What if we could eliminate the need for human intervention in the most dangerous and deadly situations? What if the ability to save a life was not done by endangering the life of another? What if the safety of an area could be determined without the need to send someone in to check the premises? These are a few of the reasons why autonomous vehicles and equipment have become such a fascinating area of development in today's world. The technology available and its integration have brought us closer to the reality of such scenarios occurring not only in a threatening situations across the globe, but in our every day lives whether it be for security and surveillance or search and rescue missions.
Researchers at Stanford University have developed STARMAC (Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control). This research shows how using the current technology available, students have created a multi-vehicle test bed used to demonstrate new concepts in multi-agent control on a real-world platform. The team created a small and light, low cost design which has provided numerous opportunities for innovative work. STARMAC consists of up to eight quadrotor vehicles. The system uses Crossbow's Stargate platform for position estimation and control. The Stargate platform was pre-configured with a compact flash 802.11b WiFi card and field testing revealed significant improvements in communication robustness between the base station and vehicle compared with earlier designs.
The video below highlights the development work being done and the ultimate goal of this type of research:
Whether this technology will be used for cinematography allowing aircraft to be flown in more cutting-edge maneuvers to gain better aerial shots than humanly possible, or creating better topographical maps for aerial mapping by flying closer to the ground than is humanly comfortable, or entering devastated areas to assess damage when humanly inaccessible...the list can go on and on. The bottom line is that this type of research and development continues to pave the path to a future where human life could be more protected in situations where it has been endangered in the past.
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!
It is always difficult to determine behavior without observing one's subject in its natural environment. If noticed, the subject may change its behavior or just run away. For example, I pride myself on being able to type at least 65-85 wpm. But of course, as soon as someone walks in and watches me I make mistakes and begin typing like a 5-year old... To observe anything in its natural habitat is one of the hardest challenges to overcome when trying to monitor many species in our world today. However, there is a group of individuals at University of Florida and University of Missouri, Colombia who are using Crossbow's wireless sensor networks products to try and understand the role of free-ranging wildlife in maintaining diversity, tracking invasive species and the spread of emerging diseases by obtaining unobtrusive visual information that prove vital when studying the behaviors and interactions of wildlife species in their environment.
The biological relationship between wildlife and humans has never been
more intertwined. Outbreaks of various infectious wildlife diseases
threaten wildlife populations, human health, food safety and national
economy. Current technologies
available for wildlife studies, such as VHF ratio-telemetry and GPS
tracking, significantly limit our capability in studying the behavior
and interaction of the wildlife species, and the dynamics of the
free-ranging wildlife remains largely unknown. Lack of scientific
knowledge about the behavioral interactions and dynamics of wildlife
systems, our ability to prevent, manage, and control wildlife diseases
is very limited.
DeerNet is a NSF-sponsored project on wireless sensor networking for wildlife
behavior analysis and interaction modeling to better understand the biology and management of the world's ungulates. The overall goal of the research is to develop a long-lived and
unobtrusive wildlife video monitoring system capable of real-time video
streaming with remote control capability. The captured video in real
time will be transmitted over wireless sensor networks to a remote
monitoring center for real-time viewing and camera control. Because
real-time transmission requirements are particularly challenging to
wireless sensor network design, the research is addressing important
issues on energy minimization and performance optimization in video
sensing over mobile wireless sensor networks. By using Crossbow's Stargate platform and MICA Mote platform along with wireless network video in a portable, low-energy solution coupled with optimized transmission protocols and routing schemes
for transferring the video images through sensor node design, access
control, and robust routing protocol this goal is becoming a reality.
In embedded video communication system design for wildlife activity monitoring, the system is expected to operate over an extended period of time, say a few weeks or even months. Therefore, energy minimization of video encoding is very critical. The design of a power-aware embedded system, e.g., DeerNet video sensor, is composed of three parts: the hardware, the underlying system architecture, and the model for distributing applications across the tiers. In general, the design is similar to many distributed systems; each tier is under autonomous control while decisions are made in a distributed manner. Client applications reside at the most powerful tier, and tasks that support those applications are distributed among the various tiers.
The DeerNet video sensor is designed in a strictly hierarchical manner, and the higher tier is more powerful than the lower tier. The two tiers can communicate each other and communication occurs via a local port where the tiers are connected to a common power source. The higher tier is based on the Stargate platform, which has an XScale PXA255 CPU (400 MHz) with 32MB flash memory and 64MB SDRAM along with a daughter board with Ethernet, USB and serial connectors. A Logitech QuickCam Pro 4000 webcam is connected through a USB connection for video capture. The MICA Mote then plays the lower tier rule which works with a powerful Atmega128L micro-controller. The data, measurements, and other user-defined information are stored in a 4-Mbit serial flash (Atmel AT45DB041). In the higher tier Stargate, the linux operating system manages all the tier resources including the power management and the video capture. The video capture mod-ule performances the new P-R-D optimization encoder which compresses the video sequence into a CF card. The power management can put the Stargate into sleep if it is necessary. Once the Stargate is in sleep state, it will wait for a signal to wake up from the Mote at the lower tier. The MICA Mote, at the lower tier, performs tasks such as determining the motion signal that reflects the deer motion state, recording the deer motion state, communicating with the higher tier, and sending wakeup signal to higher tier Stargate.
The DeerNet video sensor is used to track the deer’s action and some situations do not need to be recorded such as sleep, repeating the same action, and at night. On the Stargate, a timer is designed which tracks what time it is and how long it will last. Therefore, once the timer shows night coming, the Stargate is put into sleep. Another signal comes from MICA which determines motion state. The overall objective of this research project is to develop a next-generation wildlife monitoring
technology for behavior analysis, interaction modeling, disease
tracking and control. The research team is working to develop
theories and technologies in efficient wireless networking and video
sensing, to collect video information about their daily activities,
which is the essential information needed in wildlife behavior analysis
and interaction modeling.
DeerNet is an innovative interdisciplinary engineering, computer science and wildlife science project. The video monitoring has the potential to significantly advance this area of science and engineering, and has the broader application to other fields including surveillance, security, process monitoring and other industrial applications.
Crossbow's Mote products have been used for so many diverse and interesting applications. One of the most interesting deployments was done in 2005 using a wireless system to monitor cane toads. You may wonder why anyone would want to monitor toads, so here is some background on this little problem.
The amphibious assault and invasion of the cane toad began in 1935 when the toad (native to South America) was introduced to the sugar cane fields of Queensland in Northern Australia to eat a beetle that was damaging the state's sugar-cane plantations. The experiment was a failure as the cane toads ignored the beetles and began chomping their way through other wildlife from frogs and tadpoles to small lizards. Even worse, the poisonous glands on their backs made them deadly to the crocodiles, mammals, snakes and birds that tried to eat them (a mouthful of toad could be fatal to a dog or cat). Even the tadpoles were poisonous to native animals. The toads adapted quickly to the heat and humidity of tropical Queensland and within decades moved South and West, and finally overran the world famous Kakadu National Park - a World Heritage site. While the region of Darwin was already besieged, millions of other toads were converging on Western Australia. Females could lay up to 35,000 eggs at a time making efforts to head them off difficult. The federal government looked into cane toad control research through its scientific agency, the Commonwealth Scientific and Industrial Research Organization (CSIRO) to find pathogens or other agents to wipe out the pests.
The toads can not be rounded up like cattle, but must be caught one by one - it is only through volunteer efforts that Australians can stop this amphibian invasion. To aid these efforts, a collaboration between the University of New South Wales, Portland State University and National ICT Australia aimed to design a wireless sensor network that could work unattended. In past deployments, researchers from UNSW used PDA class, disconnected devices. The prototype developed in this project provided a cheap and scalable alternative using networked sensor motes. The wireless acoustic sensor network used automatic recognition of animal vocalizations to census the populations of native frogs and the invasive toads. The wireless sensor network was designed to recognize vocalizations of up to 9 frog species found in northern Australia. The system used Crossbow's Stargate platform and MICA2 Mote products. The MICA2 Motes were used to collect acoustic samples and expand the sensor network coverage while the Stargate were used for resource-intensive tasks such as FFTs and machine learning.
The development of the frog vocalization algorithm provided a key feature for the deployment. Acoustic features in the time and frequency domains could be used to distinguish the vocalizations of different amphibians. Frog vocalizations are much simpler than human speech, but they must be recognized in very difficult conditions (wind, rain, insects, and other prevalent noise). The algorithm examines each slice of the spectogram to extract attributes of the individual species being targeted by using pre-set classifiers. The use of this algorithm with the wireless sensor network was to pinpoint the regions inhabited by cane toads and to
track their macro movement directions as the system was deployed in boundary regions. Researchers used a hybrid network of Stargate and MICA2 Motes to make the system cost-effective. The MICA2 Motes were scattered to collect acoustic samples while the resource-rich Stargate platform was used to run the FFT algorithm and other functions required. The MICA2 Mote platform performed preliminary processing on the samples to reduce the transmission size and environmental noise of the data sent to the Stargate. The Stargate would then use these inputs to determine the existence of frogs and pinpoint their location. The macro movements were estimated by comparing the cane-toad existence snap shots at different times by using the location of the sensor device that detected the existence of the species through vocalization. This location information proved to be more than adequate for tracking the cane toad's long-term migration patterns. Although the system would sometimes confuse species, it would never give incorrect results for the cane toad species (the principal species being detected) since it has a very different vocalization compared to the other species found. This type of detection helped volunteers determine which areas they needed to target, and which areas could be left alone allowing for workers to be used more efficiently rather than spending time doing broad sweeps of the area in search of the toad.
Deployments such as these show the vast capabilities and applications into which the Mote platforms may be deployed. Their flexibility and ability to provide a low-cost solution for remote sensing applications presents situations where technology can enable us to understand and monitor our physical environment in greater detail.
Seeing the images on TV yesterday about the tragedy in Minneapolis surrounding the collapse of the I35W Bridge has raised many concerns nationwide regarding the structural integrity of the bridges we drive on each and every day. As a Bay Area company located on a peninsula in a crowded area, many Crossbow employees traverse the Bay Bridge, Golden Gate Bridge, Third Street Bridge, High Street Bridge, etc... to get to/from work. In a recent article published in the San Francisco Chronicle, we have been informed that 800 of the Bay Area's spans are rated the same as the fallen I35W Bridge. Although Caltrans has stated that 'structurally deficient' does not necessarily mean that the road is in danger of collapse, many people are left wondering about the structural integrity of the roadways we drive over on a daily basis. In California, 13% of the 23,000 bridges have been deemed structurally deficient, while 12% of the nation's 600,000 bridges share the same rating. The term can refer to anything from the paint peeling, having too many potholes, to the worst case scenario of failure.
What can be done to detect failure before it happens? In California, this is a serious issue due to the
fault lines that run all over the state. Most bridges must have had a seismic retrofit; however, is there a way to detect the early signs of structural stress? Crossbow has been working to address similar issues with our wireless sensor networks. A deployed network can provide predictive maintenance data to ensure that the correct personnel are notified immediately should any sign of deficiency be found. This technology has been used for landslide monitoring applications and this same technology can be used for monitoring bridges.
Hong Kong has a history of annual landslides. The terrain is steep and hilly with intense seasonal rainfall and very dense development on the hill slopes. Many of these slopes are prone to failure during the heavy rainfall. The ability to monitor the structure, in this case the mountain, provides valuable data to ensure that this natural hazard can be prevented or minimized. In the past 50 years, more than 470 people have been killed by landslides, and on 2 days alone, during severe rainstorms, 148 lives were lost. Hong Kong is one of the most densely populated cities in the world and the Hong Kong government has made a concerted effort to undertake landslide preventative measures whether it is identifying slopes at risk, or carrying out remediation works to monitor their geotechnical parameters including groundwater conditions.
For monitoring applications such as landslides or bridges, wiring is difficult and power supply is usually not available. A wireless and easy deployment solution is required by users. Crossbow's wireless sensor mesh network and its capability to link to the local GSM mobile phone network make it a successful solution for these applications. Crossbow's team in China has been working with the local government and local geotechnical instrumentation specialists to set up the system. In this deployment at a previous landslide site, several holes were drilled into mountain and a number of sensors, such as water level sensors and tilt sensors were placed in each hole to predict the possibility of a landslide. Sensors in each hole sampled at 3-10 minute intervals. Each sensor was interfaced to Crossbow's IRIS Mote platform through the MDA300 data acquisition board. These sensor readings were transmitted via the mesh network to the Stargate base station. The Stargate would then relay the data to a central location through the Hong Kong GSM mobile phone network. The IRIS Motes were powered by regular AA batteries and the Stargate was powered by a rechargeable battery and solar cell. The sampling rate was adjusted depending on the weather conditions to monitor the underground water level and the mountain's movement at each layer.
If a landslide is coming, the water level would typically rise first and the tilt sensors placed at the different depths would be able to report the changing angles in the slope's layers to warn about the impending disaster thus giving authorities time to vacate the area or take preventive measures. The ability to use a wireless sensor network in these scenarios could ensure the safety of many lives and homes. This monitoring solution can be applied to bridges, structures, machinery, etc. Sensors can be embedded at different support joints, truss systems, columns, stress areas, etc. and be interfaced to the Mote platforms to enable the wireless collection and transmission of data. Constant monitoring would definitely give me a little more peace of mind between the scheduled inspections and the potential changes that may occur in these structures.
Surveillance systems have always seemed like something out of a James Bond movie to me - a system that observes events without being intrusive but is able to capture valuable data that allows people to save the world from sure catastrophe (like the time I forgot to open the flue for the fireplace and almost burned smoked out the house)! Surveillance systems are used to monitor or observe the behavior of persons, processes, places, objects, etc. to determine whether they are functioning normally or if there is any deviation from their standard behavior.
It is this concept and its integration with wireless sensor networks that researchers at National Chiao Tung University are addressing to develop their iMouse platform, an integrated mobile surveillance and wireless sensor system. Incorporating the environment-sensing capability of wireless sensor networks into video based surveillance systems provides advanced services at a lower cost than traditional systems. The iMouse's integrated mobile surveillance and easy to deploy wireless sensor system uses static and mobile wireless sensors to detect and then analyze unusual events in the environment. Wireless sensor networks (WSN) provide an inexpensive and convenient way to monitor physical environments. The iMouse system, consists of a large number of inexpensive static sensors and a small
number of more expensive mobile sensors. The former is to monitor the environment, while the latter can move to certain
locations and gather more advanced data. The iMouse system is a mobile, context-aware surveillance system.
The three main components of the iMouse system architecture are (1) the static sensors, (2) the mobile sensors and (3) an external server. The system is set up so that the user could issue commands to the network through the server at which point the static sensors would monitor the environment and report events. When notified of an unusual event or change in behavior, the server notifies the user and dispatches the mobile sensors to move to the emergency sites, collect data and report back to the server.
Each static sensor is equipped with Crossbow's MICAz Motes, available in our WSN-START and WSN-PRO development kits, and a sensor board.The static sensors are placed in known locations which can be established through manual setting, GPS or localization schemes. The static sensors can then determine which sensory input is higher or lower than the predefined threshold. For example, a sensor can interpret a combination of light and temperature readings as a potential fire emergency. To detect an explosion, a sensor can use a combination of temperature and sound readings. Or, for home security, it can use unusual sound or light readings. The mobile sensors consist of Crossbow's Stargate Platform, a Lego car, a MICAz Mote, a webcam and IEEE 802.11 WLAN card to support high-speed, long-distance communications such as transmitting images. These mobile sensors can move to event locations, exchange messages with the other sensors, take snapshots of event scenes and transmit the images. The Stargate controls the movement of the Lego car and the webcam while the MICAz Mote is used to communicate with the static sensor nodes.The external server provides an interface to obtain system status and issue commands.It also maintains the network and interprets the sensor data. The researchers at National Chiao Tung University have developed the dispatch algorithms and user interface to establish the system operation and control flow.
The iMouse system integrates mobile WSN technologies into surveillance technologies to support intelligent mobile surveillance services. This is made possible by the easy to deploy capability of the Mote platform and its flexibility to be integrated into various applications. It is this type of research that is paving the way for future technologies to provide us with more accurate and detailed data about the environments and processes that surround us.
Only in Boston, where the most resilient survive - whether they are running marathons in dangerous weather or having a tea party at sea, the city of Boston has inspired many. At University of Massachusetts, Boston a center has been established to bring together university researchers, business and industry leaders as well as state and federal decision makers to provide an integrated framework for developing environmental sensor networks in coastal areas.
CESN is unique in its development of "smart" underwater networks ranging from ecological to military to recreational. With several deployments at their doorstep in the Boston Harbor, CESN has truly crossed the land-water barrier! Taking advantage of their unique surroundings, CESN has deployments operating in the 900MHz frequency range using Crossbow's MICA2 motes, MDA Mote data acquisition boards coupled with salt marsh moisture sensors, temp, light, sound, humidity, smart cameras, etc...to gather data previously unobtainable in low cost marine data buoys. This testbed of Crossbow Mote based Micro Buoys showcases the ability to integrate sensor modalities and deployment packages into marine environments.
Coastal environmental sensing networks will provide the ability to support environmental decision-making processes - this includes the ability to observe the complex interactions of coastal systems of "hotspots and hot moments" where the nodes can focus on objects and events of interest. Using Crossbow's Stargate platform, researchers have been able to work cooperatively with the USGS to provide visual monitoring of current river stages and dam status. The integration is accomplished using a DSL service with existing USGS phone lines. This allows for high bandwidth data haul to UMASS and the Stargate uplink to receive data from the mesh network environment.CESN is targeting the set-up of a multi-cluster mesh network based on Crossbow's mote and sensor architecture. The possibilities are endless. Where there is a mote...there is a way!
