In a BLIP, pervasive IP has arrived.

by Martin Turon, Director of Wireless Software, Crossbow Technology, Inc.

IPv6 was invented in 1998, over ten years ago, yet less than 1% of devices use it.

Why is IPv6 important?

The first answer is "lots of addresses".

Think of your PC and the RAM memory inside. Until recently, 32-bit processors were pervasive, and you couldn't put more than 4GB (4 billion bytes) of memory in them because of the limits in 32-bit address spaces. Now most new computers are 64-bit, and they can address 18 quintillion bytes. The Internet will eventually be forced to "upgrade" its address space as well. Currently over 99% of devices use IPv4 which uses 32-bit IP addresses that are most commonly displayed as 4 bytes in decimal: 192.168.1.100. If you want to host a web server to the world, you typically claim a static IP and one of the 4 billion possibilities is yours forever. But the population of the world is 6.7 billion, so there aren't enough to go around! And what if everyone wants multiple devices that can be uniquely addressed to serve some critical information like a cluster of wireless sensor nodes?

IPv6 is clearly the answer. It provides a 128-bit address space allowing for over 240 undecillion uniquely addressable devices. To put that in perspective, the soon-to-be 6.8 billion people in the world will each be able to have over 300 million subnets with over 18 quintillion devices in each one. That is a total of over 50 octillion uniquely addressable devices per person!  Note: The unallocated address pools in IPv4 are anticipated to be exhausted in 2012.

Which leads to the second answer: "government mandates".

In May 2009, the Federal CIO Council of the US government issued an official roadmap for IPv6 adoption. The report provides a detailed overview of the technology, it's benefits, tips on the various services and how to transition. It also tasks other government agencies with developing concrete plans for how they will deploy IPv6 and requires quarterly review of their progress.

"We can't keep operating in an IPv4 world when we're talking about sensor networks, wireless communications and mobile networks. We need more IP addresses - globally unique IP addresses - and that's what IPv6 provides. We need a target network architecture that's scalable, secure and stable." - Pete Tseronis, Federal IPv6 Working Group Chair and Deputy Associate CIO of the Department of Energy

Since the release of this document, a flurry of articles regarding IPv6 adoption has been written up in the press.

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How can big IPv6 addresses fit on tiny motes?

Almost in anticipation of the recent uptick in IPv6 adoption, back in March some researchers at UC Berkeley released an Open Source implementation of IPv6 running on TinyOS 2.x called BLIP (Berkeley Low-power Internet Protocol). The BLIP stack runs on mote-class hardware, specifically the TelosB and MicaZ. How did they manage to fit a protocol that uses 128-bit addresses onto a platform with only 4KB of RAM? Well, beyond the fact that Stephen Dawson-Haggerty and other contributors are really really smart, the IETF has had a number of efforts to define ways for IPv6 to run on lossy, low bandwidth links for a while. The IETF timeline follows:

RFC 1883,2460 - IPv6 Specification
RFC 1885,4443 - ICMPv6 Internet control message protocol
RFC 3142 - IPv6-to-IPv4 translation
RFC 3315,4580,4649,4704 - DHCPv6 Dynamic, automatic address assignment
RFC 4861 - Neighbor Discovery
RFC 4862 - Stateless Addr Autoconf
RFC 4944 - IPv6 over IEEE 802.15.4 (6LowPAN) 

Drafts: HYDRO routing (part of ROLL [routing over low-power, lossy links] effort)

Papers: IP is dead, long live IP,  Extended Internet Architecture PhD Thesis by Jonathan Hui

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Why is it cool?

IPv6 running on motes is cool because it really leverages what IPv6 was designed for -- ubiquitous computing.  Imagine a day when all of your appliances and consumer electronics will be able to talk to each other and provide you real time data on their energy usage, health, etc.  The ZigBee alliance has recently signed up to define a specification for an IPv6 stack in addition to an RF4CE stack for remote controls and consumer electronics.  Similar to how WiFi is integrated into all sorts of products today and just works, ZigBee may make it so cheap, tiny devices of the future can provide direct IPv6 connectivity over low-power, low-bandwidth radios.

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What is the status of BLIP?  When will it be released?

BLIP is a work in progress.  It is currently fully supported on the TelosB platform and works on MICAz when compiled in a memory-constrained mode.  It is being folded into the TinyOS 2.x core with a slated release date of late August 2009.  The version in contrib/berkeley/blip is the correct one to use, however, as that one will actually build without manually adding radio stack modifications that are still being negotiated.  IRIS support is in the works as well with the initial port being done by European researchers Miklos Maroti and Lars Schor.  An improved release candidate of BLIP is slated to be pushed into contrib as early as next week.

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Where can the BLIP source code be found?  How do you use it?

1) Download Xubuntos 2.1 VMware image (Howto)
2) Start the VM, login as:
  username: xubuntos
  password: tinyos
3) Start a Terminal
4) Prepare your VM to run BLIP as follows:

- Install IPv6 tools:

    sudo apt-get install netcat6

- Update tinyos-2.x trees from CVS:

    cd /opt
    # hit return for anonymous password
    cvs -d:pserver:anonymous@tinyos.cvs.sourceforge.net:/cvsroot/tinyos login
    cvs -z3 -d:pserver:anonymous@tinyos.cvs.sourceforge.net:/cvsroot/tinyos co -P tinyos-2.x
    cvs -z3 -d:pserver:anonymous@tinyos.cvs.sourceforge.net:/cvsroot/tinyos co -P tinyos-2.x-contrib/berkeley

- Add a simple environment setup script

cd /opt/tinyos-2.x-contrib/berkeley/blip
cat <<-EOF > setenv
export TOSROOT=/opt/tinyos-2.x
export TOSDIR=/opt/tinyos-2.x/tos
export LOWPAN_ROOT=$PWD
export TOSMAKE_PATH="$LOWPAN_ROOT/support/make"
EOF

- Build the driver

    cd /opt/tinyos-2.x/support/sdk/c/sf
    ./bootstrap
    ./configure
    make
    cd /opt/tinyos-2.x-contrib/berkeley/blip/support/sdk/c/blip
    make

- Patch motelist to handle mib520 for micaz discovery

cd ~
cat <<-EOF > motelist-linux.mib520.patch
--- motelist-linux	2006-12-12 10:23:01.000000000 -0800
+++ /usr/bin/motelist	2009-05-19 11:28:26.000000000 -0700
@@ -61,7 +61,10 @@ sub scan_sysfs {
 
 # Scan /sys/bus/usb/drivers/usb for FTDI devices
 my @ftdidevs =
- grep { (\$_->{UsbVendor}||"") eq "0403" && (\$_->{UsbProduct}||"") eq "6001" }
+ grep { (\$_->{UsbVendor}||"") eq "0403" && 
+ (((\$_->{UsbProduct}||"") eq "6001") || 
+ ((\$_->{UsbProduct}||"") eq "6010")) 
+ }
 map { {
 SysPath => \$_,
 UsbVendor => snarf("\$_/idVendor",1),
EOF
cd /usr/bin
sudo patch -p0 < motelist-linux.mib520.patch

- Download Blip.micaz.patch

 - Patch the blip contrib sources to add automatic micaz support
and fix some build issues.

    cd /opt/tinyos-2.x-contrib/berkeley/blip
    patch -p0 < ~/blip.micaz.patch

5) Use your prepared VM to build and deploy BLIP:

- Enable the BLIP build environment:

    cd /opt/tinyos-2.x-contrib/berkeley/blip
    source setenv

- Build the UDPEcho app and base station for telosb and micaz:

    cd /opt/tinyos-2.x-contrib/berkeley/blip/apps/UDPEcho
    make telosb blip
    make micaz blip

    cd /opt/tinyos-2.x-contrib/berkeley/blip/apps/IPBaseStation
    make blip telosb
    make blip micaz

- Connect a TelosB via USB, and flash it with the base station code
(Install FTDI drivers if needed)
(Accept TelosB device when dialog appears)
(Right click USB device in lower right of VM and select connect)

    motelist # find ttyUSB port to use
    cd /opt/tinyos-2.x-contrib/berkeley/blip/apps/IPBaseStation
    make blip telosb install,64 bsl,/dev/ttyUSB0

- Connect a MicaZ via USB, and flash it with the remote node code
  (Install FTDI drivers if needed)
  (Accept MIB520 device when dialog appears)
  (Right click USB device in lower right of VM and select connect)

 	 
    motelist # find ttyUSB port to use
    cd /opt/tinyos-2.x-contrib/berkeley/blip/apps/UDPEcho
    make blip micaz install,1 mib520,/dev/ttyUSB0

6) Fire up Linux network driver to communicate with BLIP network:

- Start the ip-driver

    cd /opt/tinyos-2.x-contrib/berkeley/blip/support/sdk/c/blip
    sudo ./ip-driver /dev/ttyUSB0 telosb
    # password: tinyos	 
    # blip console commands:
    # blip:xubuntos-tinyos> help
    # blip:xubuntos-tinyos> log WARN
    # blip:xubuntos-tinyos> routes	

7) Use standard IPv6 tools to access the remote BLIP nodes:

    # Ping - base station and remote node
    ping6 2001:470:1f04:56d::64
    ping6 2001:470:1f04:56d::1

    # Access shell on remote node
    nc6 2001:470:1f04:56d::1

Note that BLIP ships with support for pinging a node with standard the ping6 tool, shelling into a node with netcat (the shell is a custom one, not ssh, type help to see available commands), and over-the-air reprogramming of nodes with a deluge-like interface.  BLIP is an exciting software development for the TinyOS community and users of TelosB, MICAz, and soon IRIS platforms.  We encourage you to try it and track its rapid development.

Martin Turon is Crossbow's Director of Wireless Software. Not only an expert in the field of wireless sensor networks, Martin has been instrumental in simplifying the WSN user experience with advancements in interface and server tools using his background in video game design, mobile phone software and operating systems. He is the current Chair of the ZigBee WSN group which is working to establish the standard for low-power routing while leading the Wireless software development team at Crossbow for future product enhancement. Martin obtained degrees from University of California, Berkeley in Electrical Engineering and Computer Science. He has also studied Artificial Intelligence at University of California, Los Angeles and received a certificate in Math for Financial Engineering from Haas Business School. Martin is an avid lover of indie rock and performs with various ad-hoc musical projects.

Landslide Detection for Mountainous Regions

The Times of India reported today on a wireless sensor solution developed by students of Amrita Vishwa Vidyapeetham University for landslide detection. This development effort used Crossbow's MICAz Mote platform and was done in collaboration with the European commission and Indian Space Research Organisation (ISRO). This pilot deployment of India's first landslide detection system with wireless sensor networks was put in place at Munnar, Idukki, Kerala, India. This implementation brought together scientists from diverse fields such as geology and geophysics, mechanical,computer, electrical, electronics, and communication engineering to save human lives, preserve the environment, and mitigate property damage.

The devastation and loss of life caused by landslides affects hundreds of people every year around the world. Amrita University's rainfall induced landslide detection system uses a heterogeneous network that included wireless sensor networks in combination with Wi-Fi and satellite technology. The pilot site chosen for this study is highly prone to landslides due to systemic monsoon induced rainfalls in the region.

"Landslides occur frequently in mountainous terrains, especially during monsoons but detecting them in advance is not an easy task,'' says Dr P Venkat Rangan, vice chancellor, Amrita university. An expert in wireless communication, Rangan led a team of students in developing the model that has become operational in Munnar town in the Idukki district of Kerala.

This breakthrough technological system was developed as part of the research project WINSOC (Wireless Sensor Network with Self-Organisation Capabilities for Critical and Emergency Applications). Wireless panels with sensor nodes to read different soil parameters such as moisture, vibration and movement were embedded 15 metres beneath the earth at different points, says Maneesha Ramesh, a faculty member, who was part of the project.

The actual deployment site in the Idukki district built on the existing setup at Munnar as it provided the infrastructure needed for retrieving geological and hydrological data from the field as it was necessary for the data to be transmitted a long distance for further analysis. The data received from the geophysical sensors were transmitted through the wireless sensor network which used a two layer hierarchical topology.

The sensors were attached to a wireless transmission device, in this case Crossbow's MICAz Mote platform, which would then convert the analog value into a digital value and send the inputs to the base stations, which were connected to Amrita mutt's Kollam campus. "Experts will be monitoring the inputs from the base stations in real time and any unusual behaviour or extreme value will trigger an alarm,'' says Dr Rangan.

Multiple sets of geophysical sensors are located in a distributed manner inside a column, referred to as the 'sensor column'. The sensor columns are approximately 5 -6 meters long and are buried deep inside the earth and the data from them are retrieved using lower layer wireless sensor nodes attached to the sensor columns.

The lower layer wireless sensor nodes were wirelessly connected to a hierarchy of upper level wireless nodes that would forward the data on to a Gateway. The data was then sent via a directional Wi-Fi link to a Field Data Management Center (FMC). The data was then forwarded over a satellite link to the Data Management Center (DMC) which has sophisticated landslide data processing and modeling capability, located at Amrita University, Amritapuri campus which is situated approximately 252 kilometers away from the deployment field.

The fully tested model has become operational in Munnar. The system can be deployed in any part of the country prone to landslides and snow avalanches. The application could also be put to industrial use for the study of gas leakages or in conservation of forests by early identification of forest fires during summer.

As part of this project, representatives from various European partners like University of Rome, Selex Communications, Intracom Telecom, Czech Centre for Science and Technology arrived at the Amrita University to learn about the first-ever wireless sensor network system for landslide detection. The Amrita wireless sensor network system for landslide detection has been developed as part of WINSOC which is co-funded by INFSO DG of European Commission.

Testbed Testing

Wireless sensor network testbeds are critical for understanding and meeting the technical challenges of networks deployed in real world scenarios. Hardware and software testbeds have become the preferred basis for experimenting with embedded wireless sensor network applications. They provide a means for developing and evaluating sensor network technology in a controlled and instrumented environment. Experimentation with current hardware and software platforms, allows users to not only demonstrate applicability in real environments but also to validate prototypes. Compared to field deployments, the testbeds yield substantial efficiency in instrumenting potentially long-lived experiments, which is valuable in the debugging, validation, and integration phases of reliable wireless sensor networks. Universities and labs across the world have set up networks of hundreds of nodes using a Mote platform from Crossbow's suite of wireless sensor network devices choosing from simple platforms such as the TelosB to advanced devices like the Imote2.

Researchers at the University of Buffalo, SUNY and Georgia Institute of Technology have written an article focused on the the idea of taking wireless testbeds to the next level by incorporating multimedia and characterizing the challenges of wireless multimedia sensor networks (WMSNs). The availability of low-cost hardware has enabled the development of WMSNs, i.e., networks of resource-constrained wireless devices that can retrieve multimedia content such as video and audio streams, still images, and scalar sensor data from the environment, along with standard wireless sensor networks. Research is being conducted on prototypes of multimedia sensors and their integration into testbeds for experimental evaluation of algorithms and protocols for WMSNs. Open research issues and future research directions, both at the device level and at the testbed level, are discussed and tested constantly.  Network testbeds allow the effectiveness of algorithms and protocols to be evaluated by providing a controlled environment for measuring network performance.

Every testbed utilizes a specific Mote platform that is optimized for that particular testbed's focus. The wireless sensor platform is chosen based on its available capabilities to allow for multimedia integration. A WMSN is a distributed wireless system that interacts with the physical environment by observing it through multiple media. Furthermore, it can perform online processing of the retrieved information and react to it by combining technologies from diverse disciplines such as wireless communications and networking, signal processing, computer vision, control, and robotics. Applications in the real world that would benefit from WMSNs were categorized into the categories of surveillance, traffic monitoring and enforcement, personal and health care, gaming, and several elements of environmental and industrial monitoring by researchers at SUNY, Buffalo and Georgia Tech. Testbeds allow the observation of the performance of the WMSN in a controlled environment. Hence, the effect of different types of inputs, physical operating conditions, and subjects for sensing can be studied, and the functioning of the devices in the testbed may be changed appropriately for accurate measurement. A few WMSNs developed are outlined below:

A visual sensor testbed was developed as part of the Meerkats project to measure the tradeoff between power efficiency and performance. Results revealed that there was significant energy consumption in keeping the camera active, and writing the image to a Flash memory followed by switching the camera off conserved energy. There was also a finite instantaneous increase in the energy consumption due to state transients. Researchers were also able to determine that the processing-intensive benchmark resulted in the highest current requirement, and transmission was shown to be only about 5% more energy-consuming than reception.

Expandable, vision-, and sensor-equipped wireless robots with MICA sensor motes for networking were designed in the Explorebots testbed architecture. The target localization experiments on the testbed, composed of these mobile robots, used on board multimedia sensors such as custom-designed velocity and distance sensors, motor movement control, an in-built magnetic two-axis compass, and sonic sensors. By processing the sound and light sensors outputs, the robots were guided towards the target source.

The Mobile Emulab network testbed provided a remotely accessible mobile wireless and sensor testbed. Robots carried motes and single-board computers through an indoor field of sensor-equipped motes. A remote user could position the robots, control all the computers and network interfaces, run arbitrary programs, and log data in a database. The path of robots, which was also equipped with Webcams, could be planned, and a vision-based system provided positioning information with an accuracy within 1 cm.

IrisNet (Internet-scale resource-intensive sensor network services) was an example software platform for a heterogeneous WMSN testbed. Video sensors and scalar sensors were spread throughout the environment and collected potentially useful data. IrisNet allowed users to perform Internet-like queries to video and scalar sensors that spread throughout the environment. The architecture of IrisNet was two-tiered: heterogeneous sensors implemented a common shared interface and were called sensing agents (SAs), while the data produced by sensors was stored in a distributed database that was implemented on organizing agents (OAs). Different sensing services were run simultaneously on the architecture. For example, a set of video sensors could provide a parking-space finder service, as well as a surveillance service.

In the design and implementation of SensEye, a multiple-tier network of heterogeneous wireless nodes and cameras, was created to test surveillance applications. Each tier comprised nodes equipped with similar cameras and processing ability, with increasing resolution and performance at each stage. The lowest tier consisted of low end devices, i.e., MICA2 Motes equipped with 900 MHz radios interfaced with scalar sensors, e.g., vibration sensors. The second tier was made up of motes equipped with low-fidelity Cyclops or CMUcam camera sensors. The third tier consisted of Stargate nodes equipped with Webcams that could capture higher fidelity images than tier 2 cameras. Tier 3 nodes also performed gateway functions, as they were endowed with a low-data-rate radio to communicate with motes in tiers 1–2.The aim was to efficiently undertake object detection, recognition and tracking by triggering a higher tie into the active state based on a need basis.

The WMSN-testbed at the Broadband Wireless Networking (BWN) Laboratory at Georgia Tech was based on commercial off-the-shelf advanced devices and had been built to demonstrate the efficiency of algorithms and protocols for multimedia communications through wireless sensor networks. The testbed was integrated with the scalar sensor network testbed, which was composed of a heterogeneous collection of Imote and MICAz motes from Crossbow. The testbed allowed the integration of heterogeneous devices in experimental testbeds and some succesful examples in developing APIs and system software for WMSNs.

These are just a few of the various wireless sensor network testbeds found worldwide. Crossbow's vast portfolio of wireless sensor platforms provides researchers and government/commercial users with the equipment they need to set up a lab for their wireless sensor course or to verify their specifications prior to real world deployment of their wireless sensor network. For information on how to set up your own WSN testbed or for details on Crossbow's wireless sensor network platforms, contact sales@xbow.com.

Professors design AK47-locating 'smart dust' helmets

Last week Vanderbilt University's inhouse Exploration newsletter reported on the gunshot-locator net developed by the university's Institute for Software Integrated Systems (ISIS). Crossbow's Mote platforms were once again highlighted in their use for the shooter location system. Acoustic gunshot detectors have become common in the past few years, and some have been reduced in size to where a single soldier can wear one on his uniform and be cued-in to an enemy's location as soon as he fires. Engineers at ISIS have developed a system that can give soldiers just such an edge by turning their combat helmets into "smart nodes" in a wireless sensor network.

Current systems rely on centralized or stand-alone sensor arrays. This limits their accuracy and restricts them to identifying shooters at line-of-sight locations. By contrast, the ISIS system combines information from a number of nodes to triangulate on shooter positions and improve the accuracy of its location identification process. It also uses a patented technique to filter out the echoes that can throw off other acoustic detection systems, explains Akos Ledeczi, the senior research scientist at ISIS who heads up the development effort.

ISIS developed this novel technology with the support of the Defense Advanced Research Project Agency and the university has patented the system's key elements. "When DARPA gave us the assignment of creating a shooter location system using nodes with very limited capabilities, they didn't think we could solve the technical problems," Ledeczi admits. "At first, I didn't think we could do it either, but we figured out how to make it work!"

Retired U.S. Army Lieutenant Colonel Albert Sciarretta, who assesses new military technologies in urban environments for DARPA, is one of the experts who is impressed by the ISIS system: "It's strong points are that it isn't limited to locating shots fired in direct line-of-sight, it can pick up multiple shooters at the same time, and it can identify the caliber and type of weapon that is being fired."

"Because the microphones on the helmet are so close together, the precision is not very high," Ledeczi says. "However, the nodes are continuously exchanging the times and angles of arrival for these acoustic signals, along with their own locations and orientations. When two or more nodes detect the shot, they can provide the bearing with better than one degree accuracy. The range is typically within a few meters even from as far as 300 meters. The more sensors that pick up the shot, the more accurate the localization." The ISIS system communicates its findings with the personal digital assistants that the soldiers carry. The PDAs are loaded with maps or overhead pictures of the area upon which the shooter locations are displayed.

In each package is a wireless network node, of a type dubbed a "smart-dust mote" for its small size and cheapness. There are also four separated microphones, for picking up the acoustic signatures of flying bullets, and a GPS satnav location system. The GPS isn't accurate enough to act as a basis for properly pinning down opposing gunmen, so the Vanderbilt boffins added a crafty radio interferometry enhancement system of their own - apparently of such cunning that it has attracted as much interest as the rest of the system on its own.

The system works by picking up the distinctive conical shockwave trailing behind a passing supersonic bullet - the same phenomenon which produces a sonic boom behind a plane at Mach 1+. This is then related to the muzzle blast from the weapon which fired it, trailing slightly behind (the two noises are heard by people under fire as "crack-thud", or "crack-bang"). A software algorithm in the unit can work out a range and bearing to the enemy weapon's muzzle. A video of the trials can be seen on the Exploration site:

The ISIS shooter system uses the wireless nodes produced by Crossbow Technology Inc. These smart nodes, or motes, form self-organizing wireless-sensor networks and are the realization of the Pentagon's "smart-dust" concept of radically reducing the size and cost of sensor networks for military applications. Current commercial shooter location systems are extremely expensive, with prices ranging from $10,000 to $50,000 per unit. By contrast, an entire node for the ISIS system weighs only slightly more than the four AA batteries that power it and costs about $1,000 to construct using currently available commercial hardware.

The Exploration article is here, and a detailed paper from Ledeczi's team here.

Robocopters and Motes

Crossbow's Motes were featured last month in an article on IEEE Spectrum. The application featured showcases how the Motes can be used when deploying mobile distributed communications networks.

The meter-long helicopters lined up under the fluorescent lab lights at the Berlin Technical University might look like overgrown toys, but they’ve got a little more under the hood. These are flying robots. They take off, land, and scout terrain autonomously and are being wired to deploy ad hoc communications sensor networks. And unlike any other robocopters, they can work together.

Researchers expect they’ll be used to distribute sensors that would help coordinate firefighting efforts or search flood zones, to track or find people and vehicles, or to shoot movies and cover sports events. Hoisting communications gear, they could one day help channel radio, Wi-Fi, or mobile phone traffic where infrastructure has been wiped out by an earthquake or other natural disaster.

Several groups around the world are working on miniaturized robot helicopters with advanced intelligence, notably in California, South Carolina, the Netherlands, South Korea, and the UK. But the Berlin team believes it is the first to write software and build systems that get multiple robot copters to collaborate. The project brings together a half-dozen institutions and companies from across Europe.

The copters’ control systems allow small craft to work together in lifting loads and scouting environments. Coordinated, the copters can lift weights that would normally require larger, exponentially more expensive machines. Estonian robotics engineer Konstantin Kondak, a professor at TU Berlin and one of the project’s leaders, says that having three or four copters in the air, each sharing the load while tethered by a rope to a single object, creates too many contrary forces for a set of human pilots to handle: “If you try to do this flying manually, it is not a stable system. You have to correct at all times; it’s too much.” But autonomous robots, making instant and coordinated adjustments, can do the job, he says.

Each robot must account for the location of the other helicopters, the forces coming from them, and the load on the rope, to jointly lift something. The helicopters’ coordination comes from a system that integrates four software modules for stabilizing the copter: one for navigation, one for exploration, one for obstacle avoidance, and one for processing orientation, horizon, and position.

The robocopters are good for much more than just lugging things around. Project manager Aníbal Ollero, a professor of engineering and automated systems at the University of Seville, in Spain, says that a flexible, easy-to-transport team of choppers makes for more efficient scouting because they automatically divide an area among themselves.

They’re also faster at another important task: deploying distributed communications networks by dropping off sets of tiny sensor nodes. These nodes combine a data processor, a radio, a battery, and—depending on what needs measuring—temperature, light, radiation, location, or chemical sensors. For the autocopter project, off-the-shelf nodes from wireless-sensor firms Crossbow Technology and Ambient Systems were optimized and linked by data-routing experts at universities in Stuttgart, Germany, and Twente, Netherlands. Just a few centimeters across and 7 millimeters thick, the individual nodes transmit over a range of just 25 meters, but as a network they pass radio messages to one another to get to a central unit (or hovering robocopter). Hundreds of thousands of these nodes could be distributed by robot to survey a forest fire or flood zone for rescue efforts, according to the researchers.

Final trials for the project get under way, far from the Berlin winter—this spring in southern Spain, Ollero says. If all goes well, helicopters will deploy a sensor network, track mobile objects and people, follow movement inside and outside of buildings, and capture it all with high-end airborne cameras.

For more information on Crossbow's Mote platforms, visit www.xbow.com.

LiteOS v. 1.0 Released with Support for IRIS Mote Platform

In July of 2007, Crossbow Solutions featured the development of LiteOS by researchers at the University of Illinois at Urbana-Champaign. LiteOS is a UNIX-like operating system that fits on memory-constrained devices like Crossbow's Mote platforms. This operating system allows users to operate wireless sensor networks like operating UNIX.

Version 1.0 of LiteOS has just been released. Now offering complete support for Crossbow's popular IRIS Mote platform, several new features have been implemented. Key Features in Version 1.0 include:

• Windows XP, Windows Vista and Linux Support
• Support for MICAz and IRIS nodes
• Plug-and play routing stack
• Extremely lightweight event logging
• Unix like commands to operate the entire sensor network
• Multi-threading kernel
• Write applications in C
• Native wireless reprogramming
• Built-in hierarchical file system
• Extensive development libraries
• Java tools to display and visualize data
• Online debugging support, including variable watches and unlimited number of breakpoints
• Elastic dynamic memory that has almost zero overhead
• Snapshot a thread state or restore it to a previous state
• Installer for quickly deploying the LiteOS operating system
• Documentation to quickly get started with operating and programming

The goal of LiteOS is to simplify sensor network programming. For more information on this OS, click here.

Smart Attire - Bringing Technology Into The Closet!

What is smart attire? To some it may be clothes that tell you when they are mismatched, or that figure out how to conform to your body type or inform you that these clothing articles do not belong on your body unless you look like Gisele Bundchen. Smart attire like that would soon get rid of the numerous 'What not to wear' blogs and shows we watch, but unfortunately, that is not what we are talking about today. Smart Attire is the next generation of attire that will embed computing and sensing power in clothes, aiding in the development of novel personal monitoring services such as healthcare for the elderly in the comfort of their own home, safety of people working in dangerous situations such as firefighters, construction workers, etc., personal and medical monitoring for joggers, bicyclists, etc. and even entertainment in offering a personal tourist guide system or for social networking. Smart attire can be useful in many ways to help, benefit and entertain those that use them by personally monitoring their environment and bringing technology into their wardrobe.

The feasibility of embedding clothes with computing devices has come about due to the continued revolution of the decreasing sizes of these devices. This allows the device to be unobtrusive to the wearer. Researchers at the University of Illinois, Urbana-Champaign have developed a Smart Jacket. This piece of clothing is built by weaving MICAz Motes into the lining and padding of a winter jacket. As the size of Motes continue to decrease the goal is to embed these devices in shirts, pants, etc. The jacket prototype developed is capable of monitoring the motion and location information of a person remotely by using accelerometers and a GPS sensor with Crossbow's off-the-shelf sensor hardware such as the MTS310 or MTS420 sensor boards. A typical scenario would be of a person wearing the jacket outdoors while it records the motion and location information in the flash memory of the MICAz Motes. Upon coming into range of the base station, the data collected is uploaded to the PC transparently.

The idea of clothing with sensors and computing devices embedded in them is exciting. The idea is not to create a jacket with gizmos like Inspector Gadget, but to embed sensing into these items. With the development of smart attire that not only integrates technology, but is the technology - it is necessary to develop software to interpret the data collected by the clothing. Hence the development of SATIRE - a software architecture for smart attire. As personal instrumentation and monitoring services that collect and archive the physical activities of a user continue to become more popular, a general software architecture is needed to support the different categories of monitoring services. SATIRE is a personal monitoring service that records the owner's activity and location for subsequent automated uploading and archiving.  It allows users to maintain a private searchable record of their daily activities as measured by motion and location sensors; the goal is to perform this data collection in a manner that is transparent to the user when they come into range of the base access Mote at home. To identify the human activity from accelerometric data is difficult; therefore the SATIRE system uses Hidden Markov Models (HMMs) which is still in development. Future work for this project includes the development of security and privacy policies as well as the identification of more sophisticated activities.

A brief video of the prototype can be seen here:

SATIRE implements remote data logging of daily activities and location information, upload protocols for the raw sensory data collected and the use of sophisticated algorithms to interpret the data and make useful deductions to reconstruct activities from the smart attire. The software architecture developed is flexible and modular for future development of smart attire systems that simplify the introduction of new sensors and new algorithms. To get more information on SATIRE visit the project site here where you can download TinyOS for SATIRE as well as view information on installation and usage of this platform. The future is here - bringing technology into the closet!

Now that's a bright idea!

Presenting the new 'Ping-pong' Illumimote, a light sensing module for the Crossbow Mote platform. Wireless sensor networks have permeated the market in many sectors such as environmental monitoring, asset tracking, industrial automation, etc. But, these devices have exciting applications in arts, multimedia and entertainment as well. Limited sensing quality, fidelity and diversity of the sensor modules have limited their expansion into areas like film, video production and lighting control. To support research and development in these areas, high-fidelity light sensing modules in a compact form factor are required.

Enter the Ping-Pong Illumimote! This device achieves performance comparable to a commercial light intensity meter, while conforming to the size and energy constraints imposed by its application in wireless sensor networks. The board was developed to replace the light sensing capabilities on the MTS310 Mote sensor board whose response time and narrower dynamic range in light intensity capture is unsuitable to many certain applications for light measurement such as media production. The Illumimote features significantly improved SNR due to its adoption of high-end photo sensors, amplification and conversion circuits coupled with active noise suppression, application-tuned filter networks, and a noise-attentive manual layout. Unlike the MTS310, the Illumimote can capture RGB color intensity (for color temperature calculation) and incident light angle (which discerns the angle of ray arrival from the strongest source). The prototype was created by the UCLA NESL & the UCLA Hypermedia Studio, a joint effort between the film makers and the engineers, to apply wireless sensor networks to new purposes in art and entertainment.



The order in which an audience views a film’s sequence of events is remarkably different from the order in which they are produced. Shots are filmed in the order that minimizes cost and makes best use of actors, crew, and locations. Footage captured at these different times must appear the same when shown consecutively, or differences must be controllable if they are required for creative purposes. It is important to monitor and replicate the quality of light (illuminance and color) in each shot, so that footage captured at different times or in different locations doesn’t show unexpected differences, which may not be perceived by the human eye but affect the film stock. The Lord of the Rings trilogy, for example, was filmed over a year and a half of production and required that footage be captured for use in three different movies with vastly differing release dates and schedules. Researchers at UCLA have focused on lighting instrumentation as the first component of their Advanced Technology for Cinematography (ATC) because of its vital role in the creative process of filmmaking. ATC is a joint project of UCLA’s Henry Samueli School of Engineering and Applied Science and the School of Theater, Film and Television. The Illumimote is part of their larger vision to increase flexibility and creative control in media production using sensor networks and other emerging technologies. Deploying networks of tiny sensors adds a data acquisition layer to the film production environment that supports on-set decision making, such as the lighting adjustment described above, as well as post-production and asset management.

Initial work prompted the development of the Illumimote and other high-quality sensor platforms that can be deployed atop Mica Motes, the defacto standard for WSN nodes. The Illumimote is designed to have equal or better performance to the class of commercial light intensity and color temperature meters used in the entertainment, film and video production industries. It supports three different light sensing modalities: incident light intensity, color intensities and incident light angle (the angle of ray arrival from the strongest source), and two situational sensing modalities: attitude and temperature. The device demonstrated significantly faster response time (> 6x) and a much wider dynamic range (> 10x) in light intensity measurement as compared with the standard MTS310 Mote sensor boards. The light-angle estimation results were well correlated with an average error of just 2.63°. The assembled Illumimote with a lumisphere appears in the picture above. The role of the lumisphere is to protect the sensors and to integrate incident light from all directions.

The overall system architecture diagram of the Illumimote appears below. There are eight light sensor channels allocated based on the number of detector circuits required to capture the illumination attribute. For example, the color temperature unit requires three channels—one for each of red, green, and blue luminosity. Signals from the eight light acquisition units and four situational units are multiplexed via the channel selection unit and presented to the ADC for conversion into a 10-bit digital signal. This resultant data is conveyed to the networked and embedded nodes (in this case, MICAz motes) via either the I2C data bus or a direct 16550Acompatible UART link that uses line-level (rail-to-rail) output. The operation of the Illumimote’s units may be controlled directly from the Mote via the I2C bus or locally by an onboard Atmel Atmega48 microprocessor. Employing the local processor relieves the network interface (mote) of any realtime constraints associated with frame-rate-accurate sampling. The local processor also exposes interrupt facilities both to and from the host-processor onboard the mote. When operating in this mode, the continuous I2C bus may be severed and reattached dynamically (hardware is bus-state aware) to create two isolated buses—one local to the Illumimote, and one local to the Mote—as needed. In addition to calibration functions, the embedded temperature sensor can wake a sleeping mote in the event of a dangerous thermal condition (risk of meltdown). On the bottom, Illumimote features a connector that is compatible with standard Mote-type sensor nodes (IRIS, MICA2, MICAz, Cricket etc).



Three embedded software components were developed for the experimental wireless sensing system. First, sensor and sensitivity control software was programmed and downloaded to the Illumimote board. The board was then attached to a MicaZ node that has a 7.37MHz 8-bit microprocessor and a 250kbps ZigBee radio. Secondly, the Illumimote driver and light sensing application were programmed at the MicaZ mote using SOS environment. SOS is an OS for Mote-class wireless sensor networks developed by NESL at UCLA. Finally, at the base station laptop, a Java program was used to monitor and log the light measurements, and a visualization interface was used for real-time debugging and analysis. A GUI visualization interface was developed as shown below to display the status of the Illumimote in real time, that was used for testing, experimenting, and performing demonstrations. The interface was implemented in Java and Processing. This GUI made it easy to test and evaluate the Illumimotes visually and is a step towards designing the interface that could be used by a cinematographer in future.



The Illumimote achieves performance comparable to a commercial light meter and color meter (as used by professional cinematographers) over the ranges tested. It consists of incident light intensity, RGB intensity (for color temperature calculation capability), and incident light angle sensors as well as thermal and attitudinal sensors. Researchers at UCLA characterized its performance and verified its capabilities. The project website hosts the technical data and the Illumimote will soon be commercially available from Atla Labs to allow other researchers access to the technology for their own experimentation. Future work includes further enhancements to the general characteristics of the Illumimote (such as dynamic range), estimation of the vertical incident light angle, and further development of the software tools that support and integrate the Illumimote in support of its deployment on actual productions scheduled for the near future.

It's not rocket science...or is it?

Motes have been launched into a new dimension. Researchers at NASA Ames Research Center have taken the capabilities of the MICAz Mote platform and sent them to a new level...literally. Wireless sensor networks and Motes are used to monitor environments or objects to detect changes and provide information or alerts about the current configuration in real-time. This time Crossbow's MICAz Mote platform was used in a rocket engine monitoring system.

Unlike most mechanical systems, rocket engines rarely fail gradually. It's not like having your brakes wear out in your car where you can feel the brake pads getting warped. In a rocket engine, if something fails, it happens quickly making it difficult to determine the root cause or to do anything to avoid the failure. When a rocket engine does malfunction, sensor data provides important clues about the cause. The vehicle health monitoring system relays pressure, temperature, voltage, strain and acceleration data back to the Mission/Launch Control Center. Integrated Vehicle Health Monitoring (IVHM) goes a step further by providing onboard processing capability often detecting engine anomalies earlier and responding faster than a ground-linked system.

The goal of the IVHM project is to replace the standard MIL-STD-1553 databus with an 802.15.4 wireless link between groups of sensors and the Stargate flight-data-recorder. The system was used as a platform to demonstrate intra-vehicle wireless transmission and power management software for long duration missions.

The system used wireless pressure sensors with 1 mounted on the engine chamber and 1 on the fuel tank. There were 4 wireless accelerometers distributed through the vehicle and 2 thermocouples for each fuel tank. All the sensors were connected to a MICAz Mote platform as they were able to provide power/control to the sensors. The sensors transmitted their data to the flight-data-recorder based on Crossbow's Stargate platform over the 802.15.4 link as it interfaced with the MICAz. Before the flight test, the equipment was vibe tested to 6.5g rms for 30 seconds on the X, Y and Z axes to mimic the conditions during the space shuttle launch. A piezoelectric buzzer was attached to the Stargate and each sensor board to easily perform diagnostics at the test range. To optimize power management the MICAz Motes were set to go into low-power mode when the flight-data-recorder was powered off and the Stargate was modified to generate a periodic heartbeat data packet. When the MICAz radios did not see the heartbeat they would go into a low-power watchdog routine.

The IVHM system first flew last September onboard the Garvey Spacecraft Corp's P-8A rocket in Mojave, CA. This engine monitoring system is an advanced concept demonstrator for a wireless 802.15.4 databus where stage-separation makes traditional bus architectures difficult. Motes have been used in many environments for many different monitoring requirements but this deployment certainly reached new heights!
 

Intelligent Transportation Systems

When I think about the future of transportation, the image that pops into my mind is the world of the Jetsons - a world of automation and intelligent transportation systems. A place where machines have the ability to sense and understand their surroundings to allow for a safer more efficient transportation environment. With major innovations slowly taking place all around us, we do not realize how quickly Intelligent Transportation Systems (ITS) are becoming part of our every day life. Implementations such as FastTrack to stop delays at bridge tolls, new technology in vehicles such as the Lexus LS 460 with advanced parking guidance so the car can park itself, Land Rover with adjustable suspension TerrainResponse™, or the Infiniti with wireless connectivity...all these innovations lend themselves to creating more intelligence in the transportation sector.

What is an intelligent transportation system? The term refers to efforts to add information and communications technology to transport infrastructure and vehicles in an effort to manage factors that typically are at odds with each other, such as vehicles, loads, and routes to improve safety and reduce vehicle wear, transportation times and fuel consumption. The last few years have seen the emergence of many new technologies that can potentially have major impacts on Intelligent Transportation Systems. A recent study by the UK Governments Office of Science and Innovation, which examined how future intelligent infrastructure would evolve to support transportation over the next 50 years looked at a range of new technologies, systems and services that may emerge over that period. One key class of technology that was identified as having a significant role in delivering future intelligence to the transport sector were wireless sensor networks (Motes) and in particular the fusion of fixed and mobile networks to help deliver a safe, sustainable and robust future transport system based on the better collection of data, its processing and dissemination and the intelligent use of the data in a fully connected environment. Motes can also be augmented with additional sensors – such as those for detecting light, temperature and acceleration – hence enhancing their features and making their application areas virtually limitless. It is generally perceived that Motes will become the low-cost, ubiquitous sensor of the future, especially once its size shrinks dramatically to merit its name.

Researchers at Newcastle University have been at the forefront of looking into the technology challenges of using these small, low-cost and smart wireless sensors in transport and the application areas where they could be employed. It is clear to the ITS community that the emergence of low cost sensors will open up new paradigms in how we can pervasively collect data from sensors, convey information along fixed and mobile low cost wireless networks (partly or fully formed or ad-hoc) and provide a ‘connected environment’ where individuals, vehicles and infrastructure can co-exist and cooperate, thus delivering more knowledge about the transport environment, the state of the network and who indeed is traveling or wishes to travel. This may offer benefits in terms of real-time management, optimization of transport systems, intelligent design and the use of such systems for innovative road charging and possibly carbon trading schemes as well as through the Cooperative Vehicle and Highway Systems for safety and control applications. See the research and potential use of a Mote based wireless sensor network in the video below:

Initial studies suggest vehicle to vehicle, vehicle to infrastructure, and infrastructure to infrastructure communication and in-vehicle monitoring and environmental monitoring may exist for Motes in the transport domain. Over the last few years, many different versions of 'smartdust devices' have been designed and built by various companies and institutions. Such devices can be used to sense a wide range of environmental parameters as well as vehicle speed, vehicle direction and vehicle presence in the infrastructure. Even though there are several platforms available on the market, Newcastle University chose Crossbow's MICA family motes for the EMMA and TRACKSS projects due to its commercial success in many wireless sensor network applications. Also, Newcastle University has successfully used MICA family motes in its other research projects such as the ASTRA project. Low power wireless communication and low power sensing capabilities are essential for sensor network applications which are supported by Crossbow's Mote family.

The ASTRA project investigated the use of mobile ad-hoc networks, and more specifically, Motes for transport applications. The project examined the current state-of-the-art using MICA motes. A trial using Motes technology was hosted in Newcastle with a pervasive intelligent corridor established by a network of fixed Motes on roads near Newcastle Central Station. Mobile Motes were also placed in several buses. Communication between a static node and a moving node on-board a vehicle was achieved, showing that communication can take place between road side and vehicles using a network of Motes. Evaluation of the system revealed that the main limitation of the technology at the present time is battery life. The experiments have demonstrated that Motes can be used for communication between a fixed infrastructure and a moving vehicle up to a speed of 50 mph. Further testing of the devices at higher speeds (60 and 70 mph) to asses the suitability of smartdust/Motes in applications alongside fast moving roads such as a motorway will be conducted.

The focus of the EU funded TRACKSS project is to research advanced communications concepts, open inter operable and scalable system architectures that allow easy upgrading, advanced sensor infrastructure, dependable software, robust positioning technologies and their integration into intelligent co-operative systems to support a range of core functions in the areas of road and vehicle safety and traffic management and control. The overall aim is to develop new systems for cooperative sensing and predict flows, infrastructure and environmental conditions surrounding traffic, with a view to improving road transport safety and efficiency. To support the demonstration phase of the project, Newcastle University will develop a new technology for ‘smart’ detection on vehicles and infrastructure and a common framework for data collection and access from the entire array of sensors being deployed and tested in the TRACKSS project.

In the case of EMMA, the focus is automobiles and their constituent parts, and the infrastructure they utilize (both physical in the sense of roads and the ICT embedded in them for monitoring and control purposes). If we think more widely at present, most of the world’s computing power is already embedded invisibly into the things around us. The personal computers, music players and other gadgets are just the tip of the iceberg. They probably represent no more than 1% of the computing power we have deployed around us. A typical car today will have at least 20 microprocessors and a host of other electronics contributing to the general functionality required by a modern car as well as the ‘value added services’ which may be the unique selling point of a particular vehicle – whether the application, be: better information on how the vehicle is running; safety applications; or infotainment in the vehicle. The Embedded Middleware in Mobility Applications project (EMMA) application domain of transport will be taken as a pilot example where EMMA will foster cost-efficient ambient intelligence systems with optimal performance, high confidence and faster deployment. The MICAz Mote will be the best suitable platform for the EMMA project since it features sensing and networking capabilities with low power consumption.

The EMMA and TRACKSS projects being pursued by Newcastle University are committed to play a major role in creating new possibilities in the future ITS by using Mote technology. For more information on Crossbow's Mote platforms, contact sales or visit our website.