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.

Heated up about your Energy Bill? Motes to the Rescue!

by Ralph Kling, Chief Architect, Crossbow Technology, Inc.

When I opened up my Gas and Electric bill from our local utility (PG&E here in Northern California) I was shocked: it was over $100 more than I expected. Some further checking confirmed that it was also substantially higher than during the same time last year, by about that amount. So what happened? Sure, energy prices likely have increased since last year and maybe it was a bit colder here the last month. But it still didn’t add up… 

A few years ago I had installed a shiny new programmable digital thermostat to replace an old mechanical gizmo that must have been around since the house was built in the 1950s. And I actually did read the manual (well, some of it anyways) and spent quite a bit of time programming it with different cycles for days and nights and weekends and so on. And, though I was very proud of that accomplishment at the time, the promised energy savings that I had hoped for actually never really materialized. My utility bills stayed pretty much the same before and after the thermostat installation. 

So after receiving the last bill, I investigated the thermostat but it seemed to work just fine and none of the settings had been changed since I had originally made them. After contemplating this for a bit, I had an idea. Since I am working at Crossbow, the leader in Wireless Sensing technologies I have access to the essential tools needed to solve this mystery: I took home a Wireless Sensor Starter Kit which consists of two sensor nodes and a base station. I also added a Stargate Netbridge gateway to record and visualize the data from the sensor nodes without the need to install anything on my PC (or even have it running and consuming energy during the measurements). 

The next day, I installed the “Sensor Network” in my house. It was really simple, just plug the gateway into my home router, place the sensor nodes in the rooms I wanted to monitor and turn them on. All networking and data gathering happen automatically from then on. The sensor nodes are battery powered thus they can be placed pretty much anywhere eliminating the search for outlets. I placed the nodes in the kids’ rooms in the center and back of the house. The nodes have all sorts of sensors including light, humidity, atmospheric pressure etc. but I was particularly interested in the temperature readings. 

The next day, I pulled up the temperature profile gathered so far and I was shocked:

 

The Thermostat was set to 70°F, (about 21°C) during the morning and evening and to 65°F, (18°C) during the rest of the day and at night. The measurements show an average of 24°C during the high and 20°C during the low period, a full 2-3 degrees more than expected. Why were the readings so far off from the preset values at the thermostat? And then it dawned on me: the thermostat was in the living room at the other end of the house. And I remembered that last year in the summer I had closed the heating air vents in that room to prevent the kids’ Lego pieces from falling into the shafts (they are really hard to retrieve from there). Of course I had forgotten about that in the fall when I restarted the heater. 

So the warm air had to make its way through half the house before the living room (and the thermostat) warmed up thus raising the temperature in the other rooms way to high (as well as the heating bill). But this was still a theory that needed to be proven. So I opened up the living room vents all the way, let the sensors collect more data and waited impatiently for the data from the next day. The results were nothing short of astounding:

 

The temperatures in the kids’ rooms now averaged 21°C during the high and 19°C during the low periods, much closer to the desired thermostat settings. Beyond that, the data also shows that one room warms up more poorly than the other (it has more outside walls with poor insulation). Adjusting the vents in those rooms as well could further equalize the temperature readings. 

So, with a very simple setup (it took literally 5 minutes to set up) I was able to gather a lot of valuable data and hopefully significantly reduce my heating bill (we will see next month). And all that without lowering the temperature settings on the thermostat! Beyond that there are lots more insights that can be gathered from the data: The slope between the day and night settings shows how fast the house cools down and how well it is insulated. Other data like the humidity measurements can point to potential problems with mold if the readings are too high. Do your kids always “forget” to turn off the lights – well a plot of the data can very convincingly show how much energy is wasted. 

I am sure there are lots more good ideas – reader’s suggestions are welcome!

Dr. Ralph Kling is currently the Chief Architect of the Wireless Business Unit at Crossbow Technology. Ralph is leading the Wireless engineering team at Crossbow and is responsible for new product strategies, technical directions and Standards activities.

Previously, Ralph was Principal Architect and Director of Sensor Network Operation at Intel Corporate Research. In this capacity, he was responsible for ground-breaking research in the area of Wireless Sensor Network Platforms that resulted in such novel designs as the Intel Mote and Imote2. Before joining Intel Research, Ralph's previous assignments include managing the Itanium® Processor Family microarchitecture/ performance group and the Microprocessor Research Lab (MRL).

Ralph obtained his Master's and Ph.D. degrees from the University of Illinois at Urbana-Champaign. His thesis research focused on Simulated Evolution, a new global optimization method for integrated circuit designs. Prior to coming to the US on a Fulbright scholarship, Ralph studied Electrical Engineering in his hometown of Hanover in Germany. He enjoys skiing in the winter and beaches in the summer.

Motes in Antarctica!

Can you imagine a place where the temperature can get to -82°C? A place without sunlight for half the year. Imagine a frozen desert with no permanent human population - the coldest, driest and windiest continent on earth... It is in this place that research scientists from the Institute of Remote Sensing Applications at the Chinese Academy of Sciences have deployed a wireless sensing system using Crossbow's Mote platforms. Being a resident of sunny California I can barely fathom such an environment. If the temperature drops below 50°F (10°C), I want a cup of hot chocolate and a fire to cuddle in front of. Imagine being in a place where the climate is so harsh - there are no plants or animals. Talk about extreme sensing!

China News reported that the wireless sensor network called the 'Unmanned Wireless Intelligent Snow and Ice Observation System in Extreme Environments' has been successfully set up around the Dome-A area near the South Pole, which is the southernmost point on Earth's surface. Dome-A (Dome Argus) is the highest and possibly coldest place in Antarctica and perhaps the coldest naturally occurring place on Earth. It is the highest ice feature in Antarctica, comprising a dome or eminence of 4.093 m elevation.  The system was co-developed by Crossbow Technology and the Chinese Academy of Science to develop a solution that can consistently work under extreme environmental conditions such as a 4-month polar-night, -82°C temperature lows and an annual average temperature of -55°C. The wireless system deployed by CAS scientists is designed to overcome the low-temperature, high-altitude and soft snow-surface.

The deployed system consists of two base stations and four nodes. Each node is powered by two low-temperature resistant batteries which are expected to last for one year. The communication capability between each node can achieve ranges of up to 1000m. Each node samples environmental data every 15 minutes, including temperature (weather temperature, snow temperature and the snow temperature below 1 meter), humidity, sunlight, and air pressure. The collected data is sent wirelessly to the central base station that collects and sends the data to Beijing every day. Meanwhile, the other remote base station is used to store the data locally to be collected later by an expedition team. The two base stations ensure that no data is lost in the communication.

The Antarctic ice sheet where Dr. Xiao and his scientific expedition team ventured is the highest point on the continent. The group hopes to gather vital information on the environment and observing conditions around Dome-A to determine whether or not it is a viable location to expand the observatories in the region. Dome A claims the best astronomical sky conditions in the world, as it is devoid of clouds and boasting steady air that makes for clear viewing. Imagine...Motes in Antarctica!

RadMote - Mobile Framework for Radiation Monitoring

I don't know how many times I've watched the Simpsons and seen Homer Simpson sitting in front of his Safety Command Console at the Springfield nuclear power plant snoozing and eating donuts, only to scream and panic while pushing buttons at random when a meltdown seems inevitable. He is the safety inspector and is supposed to keep a close watch to ensure that no accidents occur. Yet, so often we see Homer doze off, leave his post unmanned, or even replace himself for the day with a chicken, a manatee, a homeless man or even a brick to cover for him. He is the lowest ranking person at the plant, yet is tasked with one of the most critical jobs. If only it were so simple...

Nuclear energy generates more energy when compared to other available forms such as thermal, kinetic, etc. It is a power source that is seen in many countries around the world, but its correct and safe operation is essential for its surrounding population. Although Homer Simpson's portrayal of nuclear safety at the plant appears trivial, the exact opposite rings true.  Most nations utilizing nuclear power have special institutions overseeing and regulating nuclear safety. Globally, the International Atomic Energy Agency works for the safe and peaceful use of nuclear science, and in the United States, the Nuclear Regulatory Commission ensures the safety of nuclear plants and materials. Due to the extremely serious repercussions that a nuclear accident could provoke, safety measures are especially important in these power plants.

Researchers at Malaga University in Spain have developed a prototype system using Motes to monitor the environmental conditions around and inside a nuclear power plant, with a specific focus on radiation levels. Sensor nodes equipped with radiation sensors are to be deployed in fixed positions throughout the plant. The staff at the plant is to be equipped with mobile devices with higher capabilities such as PDAs to monitor radiation levels and other conditions. The system enables communication between PDAs which form a mobile ad-hoc wireless network and allows workers to monitor remote conditions in the plant. The motes deployed in the environment communicate wirelessly to gather and report information about physical phenomena that can be used to improve safety measures.

To set up the prototype system, researchers used Crossbow's popular MICAz Mote platform along with the MDA300/100 data acquisition boards which would allow the addition of a radiation sensor to the network. The Stargate gateway was used as a sink node to interconnect the Motes using the 802.15.4/ZigBee compliant standard and PDAs using the Wi-Fi (802.11b) standard. The high level of communication was done with the HP iPAQ hw6500 Mobile Messenger which provides GSM connectivity. The sensor nodes were deployed in fixed positions. Environmental sensed data flows through the network to the sink nodes (Stargate gateways). The PDAs get connected to any of the reachable gateways in order to subscribe to the service of receiving gathered data. PDAs are also connected with each other in an ad-hoc manner, this way if it is far from the wireless sensor network; it can ask for the networks conditions from its neighbors. The data is then displayed in a datagrid component on the PDA as the front-end application. Using sophisticated routing algorithms and connection protocols, the system is able to interconnect the wireless sensor network and mobile ad-hoc wireless network to provide the information quickly and easily to the workers at the plant.

The system's basic features are to display data on the PDAs in real-time from environmental conditions, to display the relative position of the sensor nodes either via localization algorithms or noting their fixed position, alarm generation and propagation to detect risk situations, and to interact with the central server to provide data to the PDA and database. The increased safety measures that a wireless sensor network can provide to monitor the environmental conditions in situations where security, reliability and autonomy are paramount would not only aid in detecting accidents but prevent them from ever occurring. Wouldn't Homer be relieved? D'oh!

ResponSphere - Infrastructure for the Unexpected

ALARM-Net: Wireless Sensor Networks for Assisted Living and Residential Monitoring

Thanks to technology and advancements in medicine, people are living longer, and due to a change in the family unit many are living independently. This trend leads towards a growing elder population who have the desire to "age in place." With the high cost of nursing homes and related services, there is a significant need for more efficient and affordable home monitoring solutions. Today there are 35 million people over the age of 65, and by the year 2030 this number will grow to 70 million people based on data collected by the US Census Bureau. Only 4% currently reside somewhere other than their own home, with 90% of Americans, 60 years and older, wanting to remain in their own homes and communities as they age. Of this 90%, it has been determined that 75% of these adults have at least one chronic condition.

Researchers at the University of Virginia, Department of Computer Science have been developing a wireless sensor network for assisted-living and residential monitoring. ALARM-NET provides pervasive and adaptive health-care for continuous monitoring using environmental and wearable sensors. ALARM-NET is a wireless sensor network for smart healthcare. While preserving resident comfort and privacy, the network creates a continuous medical history. Unobtrusive area and environmental sensors combine with wearable interactive devices to evaluate the health of spaces and the people who inhabit them. Authorized care providers may monitor resident health and activity patterns, such as circadian rhythm changes, which may signify changes in healthcare needs. High costs of installation and retrofitting are avoided by using ad hoc, self-managing networks.

The AlarmNet architecture for smart healthcare possesses the essential elements of future medical applications such as integration with existing medical practices and technology, real-time, long-term monitoring, miniature, wearable sensors, and assistance to the elderly and chronic patients. It extends healthcare from the traditional clinic or hospital setting to assisted-living and retirement homes, enabling 'telecare' without the prohibitive costs of retrofitting existing structures. In AlarmNet, the WSN collects data according to a physician's specifications, removing some of the cognitive burden from the patient (who may suffer age-related memory decline) and providing a continuous record to assist diagnosis. Health-related tasks are also made easier for the patient, for example, medication reminders, object location, and emergency communication.The architecture is multi-tiered, with lightweight sensors, mobile components, and more powerful stationary devices. Sensors are heterogeneous, and all integrate into the network. Multiple patients and their resident family members are differentiated for sensing tasks and access privileges.

As researchers at UVA point out, wireless sensor networks are ideally suited as a foundation for smart healthcare in AlarmNet, due to these several inherent qualities:
Portability and unobtrusiveness. Small devices collect data and communicate wirelessly, operating with minimal patient input. They may be carried on the body or deeply embedded in the environment. Unobtrusiveness helps with patient acceptance and minimizes confounding measurement effects. Since monitoring is done in the living space, the patient travels less often, which is safer and more convenient.
Ease of deployment and scalability. Devices can be deployed in potentially large quantities with dramatically less complexity and cost compared to wired networks. Existing structures, particularly dilapidated ones, can be easily augmented with a WSN network whereas wired installations would be expensive and impractical. Devices are placed in the living space and turned on, self-organizing and calibrating automatically.
Real-time and always-on. Physiological and environmental data can be monitored continuously, allowing real-time response by emergency or healthcare workers. The data collected form a health journal, and are valuable for filling in gaps in the traditional patient history. Even though the network as a whole is always-on, individual sensors still must conserve energy through smart power management.
Reconfigurability and self-organization. Since there is no fixed installation, adding and removing sensors instantly reconfigures the network. Doctors may re-target the mission of the network as medical needs change. Sensors self-organize to form routing paths, collaborate on data processing, and establish hierarchies.

Researchers at UVA have adapted a low-cost sensor module that is capable of detecting motion and light intensity changes. The module also has a simple one-button and one-LED user interface for testing and diagnostics. The module is interfaced to a MicaZ wireless sensor node that processes the sensor data and forwards the information to the rest of the wireless network. The picture shows a MicaZ detached from its normal battery-pack and interfaced to the motion sensor (X-10 RF circuits were removed, making this a truly low-power sensor) via the 51-pin connector. A set of such modules (MotionMote) is used to track human presence and to monitor the lighting conditions in various locations of the living space. This activity data is used to maintain location context, and are fed to the back-end software.

AlarmNet has also implemented a wearable body network with MicaZ motes embedded in a jacket, which can record human activities and location using a 2-axis accelerometer and GPS. The components are shown (w/out jacket). The recorded activity data is uploaded subsequently through an access point for archival, from which past human activities and locations can be reconstructed. One mote is placed on the back so that the y-axis (either positive or negative) is always pointing downward. It may also possess GPS capability if the tracking aspect is to be used. The other two motes are placed one on each arm so that when the arm is in a vertical position pointing down, the y-axis (either positive or negative) also points down. A web-server interface has also been implemented to make some SQL requests of a DBMS through a localized user interface which is a user view for this sub-system. This module allows the user to query the data collected and identify various activities that the user performed in the past and his or her location information of the past.

SolarDust, a sensor board for Mica motes shown on the left was also designed to provide the mote's microprocessor with a UART interface to a bluetooth transceiver. This enables the body network to communicate with other commercially available sensor devices, as well as communicate with a resident's cell phone for emergency response! The backbone network connects traditional systems, such as PDAs, PCs, and databases, to the sensor network. It also connects discontiguous sensor nodes by a high-speed relay for efficient routing. The backbone may communicate wirelessly or may overlay onto an existing wired infrastructure. In a previous posting, we discussed the LCD interface board for the MicaZ that is suitable for wearable applications, called the SeeMote. It presents sensor readings, reminders and queries, and can accept rudimentary input from the wearer. It has a five-button interface and a Secure Digital flash memory expansion port.

A wireless sensor network solution like AlarmNet benefits both the healthcare providers and their patients. For the providers, an automatic monitoring system is valuable for many reasons as it frees humans from 24/7 physical monitoring, reducing labor costs and increasing efficiency. The wearable sensor devices can sense even small changes in vital signals that humans might overlook, such as heart rate and blood oxygen levels, boosting accuracy. The quick notification of these changes may save human lives, and the data collected from the wireless sensor network can be stored and integrated into a comprehensive health record of each patient, which helps physicians make more informed diagnoses. Eventually, the analyzing, diagnosis, treatment process may also be semi-automated, so a human physician can be assisted by an electronic physician.

Healthcare patients benefit from improved health as a result of faster diagnosis and treatment of diseases. Other quality-of-life issues, such as privacy, dignity, and convenience, are supported and enhanced by the ability to provide services in an environment more comfortable for the patient. Though 24/7 physical presence of caregivers is reduced, the patient is not isolated from contact with the outside world—an important component of mental health. Family members and the system itself become part of the healthcare team. Finally, memory aids and other patient-assistance services can restore some lost independence, while preserving safety.

This implementation of wireless sensor networks will enable us to create a world that can improve the quality of life for through continuous monitoring of those needing as 'Assisted Living and Residential Monitoring Network.'

AID-N - Advanced Heath and Disaster Aid Network

Johns Hopkins University's Applied Physics Laboratory has developed an advanced high performance communication network to facilitate collaboration among local public health officials, first responders, disease surveillance systems, etc. to respond to public health emergencies. Steady advances in wireless networking, medical sensors, and interoperability software have created exciting possibilities for improving the way we provide emergency care. The Advanced Health and Disaster Aid Network (AID-N), developed at the Johns Hopkins University Applied Physics Laboratory, explores and showcases how these advances in technology can be employed to assist victims and responders in times of emergency.

Researchers have developed a system that facilitates collaborative and time-critical patient care in the emergency response community. During a mass casualty disaster, one of the most urgent problems at the scene is the overwhelming number of patients that must be monitored and tracked by each first responder. The ability to automate these tasks could greatly relieve the workload for each responder, increase the quality and quantity of patient care, and more efficiently deliver patients to the hospital. The AID-N system accomplishes this through the following technologies:

• Wearable sensors to sense and record vital signs into an electronic patient record database. This dramatically improves the current time-consuming process of manually recording vital signs onto paper pre-hospital care reports and then converting the reports into electronic form for the hospitals.
• Pre-hospital patient care software with algorithms to continuously monitor patients’ vital signs and alert the first responders of critical changes.
• A secure web portal that allows authenticated users to collaborate and share real-time patient information.

In order to understand user needs, researchers at JHU-APL collaborated with physicians and nurses at Suburban Hospital Emergency Department (Bethesda, Maryland), physicians and bioinformatics experts at the Johns Hopkins Pediatric Trauma Center (Baltimore, Maryland), and first responders in the local area. As indicated in the figure above, a wearable computer was attached to the patient's wrist and then formed an ad hoc wireless network with the portable tablet PC. A GPS device on the mote provided the patient's geolocation. A pulse oximeter sensor on the patient’s finger measured heart rate (HR) and blood oxygenation level (SpO2) of the patient. The tablet PC was harnessed to the first responder in a weatherproof and anti-glare casing. This packaging allowed it to be used during rainy days or under bright sunlight.

The mote on the patient's wrist regularly transmitted vitals in real-time to the first responder’s tablet device. The transmission used the TinyOS Active Message protocol, which is based on the IEEE 802.15.4 standard. The device used for this application implemented Crossbow's MICAz Mote platform. The system required little setup time. Each medic carried many mote packages and distributed them to the patients. Each mote came with a pre-attached paper triage tag. When the patient was first triaged, the medic would strap the mote wristband on the patient, place the finger sensor on the patient’s finger, and would tear the triage tag to patient’s triage category (red/yellow/green). The mote would automatically start transmitting data to the medic’s tablet PC.

These wearable sensors were integrated with a pre-hospital patient care software package (MICHAELS) created by the OPTIMUS Corporation. MICHAELS ran on the first responder’s tablet PC. MICHAELS was modified to automatically record and analyze the patients’ vital signs and alert the first responder of abnormal changes. It also transmitted the patient's information in real time to a central server that hosted the patient record database. The tablet PC required a network connection to communicate with the central server. In this implementation, researchers took advantage of Verizon’s EVDO coverage in the Washington, D.C., Metropolitan Area. The tablet PCs used EVDO wireless cards to attain network connectivity at high data rates from anywhere in the greater Washington area. The tablet PC regularly transmitted vitals data and alerts for multiple patients to the electronic patient record database via the wireless network. If network connectivity was unavailable, the patient monitor and alert system on the tablet PC continued to operate. When an anomaly was detected, the medic’s software application generated an alert in the user interface, and an LED on the patient’s mote turned on. The medic could then locate the patient by selecting to view a map of the disaster scene marked with the GPS location of each patient. The medic could also select a “sound alert” feature that will sound a buzzer and blink an LED on the mote.

The AID-N system has great potential in improving problems in today’s emergency response system, especially in plans to deal with mass casualty disasters. The team at Johns Hopkin's Applied Physics Lab collaborated extensively with medical professionals in the area to build a prototype that met their greatest needs when designing the system. The key activities which could be improved using AID-N are patient monitoring, record generation and remote record review. AID-N has constructed hardware and software prototypes to address these areas, and shows promise in improving the efficiency of emergency personnel for these activities.