes with 10 masters in the stairwells of several 

floors in the upper condominium section of the building, as well as along outer walls on several floors 

of the garage. The network recorded ambient vibrations of the structure for the 3-day time period. 

Because the seismometers used ultra-low power 802.15.4 radios, they did not interfere with local Wi-Fi 

communications. The network configuration is shown in table 1.
24

Table 1. Floors with sensors in the 1100 Wilshire Boulevard building deployment, Los Angeles, California. [#, total number]

Level # ShakeBoxes # Masters

B3 3 1

B 3 1

1 2 0

2 2 2

3 2 0

16 2 0

17 2 2

18 2 0

20 2 0

21 2 2

22 2 0

36 2 0

37 2 2

38 2 0

Based on a predeployment site reconnaissance visit, we found that wireless communication was 

excellent in the open stairwells, likely because there is a significant amount of metal in the numerous 

handrails, as well as the stairs and inside the walls, providing a waveguide effect through the otherwise 

open space. Even for floors that were tall, such as the lobby and conference room levels, communication 

from floor to floor within the stairwell was better. Although we expected that we might need to use

multihop, placing the master in the middle of each cluster in nearly every case provided direct motemaster communication. 

The primary weakness of this deployment turned out to be the masters’ hardware. Some were 

not as reliable as expected and failed upon loss of communication. The eboxes used here had several 

issues. First, the operating system (Ubuntu 10.04) became unstable for a few specific CPU frequencies 

and the operating system would eventually hang. Second, not all USB ports functioned well. If the 

master mote was attached to a bad USB port, the data collection would stop halfway through, and the 

communication between the master and ShakeBoxes was lost. On the other hand, throughout the 1100 

Wilshire Boulevard building deployment, we were able to evaluate the integration of the whole system 

and test the lifetimes of both ShakeBoxes and eboxes powered by car batteries under realistic 

deployment conditions.

Spectra from a section of horizontal records from acceleration data recorded in the building at

1100 Wilshire Boulevard are shown in figure 12. The spectra have been arranged in order of increasing 

height inside the building with the bottom six spectra from within the parking garage cube. The more 

flexible steel frame triangular prismatic pentahedron produces peaks in the spectra that are more 

obvious to identify than the stiffer reinforced concrete cube. The upper stories show distinguishable 

peaks at 0.25 Hz (possibly the first translational mode), 0.4 Hz (first torsional mode), 0.7 Hz (second 

torsional mode), 0.8 Hz, 0.9 Hz, 1.4 Hz, 1.6 Hz, 2.0 Hz and higher, also identified by Celebi and others

(1991). The spectral lines in the spectrogram above 10 Hz are most likely due to machinery running at a 
25

range of frequencies and for limited time durations (for example, heating, ventilation, air conditioning, 

and elevators).

Figure 12. A, Spectra from a 1-hour section of horizontal component waveforms from 30 ShakeBoxes deployed 

in stairwells on various floors arranged from bottom to top of building (bottom to top of figure) at 1100 Wilshire

Boulevard, Los Angeles, California. Numbers overwriting file name in left-hand column indicate amplitude 

normalization factor.

 
26

Figure 12.—Continued B, Spectrogram from a section of horizontal component data recorded by a ShakeBox

deployed on the 36th floor, from the test deployment in the building at 1100 Wilshire Boulevard, Los Angeles, 

California.
27

Seven Oaks Dam

In October 2011, we conducted our second deployment at the Seven Oaks Dam (fig. 13). The 

Seven Oaks Dam sits within 1 km of the San Andreas Fault and is located in a region of alluvial 

sediments in the southern foothills of the San Bernardino Mountains. For three days, we set up and 

operated seismometers in 31 locations along the Seven Oaks Dam crest road and the downstream 

switchback roads (see fig. 13C). Specifically, we placed 24 seismometers at approximately 120-foot 

spacing along the crest road (fig 13B), and two seismometers at 120-foot spacing along the center of all 

three downstream switchback roads. Deployment layout with locations of clusters is shown in table 2. 

 

Figure 13. Seven Oaks Dam in Highland, California. A, Aerial view. Picture taken on February 8, 2005, by Steve 

Schumaker. B, Example ShakeBoxes deployed on crest of dam. C, Network configuration showing locations (red 

squares) of the 31 seismometers.

A B

C
28

Table 2. Locations of sensors and associated clusters during Seven Oaks Dam deployment. Sensors on crest 

road are listed in increasing distance order from westernmost to easternmost end and are approximately 120 feet 

apart. See also figure 13. [#, number]

ShakeBox Serial # Cluster # Location

B00E A Crest—westernmost end

B008 A Crest

B007 A Crest

B00A B Crest

B00B B Crest

B009 B Crest

B00C C Crest

B00F C Crest

B00D C Crest

B010 D Crest

B012 D Crest

B011 D Crest

B020 E Crest

B015 E Crest

B014 E Crest

B018 F Crest

B016 F Crest

B017 F Crest

B019 G Crest

B01B G Crest

B01A G Crest

B01E H Crest

B01D H Crest

B01C H Crest—easternmost end

B02B I Middle of highest switchback road

B02A I Middle of highest switchback road

B029 J Middle of middle switchback road

B028 J Middle of middle switchback road

B022 K Middle of lowest switchback road

B023 K Middle of lowest switchback road

B02C L Base of dam
29

Spectra from several hours of ambient vibration data collected during one of the deployment 

days are shown in figure 14. This deployment posed problems we did not anticipate, alerting us to issues 

that still needed to be solved before making ShakeNet fully reliable. We had expected that wireless 

communication would be excellent because of the clear mote-to-mote line of site and because there 

were no wireless signals present that would interfere with ours. Communication between some motes 

and masters was faulty as it turned out, but we expect that more powerful antennas will partially solve 

this problem in the future. As with the previous deployment, the masters’ hardware again posed 

problems for reliable data recording. During the data collection, we could not easily establish 

communication between the master and ShakeBoxes in at least four clusters. After trial-and-error 

placement of the antennas in various possible orientations, we were able to reach all ShakeBoxes, but 

postdeployment analysis showed that the communication links did not last long. We hypothesize that 

the reasons for bad communication links might be that the antennas we used were relatively weak for 

outdoor environments; they worked well in the 1100 Wilshire Boulevard building deployment which 

was indoors where walls helped reflect signals. We also encountered a strange reset behavior in the 

USB driver of the master nodes. Because of the reliability issue of the previous master (ebox) nodes 

used at the 1100 Wilshire Boulevard building, we replaced them with newer nodes with equivalent 

functionality and newer hardware (manufactured by Habey). The unpredictable resets occurred with 

three clusters, and we need to further test these to pinpoint the cause. It might be that these Habey nodes 

are faulty or that the master motes do not function well. The very small ambient vibration amplitudes of

this large, stiff dam, near the internal noise level of the Colibrys sensors, precluded us from performing 

system modal identification from the 3-day records (fig. 14).

Figure 14. Ambient vibration spectra from transverse direction (channel 2, north-south orientation) produced 

from several hours of acceleration data recorded during one of the deployment days at Seven Oaks Dam in 

Highland, California. Numbers overwriting file name in left-hand column indicate amplitude normalization factor.
30

Summary and Conclusions

The ShakeNet project enabled the testing of new wireless protocols with accelerometers to 

collect ambient vibration data in order to identify system response modes of civil structures. ShakeNet 

deployments required placing the nodes in harsh radio environments; thus, one of the most important 

aspects of the communication protocol development was to find the best route to the data collection 

node and to minimize packet drops. Another aspect of the development was that ShakeNet end-users not 

be required to write customized wireless sensor network data collection and communication software. 

Use of existing wireless sensor network software (Tenet) and modifying it for ShakeNet requirements 

helped reduce development time because Tenet could be tasked to operate a number of applications. The 

ShakeBoxes are currently being used by other researchers doing conducting software development so 

that the instruments can be operated either in network mode or in individual node mode in any Windows 

or Linux Operating System. 

Since the conclusion of this project, new research has been carried out in seismic networks in 

which nodes are hosted by nontechnical volunteers. We envision that next-generation ShakeBoxes could 

be incorporated into such networks. The Quake-Catcher Network (QCN; Cochran and others, 2009, 

2011) and Community Seismic Network (CSN; Clayton and others, 2011; Kohler and others, 2013) are 

dense networks of accelerometers deployed by community volunteers in homes, public spaces 

associated with civic services (such as city libraries), utilities, university campuses, and business offices. 

In addition to the standard USB device, which connects to the host’s computer, a stand-alone version 

directly connects to the Internet via Ethernet. The QCN sensors in buildings are connected to netbooks 

with continuous data streaming in real time via the Berkeley Open Infrastructure for Network 

Computing (BOINC) software program to a server at Stanford University (Cochran and others, 2009). 

The basic analysis currently done uses only a fraction (1−5 percent) of the computing capabilities of the 

desktop, netbook, or other computer that is monitoring the sensor. Therefore, each sensor node has 

additional processing power that can be exploited for more than just the current event detection and data 

streaming. In the case of CSN, the data are sent to a cloud service where the data are fused (Clayton and 

others, 2011). 

Future developments with community-hosted networks can take advantage of 

ShakeNet/ShakeBox setups by exploiting performance in the individual computers, or subsets of those 

computers, that are connected to the sensors, and cloud or distributed computing. Computations could 

be carried out on collections of sensors in a multi-tiered fashion (see Zhao and Guibas, 2004; Pottie and 

Kaiser, 2006; Iyengar and Brooks, 2012; Madisetti and Bahga, 2014) such that a subset of clients could 

aggregate information across only part of the structure, and one client (or stand-alone computer) could 

aggregate information for the entire building. This framework—combined with enhancements in 

telemetry systems that include, for example, cellular data—would provide increased management of the 

overall system in a wide variety of indoor and outdoor environments for structural monitoring.

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