InTech - A Real Mesh

This month InTech Magazine had a special section on automation with wireless technology. The article featured work done by researchers from EPRI, Oak Ridge National Laboratory, Southern Company Services, University of North Carolina at Charlotte, and Taft Engineering who set out to demonstrate the effectiveness of wireless sensors in a power plant. Since low-cost, battery-powered, wireless sensors have the potential to radically alter traditional methods of equipment monitoring in power plants, they wanted to provide guidance for someone deploying a wireless sensor network in a plant on the allowable distance between sensors and what to expect for battery life. The results were a 15-minute powerup of 12 Mote platforms communicating with the base station and no obvious problems.

The research was done using various Crossbow wireless sensor networking prducts such as the MICAz Mote, MDA and MTS sensor boards and the Stargate NetBridge gateway.

Historically, the normal practice in power plants and other process industry facilities has been to hardwire important sensors from their location in the plant to a central equipment room where monitoring systems are installed to collect the data from the sensors. This arrangement worked well, but the cost of installing all the wiring to connect each sensor to the central location was high, often more than the cost of the sensor itself. This high cost has discouraged companies from installing all the sensors they need to fully monitor their plants.

A research project co-sponsored by Southern Company and EPRI to demonstrate wireless sensors in a power plant environment focused on sensors’ radio performance and battery life. Each wireless device, or mote, consists of two small circuit boards, one for the processor and radio and the other for sensors or data acquisition. The research team deployed two types of processors and radios and three types of sensor boards. The sensor boards had several built-in sensors for temperature, ambient light intensity, barometric pressure, sound, magnetic field, and acceleration in x and y directions, along with general purpose data acquisition capabilities. The wireless communication conforms to the IEEE 802.15.4 standard for low power, low data rate sensors with mesh networking capabilities. The team gathered results of a radio frequency site survey conducted before the installation of the sensors.

Wireless sensors
Early wireless sensors used proprietary protocols over a point-to-point radio link and required power high enough to make operation on batteries impractical. In the last few years, a new class of wireless sensors features a standard physical communication layer, a self-forming mesh network, and power use low enough to enable battery life of a year or more. These new wireless sensors have the potential in the next few years to dramatically change not only the wireless sensor landscape but the process monitoring landscape.

Before the power industry can accept any new technology, tests must occur in a realistic power plant environment. Southern Company and the UNC Charlotte conducted two sets of tests focused on wireless communication and battery life. Before testing the sensors in the plant environment, the research team tested them in an office environment to gain understanding of the operation of the sensors and the mesh network.

Plant radio frequency site survey
Before installing any new wireless network technology such as a wireless sensor network, quantify the existing radio frequency (RF) environment to determine if potential interference exists. It is also useful to test the signal propagation characteristics of the facility where you will install the wireless equipment to ensure reliable communication. The U.S. Department of Energy Extreme Measurement Communication Center at Oak Ridge National Laboratory will perform both tests at the E.C. Gaston Electric Generating Plant. Plant Gaston currently does not have any wireless sensor networks installed.

The team used two instruments to record and analyze ambient RF signals. An Aeroflex CS65040 Broadband Signal Recorder and Generator recorded the signals in the time domain, and a Rohde & Schwarz FSH3 spectrum analyzer provided spectral information about the signals. Two special antennas provided the inputs to the analyzers. The monitoring equipment was mounted on a wheeled cart and moved to four sites in the plant. The test site locations were 1) on the turbine deck near the unit 4 turbine, 2) on the mezzanine level under the unit 5 high pressure turbine, 3) on the mezzanine level under the unit 5 generator, and 4) on the base level near a boiler feed-pump turbine.

Data from these tests is presented as screen shots from the instruments. Only a few screen shots are included in the report as examples of the information obtained from the tests.

The signal recorder has an anomaly that appears as four continuous wave (CW) signals, first at -15 MHz from center, second at -10 MHz from center, third at +5 MHz from center, and fourth at +30 MHz. The signal at -15 MHz pulses, while the others are constant. They are present at these frequency offsets in all plots and in all frequency bands. Ignore these signals.

The team set up the signal recorder to collect data in four frequency bands: 500 MHz, 900 MHz, 2.4 GHz, and 5.8 GHz. The bandwidth for all bands is 130 MHz. The plots are the result of replaying the signals recorded during the tests. The average noise floor across the different locations ranged from -79 dBm to -85 dBm in the different frequency bands.

Southern Company mote testing
The project plan for mote testing was to do the initial familiarization and setup and a short test in an office environment and then deploy the sensors in the plant for longer term testing. Testing the wireless sensors in an office environment before testing them in the plant was attractive because the office environment was more controlled, more convenient, and less costly. The objectives of all the tests were:
• Familiarization with the hardware and software being tested.
• Document the range of the low power radio system.
• Verify the operation of the mesh network and its adaptability to network changes.
• Measure the battery usage and estimate battery life.
• Develop a method for measuring temperature with an external thermocouple.

The team set up the initial wireless sensors in an office where the radio environment is friendlier than in a plant. It developed the thermocouple input system using the low level analog input data acquisition board in the office. The monitoring program monitored the sensors and saved the collected data. The team estimated battery life at about 100 days based on one week of operation. The team learned during the office testing that the monitoring program could only collect data from a single type of sensor board at one time. Since two types of sensor boards were seeing use in the project, another program was needed. The mote vendor provided a new gateway product that supported many types of sensor boards at the same time.

The gateway is a small computer running the Linux operating system, which interfaces with the base station on one side and an Ethernet network on the other. The focus of the plant environment testing was to determine how well the sensors communicated in the relatively unfriendly radio environment of a power plant. The goal was to provide guidance for someone deploying a wireless sensor network in a plant on the allowable distance between sensors and what to expect for battery life.

The wall of the control room in which the base station was located is made of sheet metal. To ensure good communication through the wall, the team positioned one mote just outside the control room. The bulk of the remaining motes were at least 100 feet away under the unit 5 turbine.

The computer communicates with the gateway in one of three ways over an Ethernet network. The gateway has a web server built-in, so a web browser in the computer can login to the gateway and view sensor and network data. You can also make a connection using a secure shell (ssh) program on the computer. Finally, you can attach the disk drive on the gateway as a network drive (using Samba on the gateway) to the computer for sharing data files.

The research team distributed 12 motes around the area under the unit 5 turbine. This area has many large steam pipes and structural steel elements that have the potential to obstruct the radio signals from the wireless sensors. In most cases, there was no clear line of sight between motes. Because the team only planned the test to last a couple of months, it placed the motes in plastic zip-lock bags to protect them from dust and water.

The research team powered up the wireless sensor network equipment, and within 15 minutes, most motes were communicating with the base station. A mesh network was established, and all but two motes that could not communicate with the base station directly were able to communicate through the mesh. After the two motes were relocated slightly, they began communicating. The team left the motes in these locations for several weeks, recording sensor data and mesh network performance data continuously. There were no obvious problems with the mote communication, but the mesh structure did change occasionally for unknown reasons.

Visit www.xbow.com for more information on Crossbow's wide range of wireless sensor network platforms and to view the original article visit the InTech site here.

Structural Health Monitoring

Part 2 – Software

The Illinois Structural Health Monitoring Project (ISHMP) introduced earlier is working to develop an inexpensive means for continuous and reliable SHM (Structural Health Monitoring) using dense arrays of wireless smart sensors. Researchers have designed, developed, and tested sensors to produce the high-fidelity data required for SHM that can be manufactured very cheaply. Their research has also produced an enabling customizable software framework that greatly reduces both the complexity and time for development of SHM applications for smart sensor platforms.

The ISHMP Services Toolsuite provides an open-source software library of customizable services and examples of SHM applications utilizing wireless smart sensor networks (WSSNs). The ISHMP provides users with a collection of guides to help those who are new to Crossbow’s Imote2 platform, its operating system or programming languages.

As with many wireless sensor platforms, the ISHMP Services Toolsuite on the Imote2 employs TinyOS as the operating system. TinyOS is tailored to the specific constraints of sensor network applications and occupies a small memory footprint, while efficiently supporting complex programs. TinyOS applications are implemented in NesC, a C-like programming language which supports the concurrency model of TinyOS. While TinyOS has been adopted by many sensor network applications and has quite a large user-community, it can be a daunting undertaking for engineers lacking such specific programming experience to develop code for their applications. To alleviate this problem, the ISHMP Services Toolsuite was designed assuming that the typical user will have limited background in computer science. Rather, the user is expected to be familiar with basic Windows operation and have a desire for a smart SHM system that can be installed easily and operated reliably.

The ISHMP Services Toolsuite employs a Service-Oriented Architecture (SOA) that lends itself to further expansion, customization, and development of WSSN applications for SHM. It provides complete applications that facilitate common tasks throughout the design, testing, deployment, and monitoring of the SHM system, while utilities offer a set of basic testing and debugging commands to be included with existing applications. The SHM Services Toolsuite includes utilities for resetting nodes remotely, listing the nodes within communication range of the local node, testing radio communication performance, and changing the radio channel and power for local and remote nodes. Specific services and tools currently available include the following:

Foundation Services: The foundation services provide commonly used wireless sensor functionalities that are required to support higher-level applications. These services include basic communication and sensing functionalities.

• Unified Sensing is a TinyOS-based sensing interface for Imote2 that supports various sensor boards including Crossbow ITS400 and Illinois SHM-A. Unified Sensing service provides precise, variable-resolution time stamping of sensor data that can be used to synchronize sensor data from different sensor nodes.
• Time Synchronization is a network-wide service for synchronizing the local clocks that sensor nodes in the network locally have.
• Reliable Communication ensures reliable data communication in a wireless sensor network. Data loss, a common problem in the wireless communication, is handled by the Reliable Communication service.
• Remote Command provides an efficient means for nodes to interact with each other. A command message is delivered to receiver nodes that process the designated tasks, and returns the list of responsive nodes and requested data to the sensor node. Remote Command allows the fault tolerant features to be easily implemented in sensor applications.
• Reliable Multi-Hop Communication provides the beta-implementation of any-to-any reliable multi-hop routing for sensor network applications. Multi-hop communication is essential for monitoring of large structures, where all sensors cannot be deployed within direct communication range of a small number of base stations.

Application Services: The application services provide the numerical algorithms necessary to implement SHM applications on the Imote2s and may also be used independently.

• Synchronized Sensing resamples the sensor data, providing synchronized data. Although the local clocks are synchronized by the Time Synchronization service, the sensing start time and the sampling rate vary from sensor to sensor with a certain amount of error. The unsynchronized sensor data is synchronized by retroactive resampling using the SyncSensing service.
• CFE estimates correlation functions between two arrays of synchronized data.
• CPSD estimates cross power spectral density between two array of synchronized data.
• RD performs the Random Decrement method to estimate unscaled impulse response functions.
• ERA estimates modal properties (i.e., natural frequency, damping factor, and mode shapes) using the Eigensystem Realization Algorithm (ERA). NExT allows the correlation functions estimated from the CFE service to be used in the ERA service.
• SSI performs the covariance-driven Stochastic Subspace Identification (SSI) for modal property estimation.
• FDD performs the Frequency Domain Decomposition (FDD) algorithm for modal property estimation.
• SDLV performs the Stochastic Damage Locating Vector (SDLV) method for damage localization.
• SDDLV performs the Stochastic Dynamic Damage Locating Vector (SDDLV) method for damage localization.

Tools and Utilities: The tools and utilities provide network testing and debugging capabilities that are necessary in any large-scale or long-term WSSN deployment. These tools facilitate evaluation of the network conditions at the structure to determine appropriate values of adjustable system parameters, and assess power consumption and longevity issues.

• LocalSensing collects sensor data from the single Imote2 connected to the PC. This tool is useful for testing new sensor board hardware as well as driver software.
• imote2comm is a terminal program that provides an interface between the PC and the Imote2 through the Crossbow IIB2400 interface board. This tool is frequently used to run the application in the ISHMP Toolsuite.
• TestServices combines numerical services, CFE, ERA, and SDLV, and performs damage detection from user-defined acceleration signals. TestServices is an application example that illustrates how the numerical services can be combined.
• TestRadio allows testing the raw bidirectional communication between a local node and remote nodes.
• RemoteSensing is an implementation of the centralized data acquisition approach that collects synchronized sensor data from a network of sensors to the base station. Time Synchronization and Synchronized Sensing services used in RemoteSensing for the synchronized sensor data.
• SensingUnit, a service component that performs synchronized or unsynchronized sensing, is particularly useful for SHM application development
• IndependentProcessingPSD is an implementation of the independent processing that decentrally estimates the power spectral densities in each node.
• DecentralizedDataAggregation is an application for the data acquisition and processing on decentralized hierarchical sensor network.

Continuous and Autonomous Monitoring Services: These services provide for continuous and autonomous WSSN operation while maintaining power efficiency.

• SnoozeAlarm provides sleep cycle functionality, which greatly reduces long-term power consumption. Sensors sleep for a period of time and then wake up for a relatively short period, during which they can interact with the network. The duty cycle is configurable by the user.
• ThresholdSentry allows a subset of the network to act as “sentry” nodes that are awakened periodically to sense data for a short period of time, determine if an interesting event is in progress, and notify the base station.
• AutoMonitor is a high-level network management application that coordinates each of its components in response to various events. It schedules sensing, data transfer, and ThresholdSentry operation according to a user-specified policy, allowing the network to operate unattended.

In addition, a library of supporting numerical functions that are common to many SHM algorithms is provided including Fast Fourier transform (FFT), singular value decomposition, eigenvalue analysis, etc. Documentation is provided for each service and test application, giving specific requirements and formats of the inputs and outputs for the service. More detailed information regarding the service-oriented architecture of the ISHMP Services Toolsuite can be found here.

To illustrate how SOA of the ISHMP Services Toolsuite lends itself to further expansion and in the development of WSSN applications for SHM, consider the figure below, which shows how the system identification method can be swapped out in an SHM application. In keeping with the SOA framework, these interchangeable services share the same input and output parameters.

In its current form, the ISHMP Services Toolsuite requires application programmers to simply provide the code necessary to interconnect the services and tools in a way that makes sense for their applications. In general terms, this code serves the following functions:
        • Run service X at node A
        • Send a control message to node B to run service Y
        • Send results from B to A
        • Run service Z on node A taking as inputs the outputs of services X and Y

Full-scale Integration
As described in the initial post, the software and hardware developed in this research has enabled the deployment of the smart SHM system on the Jindo Bridge in South Korea. This effort is part of a trilateral collaboration between the USA (University of Illinois at Urbana-Champaign), South Korea (Korean Advanced Institute of Science and Technology, KAIST), and Japan (University of Tokyo).

In total, 70 Imote2 sensor nodes with SHM-A sensor boards have been installed on Jindo Bridge. This SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date and demonstrates the suitability of the Imote2 smart sensor platform, the SHM-A sensor board, and the ISHMP software for full-scale, continuous, autonomous structural health monitoring. The figure shown below shows the measured data from WSSN on the Jindo Bridge.

The figure below compares computational model predictions (inset) with the experimentally determined frequencies and mode shapes obtained using the frequency domain decomposition method. As can be seen, the agreement is excellent.

In summary, the ISHMP Services Toolsuite provides an extensive set of middleware services, utilities, and tools that enable creation of complex, data-intensive WSSN applications for structural health monitoring. This SOA-based approach creates a framework which allows application programmers to more easily create applications for SHM systems. As a result, the framework allows more researchers, and ultimately application engineers, to design and implement successful SHM systems without the requirement of understanding how the underlying middleware and numerical services are implemented.

For information on installing the Toolsuite, visit the ISHMP site here.
For more details on the Imote2 platform, visit Crossbow's site here.

The Illinois SHM Project Services Toolsuite software is open source, but not public domain. The license, a copy of which is also included in the software distribution, allows for unlimited use and modification of the software for non-commercial purposes. Unless otherwise stated, the software and source code in the package is licensed under the OSL Software License (see LICENSE.txt), and is free for non-commercial distribution. Also included are modified files from TinyOS (BSD and Intel Open Source licenses) and LAPACK 3.0 (no formal license, free for redistribution); these licenses are indicated at the top of the respective files.

EcoWizard: Next Generation Energy Monitoring System

Crossbow Japan Ltd., a subsidiary of Crossbow Technology, Inc., along with strategic partner Sumitomo Precision Products Co., Ltd. announced today the availability of the EcoWizard Wireless Energy Monitoring System. EcoWizard enables users to analyze and monitor energy consumption in real-time using intuitive visualization tools allowing intelligent and efficient energy conservation.

Using leading-edge wireless sensor networking technology EcoWizard offers various energy measurement modes such as watt-hour by RS485, current transformer, and pulse inputs, while significantly reducing the installation costs associated with current solutions. The newly developed data viewer provides numerous options and increased functionality with simple graphical displays of past and present energy consumption (electricity, temperature, etc.).

Crossbow Japan, who has been supplying customized wireless energy solutions to the Japanese market for several years, has now expanded its offering to the public sector with the introduction of EcoWizard. This energy sensing and monitoring system is a cost-effective solution for users in many countries who are now faced with strict energy conservation policies and legislation. The need for a solution that quickly and easily facilitates energy savings is here. Crossbow’s expertise in sensing and wireless network solutions have shaped EcoWizard and launched an advanced system for smart and effortless energy monitoring and conservation.

System Features

• Complete Hardware Monitoring Solution - Sensors for electric power consumption, water, gas, temperature, humidity, light, etc. including pulse input wireless nodes enabling data acquisition from typical gas or water gauges.
• Multi-functional Software Package - The flash-based application is simple to operate, allowing intuitive data viewing. The graphical displays enable identification of total and individual local power consumption instantly. Data can be exported to CSV format, permitting easy report creation. The system offers real-time monitoring and data logging, with built-in alert capability when sensor data exceeds the predetermined threshold.
• Low-cost Installation - Compared to current wired systems, installation or layout changes take a significantly shorter time, leading to increased cost savings. Crossbow's XMesh enables a multi-hopping ad-hoc network between sensor nodes to relay data back to the base station. If the wireless connection is interrupted, the system will automatically re-route to ensure complete data transfer from all nodes to the base station. The sensor nodes are built on the NeoMote product from Sumitomo Precision Products who have deployed over 30,000 nodes for customized industrial sensing.

Pricing and Availability
EcoWizard is priced competitively. The system will be immediately available for purchase in November 2009. Sales inquiries may be directed to sales@xbow.com.

About Crossbow Japan
Established in 2005, Crosbow Japan Ltd. is a joint partnership of Crossbow Technology, Inc. San Jose and Sumitomo Precision Products Co., Ltd. located at the Sumitomo Precision Products’ complex in Amagasaki, Hyogo, Japan. Sumitomo Precision Products has been developing and manufacturing industrial grade wireless sensor networks under the license of Crossbow Technology, whose sales are conducted by Crossbow Japan, Ltd. Founded in 1995, Crossbow Technology, Inc. is the leading end-to-end solutions supplier of wireless sensor networks for diverse applications such as industrial automation, building monitoring, home automation, environmental control, structural monitoring and asset tracking.

Crossbow in the Smithsonian!

The Ghostrider comic character was said to possess superhuman strength and durability with the ability to travel between realms and along any surface... the same mission of Berkeley's Blue team who was sponsored by Crossbow Technology when they entered the Pentagon's DARPA Grand Challenge and perhaps why they named their creation the Ghostrider - the only two-wheeled vehicle in that robot car race.

The original DARPA Grand Challenge was intended to accelerate the development of autonomous vehicle technologies by offering a cash prize of $1 Million to the team that built an autonomous robotic ground vehicle that would successfully win a race from Los Angeles to Las Vegas. This specific endeavor was targeted to find smart solutions that would be tested in a realistic scenario under challenging race conditions - something that had never been done before on this scale. Although none of the vehicles completed the course, and the cash prize was not awarded, a tremendous amount was learned about autonomous ground vehicle technology inspiring the future DARPA challenges.

Enjoying a vacation in our nation's capital a few weeks ago, Crossbow's Director of Software for our Inertial Systems, Darren Liccardo stumbled upon the Ghostrider bearing Crossbow's blue and white logo proudly - immortalized in Washington D.C where it has been inducted into the Smithsonian's National Museum of American History's Collections. Ghost Rider was part of the “Robots on the road” display in the "Looking Ahead" gallery, which was in the “Science in American Life” exhibit.

Ghostrider drove itself without a human rider or remote controls. Utilizing Crossbow's 400 series product as part of its system for balance and control, the modified motorcycle was able to navigate, balance and right itself independently.

For information on the Ghostrider robot visit the team's website here.
For details on Crossbow's inertial systems, visit the site here.

Structural Health Monitoring

Part 1 Hardware

Investment in civil infrastructure in the United States alone is estimated to be $20 trillion. Moreover, annual costs amount to between 8-15% of the GDP for most industrialized nations, and this investment is only likely to increase. Much attention has been focused in recent years on the declining state of the aging infrastructure in the U.S., such as the nation's bridges, highways, and buildings. The ability to continuously monitor the integrity of civil infrastructure in real time offers the opportunity to reduce maintenance and inspection costs, while providing increased safety to the public.

Bridges account for a large part of the capital investment in constructing road networks and represent a key element in terms of safety and functionality of the entire highway system. As such, informed bridge management is important to provide the public with timely transportation while maintaining a high level of safety. Manual inspection of bridges costs millions of dollars, is relatively unreliable, and can only be carried out sporadically. Recent years have seen tremendous attention directed toward development of structural health monitoring strategies, with the primary outcome sought being enhanced safety and reliability, with reduced maintenance and inspection costs. Many of the recently constructed bridges have in-depth monitoring systems; for example, the Stonecutters Bridge in Hong Kong which has over 1200 sensors. However, the enormous expense of installing traditional monitoring systems has significantly limited deployment. For example, the total system cost of the monitoring system (including installation) on the Bill Emerson Memorial Bridge in Cape Girardeau, Missouri, USA is approximately $1.3M for 86 accelerometers, which makes the average installed cost per sensor a little over $15,000. Average per node cost for other wired bridge monitoring installations are of a similar magnitude.

The Illinois Structural Health Monitoring Project (ISHMP), based at the University of Illinois at Urbana-Champaign (UIUC), is working to develop an inexpensive means for continuous and reliable SHM (Structural Health Monitoring) using dense arrays of wireless smart sensors. Researchers have designed, developed, and tested sensors to produce the high-fidelity data required for SHM that can be manufactured very cheaply. Their research has also produced a customizable software framework that simplifies the development of SHM applications for smart sensor platforms. In combination, their sensors and software create an integrated framework that can easily be utilized by most civil engineers without requiring an extensive background in computer science!

ISHMP researchers have focused on Crossbow’s Imote2, because they believe that it to be the only commercially available wireless sensor platform that can meet the high-data throughput demands of SHM applications. The powerful processor and the onboard memory of the Imote2 are the features that set it apart from other wireless sensor platforms and allow its use for the high-frequency sampling required for dynamic structural monitoring. The Imote2 has a low-power X-scale processor (PXA27x) with variable processing speed to optimize power consumption. Moreover, it has 256 KB of integrated RAM, 32 MB of external SDRAM, and 32 MB of flash memory.

The Structural Health Monitoring Accelerometer (SHM-A) sensor board was designed to meet the specific needs of SHM by Prof. Jennifer A. Rice from Texas Tech University as part of her PhD research at UIUC. The board provides flexible and accurate user-selectable sampling rates and anti-aliasing filtering capabilities to account for the local nature of structural damage where higher mode responses of the structure are often required (up to 500 Hz) in addition to low-frequency signals (DC to 20 Hz). To avoid potential signal errors, especially in the higher frequency range, minimizing sample-rate fluctuation (jitter) is critical. While simply interfacing an analog accelerometer with a high-quality ADC could address the sampling rate issues, a programmable signal conditioner was chosen because of the flexibility it provides the user in terms of anti-aliasing and signal processing. The key component of the SHM-A board is the Quickfilter QF4A512, a versatile, 4-channel ADC and programmable signal conditioner with user-selectable sampling rates and programmable digital filters. The board interfaces with the Imote2 via SPI and I2C I/O and has a 3-axis analog accelerometer for vibration measurement, one general analog input, as well as digital temperature, humidity and light sensors. One purpose of the temperature sensor is to provide onboard temperature compensation to the acceleration data. The SHM-A board provides the enabling technology that had been previously lacking to perform structural health monitoring using the Imote2.

Full-scale Implementation

After much testing and lab work, ISHMP researchers moved forward on the full-scale monitoring of the Jindo Bridge in South Korea in June. The Jindo Bridge is Korea's first cable-stayed girder bridge. A joint project between University of Illinois at Urbana-Champaign, KAIST in Korea, and the University of Tokyo in Japan, this deployment constitutes the first dense deployment of a WSN on a cable-stayed bridge. Installed with 70 nodes, the deployment is largest of its kind for civil infrastructure to date.

Prior to deploying the smart sensor network on the Jindo Bridge, the Imote2 and sensor board stacks were housed in enclosures that provided protection against environmental conditions such as rain, wind and dust. The enclosures had a gasketed lid and the ability to mount to the structure. Several nodes were designed to accommodate larger battery sources, while some were designed to utilize integrated solar panels.

Smart sensing technology for structural health monitoring is an emerging field that, by combining civil engineering knowledge with developments in sensor technology, information management, and networking technologies presents a solution that is a robust, significantly lower-cost (~$500/node), alternative to traditional structure inspection techniques. This process of implementing a damage detection and characterization strategy for engineering structures has changed the idea of SHM. The SHM process involves the observation of a system over time using periodically sampled dynamic response measurements from an array of sensors, the extraction of damage-sensitive features from these measurements, and the statistical analysis of these features to determine the current state of system health.

For more details on the Imote2 platform visit Crossbow's site here.

For more information on the SHM sensor board developed at UIUC visit the ISHMP site here and view a detailed report on the development and implementation here.

Stay tuned for Part 2 of the Jindo Bridge Deployment related to the software strategy implemented...

WSNs See Through Walls

Researchers at the University of Utah SPAN lab have found a way to see through walls to detect movement inside a building using wireless sensor networks!

The surveillance technique is called variance-based radio tomographic imaging and works by visualizing variations in radio waves as they travel to nodes in a wireless network. A person moving inside a building will cause the waves to vary in that location, the researchers found, allowing an observer to map their position.

The researchers, electrical engineering graduate student Joey Wilson and his faculty advisor Neil Patwari, have tested the technique with a 34-node wireless network using the IEEE 802.15.4 wireless protocol and TelosB hardware. By “interrogating” the space with signals and multiple receivers, the researchers found they were able to read the waves to detect the location of a moving object within a meter of accuracy.

In a mission-critical application, the researchers envisioned a building imaging scenario similar to the following: Emergency responders, military forces, or police arrive at a scene where entry into a building is potentially dangerous. They deploy radio sensors around (and potentially on top of) the building area, either by throwing or launching them, or dropping them while moving around the building. The nodes immediately form a network and self-localize, perhaps using information about the size and shape of the building from a database (e.g., Google maps) and some known-location coordinates (e.g., using GPS). Then, nodes begin to transmit, making signal strength measurements on links which cross the building or area of interest. The RSS measurements of each link are transmitted back to a base station and used to estimate the positions of moving people and objects within the building.

Locating interior movement from outside of a building is extremely valuable in emergency situations, enabling police, military forces, and rescue teams to safely locate people prior to entering. Variance-based radio tomography is a powerful new method for through-wall imaging that can be used to track the coordinates of moving objects. The cost of VRTI hardware is very low in comparison to existing through-wall imaging systems, and a single network is capable of tracking large areas. These features may enable many new applications that are otherwise impractical.

OceanSense: Realtime Ocean Environmental Sensing

How important are the oceans? Earth is the only planet in the Solar System that has a vast open ocean of liquid water, and it is the ocean that makes our planet uniquely life-bearing. Today, ocean life is regarded by many as more important in the total scheme of things than even plant life on land. There are microscopic plant cells in the top layer of the ocean that produce four times as much oxygen and food as plants on land produce. The bottom line is that there is no life without water and the global ocean is the defining characteristic of our planet. It is the original ecosystem.

Oceanography is of great importance for human beings. For hundreds of years, people have been recording ocean environmental data from scientific expeditions to coastal environmental research. However, even today the only real-time environmental data observation method is through Argo (Array for Real-time Geostrophic Oceanography), which does not come close to meeting the true requirements of oceanography research. Researchers at the Ocean University of China have developed a wireless sensor network for environmental monitoring at sea believing that with the recent progress of sensor networks - it is the tool for the future collection of data for oceanography research.  

Deployed off the seashore near the Moutain LAO of Qingdao, China, OceanSense is a system designed to obtain ocean environmental data in real-time. Using the TelosB Mote platform, the nodes are deployed on the surface of the sea collecting environmental data, such as temperature, light, tide velocity, sensor depth and RSSI from the testbed. The TelosB Motes were encapsulated in bottles and attached to lightweight supporting equipment to make them waterproof as well as raise them 1m above the ocean surface to enable optimal signal strength. To view the process used to create these ocean ready nodes, watch this video that shows the testing, creation and deployment of the OceanSense System.

The OceanSense system has been running for more than half a year, providing environmental monitoring data for further study. The motes communicate with the base station, which transmits collected data to a visualization system running on a database server. Users may then access the data using a browser-based web application that provides a scalar field mapping tool to depict temperature and light intensity as well as a vector field mapping tool to display the tide velocity.

The current system consists of 20 sensor nodes deployed in the field, reporting sensing data continuously to the base station. The complete system is designed to scale to hundreds of sensors covering the sea area off Taipingjiao, Tsingtao. For more information on the OceanSense solution visit the site here and click on the video below for a brief demo of the system and the deployment.

Contiki Port for Crossbow's MICAz Mote

Contiki is an open source, highly portable, multi-tasking operating system for memory-efficient networked embedded systems and wireless sensor networks. It has been used is a variety of projects, such as road tunnel fire monitoring, intrusion detection, water monitoring in the Baltic Sea, and in surveillance networks.

Designed for microcontrollers with small amounts of memory and providing IP communication, both for IPv4 and IPv6, a typical Contiki configuration is 2 kilobytes of RAM and 40 kilobytes of ROM. As of yesterday, there was a new Contiki target in the development code: a port for Crossbow's MicaZ Mote, the popular prototyping and research platform for wireless sensor networks. The MicaZ port was developed by Kasun Hewage from the University of Colombo School of Computing, Sri Lanka.

Contiki is developed by a group of developers from industry and academia lead by Adam Dunkels from the Swedish Institute of Computer Science. Dunkels was recently named by Technology Review as one of the Top Young Innovators under 35 in 2009 for his development of minimal wireless-networking protocols that allow almost any device to communicate over the Internet. He wrote the uIP for Crossbow's TelosB Mote platform.

The Contiki team currently has sixteen members from SICS, SAP AG, Cisco, Atmel, NewAE and TU Münich. For more information on this operating system visit the Contiki site here.

eKo Environmental System Expanded with Long Range Node

Crossbow Technology Adds High Range Capability to eKo Pro Series

SAN JOSE, Calif.--Crossbow Technology, Inc. (www.xbow.com/eko), a leading supplier of wireless sensor technology and cutting-edge environmental monitoring solutions, announced today the release of the EN2120 eKo Long Range Node. With the communication range between nodes extending up to 2 miles, the eKo Long Range node is the only true mesh wireless solution with this ability, increasing the coverage area four to five times that of other wireless solutions.

“The eKo system and specifically the new EN2120 Long Range Node allows users to gather data from a larger area with less nodes thereby reducing their installation costs and simultaneously expanding their coverage area,” said Jack Coots of Iris Connection, Inc. “In the Central Valley users have large fields and orchards making this capability crucial to enable complete cost-effective monitoring of their planted acreage.”

The Long Range Node addresses deployments with substantial areas, dense canopies and remote locations enhancing the capability of the standard eKo Node while still using the same form factor and solar recharging scheme. The eKo system provides users with the ability to collect data from multiple points through their entire site providing a micro level of detail regarding various critical parameters affecting their environment instead of relying on information from a single point.

“Using the eKo Long Range Node, we have been able to collect real-time data over a large area of the reserve with fewer nodes,” said Mike Hamilton, Reserve Director at the University of California Blue Oak Ranch Reserve. “Regardless of the varying terrain, wildlife, and vegetation, we were able to quickly and easily install the eKo system and collect vital data pertaining to our ecological and environmental research.” 

Pricing and Availability 

The eKo Pro Series System and related sensors including the new EN2120 Long Range Node is priced competitively. The system is immediately available for purchase from select distributors and online directly at www.xbow.com/eko. Sales inquiries may be directed to eKo.sales@xbow.com.

Flying Magazine Highlights Crossbow's Efforts

Excerpts from Flying Magazine 2009 Issue

Robert Goyer, Senior Editor at Flying magazine, recently flew up to Olathe, Kansas, home to Bendix/King's flight test development facility to fly the KFD840. In the current issue, Goyer relays the details of this experience:

A funny thing happened in the race to develop retrofit avionics systems for light airplanes: competition. Just a few years ago the price of a retrofit LCD primary flight display for your light single or twin was... well there was no such thing. What a difference a few years makes...With the introduction of the KFD840, Bendix/King (a division of Honeywell) has jumped into the fray, bringing to the game not only its legendary name but much of the expertise that has gone into its sister company Honeywell's Primus Epic flat-panel systems which are standard equipment in some of the most technologically advanced and expensive business jets in the world.

The KFD840 is Bendix/King's new Primary Flight Display (PFD) for piston powered aircraft and is the company's vision of what a flat-panel retrofit primary flight display should be. The display was installed in the company's Cessna 182 test bed (the same type of aircraft owned by Crossbow Technology and used for all of its development and validation flight tests) which was a great platform for the test as it represented the kind of mid-level single into which one of these new lower-priced retrofit PFDs are finding their way.

The philosophy behind the 840 is clear: to create a smart-sized, low-cost, elegant, easy-to-use, reliable and expandable system that many pilots will be able to afford to put in their panels.The most remarkable thing about retrofit flat-panel avionics systems is how competitive they are in terms of price. The suggested price for the KFD840 is $16,995 largely due to Crossbow Technology's internal ADAHRS. With solid-state ADAHRS, the mean time between failures is off the charts and the redundancy of the systems, especially with the optional battery backup is a huge improvement over most conventional vacuum powered systems.

“We see significant interest in the retrofit market for “glass cockpit” technology that makes flying easier and safer such as solid state sensors and a wide horizon. For many aircraft this will allow a pilot to add a second attitude, airspeed and altitude source, improving safety.” said Dan Barks, Business Director, GA Operators and Dealers at Honeywell. “And by working with Crossbow Technology Inc. we can allow the piston aircraft pilots to be able to have a certified glass cockpit for under $20,000, a breakthrough price point for that segment.”

Aesthetically, the 840 is clean and businesslike. There are relatively few buttons and knobs. A pair of dual concentric knobs one at either end, and five semisoft keys lined up along the bottom of the bezel are it. It represents a way to upgrade the panel with solid-state attitude and air data while being dirt simple to transition to and at a price that even a few years ago seemed simply impossible.

Crossbow is anticipating TSO approval at the end of Q3 2009. For more information on Crossbow's line of inertial systems, visit the site here.

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