IN11A-0095
Environmental Sensor Networks: A revolution in Earth System Science?
Environmental Sensor Networks (ESNs) facilitate the study of fundamental processes and the development of hazard response systems. They have evolved from passive logging systems that require manual downloading, into ‘intelligent' sensor networks that comprise a network of automatic sensor nodes and communications systems which actively communicate their data to a Sensor Network Server (SNS) where these data can be integrated with other environmental datasets. At present ESN's can be classified into three types: Large Scale Single Function Networks (which use large single purpose nodes to cover a wide geographical area), Localised Multifunction Sensor Networks (typically monitor a small area in more detail, often with wireless ad-hoc systems), and Biosensor Networks (which use emerging biotechnologies to monitor environmental processes as well as developing proxies for immediate use). In the future, sensor networks will integrate these three elements (Heterogeneous Sensor Networks). We describe the development of a glacial ESN (Glacsweb) to monitor subglacial processes in order to understand glacier response to climate change. We discuss the advantages of the new system, and research highlights, as well as the problems of real world ESNs. We argue that Environmental Sensor Networks will become a standard research tool for future Earth System and Environmental Science. Not only do they provide a ‘virtual' connection with the environment, they allow new field and conceptual approaches to the study of environmental processes to be developed. We suggest that although technological advances have facilitated these changes, it is vital that Earth Systems and Environmental Scientists utilise them. http://www.glacsweb.org
IN11A-0096
Advances in Sensor Webs for NASA Earth Science Missions
The world is slowly evolving into a web of interconnected sensors. Innovations such as camera phones that upload directly to the internet, networked devices with built-in GPS chips, traffic sensors, and the wireless networks that connect these devices are transforming our society. Similar advances are occurring in science sensors at NASA. NASA developed autonomy software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events. This software has also enabled NASA satellites to coordinate with other satellites and ground sensors to form an autonomous sensor web. A vision for NASA sensor webs for Earth science is to enable "on-demand sensing of a broad array of environmental and ecological phenomena across a wide range of spatial and temporal scales, from a heterogeneous suite of sensors both in-situ and in orbit." Several technologies for improved autonomous science and sensor webs are being developed at NASA. Each of these technologies advances the state of the art in sensorwebs in different areas including enabling model interactions with sensorwebs, smart autonomous sensors, and sensorweb communications. Enabling model interactions in sensor webs is focused on the creation and management of new sensor web enabled information products. Specifically, the format of these data products and the sensor webs that use them must be standardized so that sensor web components can more easily communicate with each other. This standardization will allow new components such as models and simulations to be included within sensor webs. Smart sensing implies sophistication in the sensors themselves. The goal of smart sensing is to enable autonomous event detection and reconfiguration. This may include onboard processing, self-healing sensors, and self-identifying sensors. The goal of communication enhancements, especially session layer management, is to support dialog control for autonomous operations involving sensors and data processing and/or modeling entities. These technologies may include antenna for tracking dynamic sensors, autonomous networks and protocols that can distribute data communication tasks among the sensors and control the flow of data, transmission schemes that optimize bandwidth use, and distributed data storage devices. Demonstration of these sensorweb capabilities will enable fast responding science campaigns of both spaceborne and ground assets. These sensor webs will be operated directly by scientists using science goals to control their instruments.
IN11A-0097
Supporting Ecological Research With a Flexible Satellite Sensornet Gateway
Wireless sensor networks are a promising technology for ecological research due to their capability to make continuous and in-situ measurements. However, there are some challenges for the wide adoption of this technology by scientists, who may have various research focuses. First, the observation system needs to be rapidly and easily deployable at different remote locations. Second, the system needs to be flexible enough to meet the requirements of different applications and easily reconfigurable by scientists, who may not always be technology experts. To address these challenges, we designed and implemented a flexible satellite gateway for using sensor networks. Our first prototype is being deployed at Stunt Ranch in the Santa Monica Mountains to support biological research at UCLA. In this joint USC/ISI-UCLA deployment, scientists are interested in a long-term investigation of the influence of the 2006-07 southern California drought conditions on the water relations of important chaparral shrub and tree species that differ in their depth of rooting. Rainfall over this past hydrologic year in southern California has been less than 25% of normal, making it the driest year on record. In addition to core measurements of air temperature, relative humidity, wind speed, solar irradiance, rainfall, and soil moisture, we use constant-heating sap flow sensors to continuously monitor the flow of water through the xylem of replicated stems of four species to compare their access to soil moisture with plant water stress. Our gateway consists of a front-end data acquisition system and a back-end data storage system, connected by a long-haul satellite communication link. At the front-end, all environmental sensors are connected to a Compact RIO, a rugged data acquisition platform developed by National Instruments. Sap flow sensors are deployed in several locations that are 20 to 50 meters away from the Compact RIO. At each plant, a Hobo datalogger is used to collect sap flow sensor readings. A Crossbow mote interfaces with the Hobo datalogger to collect data from it and send the data to the Compact RIO through wireless communication. The Compact RIO relays the sensor data to the back- end system over the satellite link. The back-end system stores the data in a database and provides interfaces for easy data retrieval and system reconfiguration. We have developed data exchange and management protocols for reliable data transfer and storage. We have also developed tools to support remote operation, such as system health monitoring and user reconfiguration. Our design emphasizes a modular software architecture that is flexible, to support various scientific applications. This poster illustrates our system design and describes our first deployment at Stunt Ranch. Stunt Ranch is a 310-acre reserve in the Santa Monica Mountains, located within the Santa Monica Mountains National Recreation Area of the National Park Service. The reserve includes mixed communities of chaparral, live oak woodland, and riparian habitats. Stunt Ranch is managed by UCLA as part of the University of California Natural Reserve System.
IN11A-0098
Environmental sensing systems: some myths and some realities
While it is true that miniaturization and Moore's law has enabled us to combine sensing, computation and wireless communication in integrated devices, and to embed networks of these devices in the physical world. We have found that it takes far more than embeddable devices to achieve the holy grail of "revealing the previously unobservable". Looking back over the past few years we have made our greatest strides using mobility at multiple scales, as well as judicious application of server-side models and processing. We will use examples from soil, river, and coastal water environments, where the respective science objectives include observing respiration and nutrient cycling, contaminant transport and mixing, and algal dynamics. In the context of these applications, this presentation will describe innovations in sensor devices, sampling algorithms, and data management.
IN11A-0099
Low-Cost Pulse-Counting Networked Magnetometer
Building upon our previous successful low-cost (~500 dollar) triaxial magnetometer design, we are developing a networked magnetometer, based on the Speake and Company FGM-3 magnetic field sensor. A cluster of three sensors, each sensitive to magnetic variations as small as 1 nT, generate pulse streams non- linearly proportional to the strength of the surrounding magnetic field, and can measure a dynamic range of ± 50,000 nT. A one second GPS timing pulse provides accurate time and position data, as well as a stable time base from which to calculate sensor frequency. The Microchip PICDEM.net2 Ethernet development board, based on a PIC 18F97J60 8-bit microcontroller, drives pulse counting and network communication. Magnetic data are transmitted over the Internet or local area network to a data-logging server using the UDP protocol. System configuration and status monitoring is performed using a dynamic HTTP web interface. On-board 10-bit analog/digital converters sample ambient temperature in order to calibrate the magnetic readings, which vary due to temperature change. The use of a network-enabled microcontroller-based platform at a time when availablility of networking in remote locations is expanding, provides an unprecedented capability to monitor magnetic or other environmental data.
IN11A-0100
Sensor Management for Applied Research Technologies (SMART) On Demand Modeling (ODM) Project
On-demand data processing and analysis of Earth science observations will facilitate timely decision making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor, data type and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. The authors will present initial results from Sensor Management for Applied Research Technologies (SMART) On Demand Modeling (ODM). This NASA- funded project is developing and demonstrating the readiness of Open Geospatial Consortium Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. First year accomplishments include development of numerous Sensor Observation Services (SOS) and an SOS registry for sensor data discovery and access, as well as a prototype user application, built on these services, for validating cloud types as observed by multiple instruments. The three-year goal of this project is to demonstration how SWE-enabled systems can have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection. http://smart.itsc.uah.edu
IN11A-0101
Usage of Wireless Sensor Networks in a service based spatial data infrastructure for Landslide Monitoring and Early Warning
The joint project Sensor based Landslide Early Warning System (SLEWS) aims at a systematic development of a prototyping alarm- and early warning system for the detection of mass movements by application of an ad hoc wireless sensor network (WSN). Next to the development of suitable sensor setups, sensor fusion and network fusion are applied to enhance data quality and reduce false alarm rates. Of special interest is the data retrieval, processing and visualization in GI-Systems. Therefore a suitable serviced based Spatial Data Infrastructure (SDI) will be developed with respect to existing and upcoming Open Geospatial Consortium (OGC) standards.The application of WSN provides a cheap and easy to set up solution for special monitoring and data gathering in large areas. Measurement data from different low-cost transducers for deformation observation (acceleration, displacement, tilting) is collected by distributed sensor nodes (motes), which interact separately and connect each other in a self-organizing manner. Data are collected and aggregated at the beacon (transmission station) and further operations like data pre-processing and compression can be performed. The WSN concept provides next to energy efficiency, miniaturization, real-time monitoring and remote operation, but also new monitoring strategies like sensor and network fusion. Since not only single sensors can be integrated at single motes either cross-validation or redundant sensor setups are possible to enhance data quality. The planned monitoring and information system will include a mobile infrastructure (information technologies and communication components) as well as methods and models to estimate surface deformation parameters (positioning systems). The measurements result in heterogeneous observation sets that have to be integrated in a common adjustment and filtering approach. Reliable real-time information will be obtained using a range of sensor input and algorithms, from which early warnings and prognosis may be derived. Implementation of sensor algorithms is an important task to form the business logic. This will be represented in self-contained web-based processing services (WPS). In the future different types of sensor networks can communicate via an infrastructure of OGC services using an interoperable way by standardized protocols as the Sensor Markup Language (SensorML) and Observations & Measurements Schema (O&M). Synchronous and asynchronous information services as the Sensor Alert Service (SAS) and the Web Notification Services (WNS) will provide defined users and user groups with time-critical readings from the observation site. Techniques using services for visualizing mapping data (WMS), meta data (CSW), vector (WFS) and raster data (WCS) will range from high detailed expert based output to fuzzy graphical warning elements.The expected results will be an advancement regarding classical alarm and early warning systems as the WSN are free scalable, extensible and easy to install.
IN11A-0102
Turtle Nest Monitoring with Wireless Sensor Networks
We have recently developed a wireless sensor system for environmental monitoring. The system is based upon the sensor platform by Telos, soil moisture sensors from Decagon and our own temperature sensors. The system was deployed at the Jug Bay Wetland Sanctuary, around several nests of Eastern Box Turtles (Terrapene carolina). Conditions in the soil where turtles excavate their nests can have a profound effect on egg survival, hatchling survival and on the sex of hatchling turtles. Turtles prefer nesting in sunny areas where solar radiation provides the heat source that warms the developing embryos. Our system has provided a continuous monitoring of all these parameters over a period of several months in the summer of 2007. The data show several interesting phenomena about temperature gradients in the vicinity of the turtle nests. The deployment also served as a validation of our second generation sensor platform, which performed remarkably well.