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Wireless sensor Grid - Reports LTER ASM Meeting, Workshop on Sensor Networks; NSF Workshop Report on Environmental Cyberinfrastructure Needs for Distributed Sensor


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Title: Wireless sensor Grid - Reports LTER ASM Meeting, Workshop on Sensor Networks; NSF Workshop Report on Environmental Cyberinfrastructure Needs for Distributed Sensor

Wireless sensor Grid - ReportsLTER ASM Meeting,
Workshop on Sensor Networks NSF Workshop
Report on Environmental Cyberinfrastructure Needs
for Distributed Sensor
  • Wireless Sensor Networks and Their Applications
    in the Environment
  • Thursday 29 January 2004
  • Peter Arzberger

Long Term Ecological Research Network
  • LTER Network is a collaborative effort
  • More than 1100 scientists and students involved
  • Ecological processes over long temporal and broad
    spatial scales.
  • The Network promotes synthesis and comparative
    research across sites and ecosystems and among
    other related national and international research
  • The NSF established the LTER program in 1980 to
  • Support research on long-term ecological
    phenomena in the United States.
  • Provide information for the identification and
    solution of ecological problems
  • The 24 LTER Sites represent diverse ecosystems
    and research emphases
  • The LTER Network Office coordinates
    communication, network publications, and
    research-planning activities.

Long Term Ecological Research Network
1. Andrews LTER (AND)2. Arctic LTER (ARC) 3.
Baltimore Ecosystem Study (BES) 4. Bonanza Creek
LTER (BNZ)  5. Central Arizona - Phoenix
(CAP)  6. Cedar Creek LTER (CDR) 7. Coweeta LTER
(CWT) 8. Harvard Forest (HFR) 9. Hubbard Brook
LTER (HBR)  10.Jornada Basin (JRN) 11.Kellogg
Biological Station (KBS) 12.Konza LTER
(KNZ) 13.Luquillo LTER (LUQ) 14.McMurdo Dry
Valleys (MCM) 15.Niwot Ridge LTER (NWT) 16.North
Temperate Lakes (NTL) 17.Palmer Station
(PAL)  18.Plum Island Ecosystem
(PIE)  19.Sevilleta LTER (SEV) 20.Shortgrass
Steppe (SGS) 21.Virginia Coast Reserve
(VCR) 22.Florida Coastal Everglades
(FCE) 23.Georgia Coastal Ecosystems
(GCE) 24.Santa Barbara Coastal (SBC)
International LTER Network
Launched in 1993 http//www.ilternet.edu
Current Chair, ILTER Hen-Biau King, TFRI
Exploring New Spatial and Temporal Scales in
Ecology Using Wireless Sensor Networks
  • September 2003 All Scientist Meeting of the Long
    Term Ecological Research
  • Participants
  • Tim Kratz, Paul Hanson North Temperate Lakes
  • Stuart Gage Kellogg Biological Field Station
  • Hen-biau King, TERN and Fang-Pang Lin, NCHC
  • John Porter Virginia Coast Region
  • Bill Michener LTER Network Office

Goals of LTER Workshop
  • To identify scientific research opportunities and
    areas enabled and opened up by wireless sensor
  • New Science
  • Cross-Site or Synthetic Research
  • Impact of working at new spatial or temporal
  • To exchange information on capabilities,
    techniques and technologies, and experiences for
    wireless sensor networks
  • Lessons Learned
  • Biggest Challenges
  • Develop products that help achieve the goals above

VCR/LTER Wireless NetJohn Porter, Tom Williams,
Dave Smith
  • The VCR/LTER uses a hybrid network with both
    proprietary 900 MHz and standard WiFi 802.11b 2.4
    GHz wireless Ethernet connections.
  • Areas within line of sight of our two towers are
    tinted in yellow

Source John Porter, Virginia Coast Reserve
Uses of Wireless at VCR/LTER
Integrated camera/ web server/radio/power
  • Real-time Meteorological Tide data
  • Web Cameras (6 currently deployed)
  • Access to networked data resources (e.g., the
    web) in the field

Source John Porter, Virginia Coast Reserve
Uses of Webcams
  • Capture time series
  • Education
  • Non-obtrusive observation
  • Observe rare events

A picture is worth a thousand words
Source John Porter, Virginia Coast Reserve
Wireless Webcam pre Isabel
  • Source John Porter, Virginia Coast Reserve

During Isabel
Source John Porter
Source John Porter, Virginia Coast Reserve
Early Isabel
Source John Porter
Source John Porter, Virginia Coast Reserve
Peak Flooding
Source John Porter, Virginia Coast Reserve
Isabel Winds
Sensors can be where it is too dangerous for
Source John Porter, Virginia Coast Reserve
Some lessons learned
  • Power supplies, not radios, are the most
    difficult component
  • Most consumer-grade DC-DC voltage converters are
    power hogs
  • Use cheap inverters, not expensive ones
  • The cheap ones reset automatically if batteries
    are drawn down, expensive ones dont.
  • Use digital, not analog timers to cut down on
    hours of operation to save power
  • Cheap inverters have poor frequency control

Source John Porter VCR
North Temperate Lakes
Source Paul Hanson, NTL
Freshwater important for human survival habitat
important of other species
North Temperate Lakes University of Wisconsin
Automated Sampling Buoys
Source Paul Hanson, Tim Kratz, NTL
Picture of Lab Freewave
Picture of Buoy Freewave
Continuous monitoring provides opportunity for
pattern discovery And understanding relationships
between variable
Source Paul Hanson, Tim Kratz, NTL
  • Successes (the dedicated network)
  • Building large platforms
  • Establishing bi-directional communication
  • Publishing data to the Web
  • Studying processes contained within an ecosystem
  • Studying processes at few spatio-temporal
  • Current Exploration (the adaptive network)
  • Optimizing wireless networks
  • Auto-configuring ad hoc networks
  • Managing the data load from ad hoc networks
  • Managing power
  • Distributing data to diverse clients
  • Developing network intelligence
  • Studying links across ecosystem boundaries
  • Studying processes at multiple spatio-temporal

Source Paul Hanson, Tim Kratz, NTL
Where to from here?
Better power sources More radio
range Communication among sensors Adaptive
Sampling run by intelligent agents Scalable
Source Paul Hanson, Tim Kratz, NTL
Development of Wireless Instrumentation for
Remote Environmental Acoustic Sensing
Stuart Gage Computational Ecology and
Visualization Laboratory Michigan State University
Source Stuart Gage, KBS
Sound as an Ecological Indicator and a Stressor
As an Ecological Indicator- The integrity and
dynamics of an ecosystem may be correlated to the
complexity of that ecosystems soundscape.
As a Stressor- Organisms require communication
for their survival. Organism population may be
inversely proportional to the degree of acoustic
Source Stuart Gage, KBS
Environmental Acoustic Monitoring Infrastructure
Source Stuart Gage, KBS
EcoGrid Expanding
Source Fang-Pang Lin
HPWRENconnected topologyagendaMay 2002
Santa Margarita Ecological Reserve
Palomar Observatory
Los Coyotes Indian Res.
Pala Indian Res.
Pauma Indian Res.
Rincon Indian Res.
La Jolla Indian Res.
Mesa Grande Indian Res.
San Pasqual Indian Res.
Santa Ysabel Indian Res.
Mt. Laguna Observatory
Scripps Pier
Backbone/relay node Science site Researcher
location Education site Incident mgmt. site
Courtesy Hans-Werner Braun
Mt. Woodson area
to North Peak
to Indian Reservations
to Dan Cayan
Doug Bartlett
Hans-Werner Braun
Courtesy Hans-Werner Braun
HPWREN Applications
  • Ecology
  • Stream Sensors,
  • Behavioral Ecology
  • Oceanography
  • Astronomy
  • Earthquake Engineering
  • Geophysics
  • Crisis Management
  • Distance Education

Multiple applications on same wireless backbone
Instrumenting the Environment
Courtesy NSF Brochure
This model can be replicated and scaled to meet
the challenges of global environmental observing,
analysis, and action
http//www.nsf.gov/pubsys/ods/ getpub.cfm?nsf04549
ParticipantsDeborah Estrin, Bill Michener,Greg
Bonito Total more than 85 AP Community
Masayuki Hirafuji (NARO), Fang-Pang Lin
(NCHC), Shinji Shimojo (Osaka)
http//lternet.edu/ sensor_report/ cyberRforWeb.pd
Overarching View Sensor Networks
  • Revolutionary Tool for Studying the Environment
  • Enables Scientists to Reveal Previously
    Unobservable Phenomena
  • New Cyberinfrastructure Capabilities and
    Infrastructure, Methodology, Middleware, People
  • These will lead to paradigm shift in science

Overarching View Sensor Networks
  • Revolutionary Tool for Studying the Environment
  • Spatially extended networks of multivariable
    intelligent sensor arrays are seen as
    revolutionary tools for studying the environment.
  • Enables Scientists to Reveal Previously
    Unobservable Phenomena
  • The temporally and spatially dense monitoring
    afforded by this technology portends a major
  • New Cyberinfrastructure Capabilities and
    Infrastructure, Methodology, Middleware, People
  • To realize this vision will require above and a
    community of multidisciplinary scientists and
  • To pose newly-enabled scientific questions.

Vision of Environmental Sensor Networks
  • SCALE Pervasive in situ sensing of the broad
    array of environmental and ecological phenomena
    across a wide range of spatial and temporal
  • INFRASTRUCTURE Sensor networks should be robust
    and autonomous, be inexpensive and long-lived,
    have minimal infrastructure requirements, and be
    flexible (expandable and programmable) and easily
    deployed and managed
  • DATA Sensor network data should be maximally
    self-documenting and of known quality, readily
    integrated with other sensor data, and easily

Key Areas of Discussion and Recommendations
  • Sensing Technology
  • Deployed Sensor Arrays
  • Cyberinfrastructure for Sensor Networks
  • Error Resiliency
  • Security
  • Data Management
  • Metadata
  • Analysis and visualization
  • Education
  • Outreach
  • Collaboration and Partnerships

Sensing Technology
  • What are the greatest needs for sensor component
    development for the different communities
  • Recommendations
  • Design more capable sensors
  • Long-term integrity
  • Performance
  • Interactivity
  • Minimal environmental impact
  • Minimal Power consumption

Deployed Sensor Arrays
  • What are the most urgent needs in relation to
    deploying sensor arrays in the field to achieve
    the overarching vision of the report?
  • Recommendations
  • Invest in prototyping and end-to-end testbeds
  • Tested in large-scale natural environments across
    range of applications
  • Validation, comparison with traditional
    monitoring systems
  • Sensor networks include sensors, network
    security, information technologies
  • Automated system layout and coverage estimation
    composition and configuration of synthetic and
    simple sesnors validation and calibration of
    sensor systems

Cyberinfrastructure for Sensor Network
  • Support new genre of cyberinfrastructure research
    and development for scalable sensor arrays
  • Middleware and services (time synchronization,
    localization, in situ calibration, adaptive duty
    cycling, programmable tasking, triggered imagine)
    needed for hyper-scalability, sustainability, and
  • Build the requisite Grid and Web services
  • To convert raw environmental data into
    information and knowledge

Security and Error Resiliency
  • How can we construct flexible, light-weight
    systems that are secure? (e.g. not excessively
    vulnerable to denial of service, inappropriate
  • How do we best characterize and optimize data
    quality from systems composed of large numbers of
    noisy/faulty channels?
  • Recommendations
  • Need solutions for free/open access to most data,
    but protect network, sensors, and sensitive data
  • Need tools for self-diagnosis and self-healing of
    network, and resilient operation when some nodes

Metadata and Data Management
  • What metadata developments are needed to promote
    data discover, access, integration, synthesis?
  • How do we best manage diverse, heterogeneous data
    streams (biological, physical, chemical )?
  • Recommendations
  • Support development of metadata tools (for
    automated metadata and data encoding)
  • Engage community in standardization efforts
  • Community includes sensor developers, users,
    informatics specialists, standards organization
  • Focus on design, development implementation,
    testing, adoption stages

Analysis and Visualization
  • What tools are needed for analyzing and
    visualizing complex, multidisciplinary, spatially
    extended data?
  • Recommendations
  • Algorithm development drawing from statistics,
    machine learning, visualization
  • Work in high-bandwidth sensor streams
  • Tools for mobile devises
  • Tools that integrate high-resolution imagery and
    video, high-fidelity audio and tactile interfaces
    to support virtual and augmented reality

Education and Outreach
  • Train in interdisciplinary setting
  • Outreach to public, decision-makers and resource
    managers needed
  • Information systems needed

Collaborating and Partnering
  • Build Partnerships
  • Universities, research labs, industry, standards
  • Sustain long term deployment
  • To keep facilities alive, evolving, and
  • Need funding for staffing for stewardship and
  • Promote open source solutions and repositories
  • Need incentives for and ease of contributing to
    open source toolsets, models and testbeds
  • Allow for developing reusable system components
    and enhancing interoperability

Examples in Report
  • CUAHSI Consortium of Universities for the
    Advancement of Hydrologic Science, Inc.
  • GEON the Geosciences Network
  • SpecNet Spectral Network
  • Embedded Networked Sensing
  • NSF CLEANER Initiative Collaborative
    Large-scale Engineering Analysis Network for
    Environmental Research
  • Fixed Ocean Observatories (Neptune)
  • NEON National Ecological Observatory Network
  • North Temperate Lakes Monitoring
  • Observing the Acoustic Landscape (KBS)

Role for APAN in Sensor NetworksSome Thoughts
for Discussion
  • Forum for discussion
  • Topics
  • Sensor technology
  • Grid and web services
  • Networking needs
  • Application drivers
  • Communities
  • Grid working group and current/ future partners
    ApGrid, PRAGMA,
  • Natural Resources working group and
    current/future partners
  • Networking working with partners
  • Catalyst for testing sensor nets
  • Place where new technologies are tested in a
    diverse set of environmental conditions

  • Exploring New Spatial and Temporal Scales in
    Ecology Using Wireless Sensor Networks, September
    2003 All Scientist Meeting of the Long Term
    Ecological Research http//atlantic.evsc.virginia.
  • Environmental Cyberinfrastructure Needs for
    Distributed Sensor Networks, D. Estrin, W.
    Michener, G. Bonito, August 2003 NSF Workshop,
  • Scalable Information Networks for the
    Environment, A.Withey, W.Michener,
    P.Tooby,October 2001 NSF Workshop,

  • Center for Embedded Networked Sensing PI Deborah
    Estrin, http//www.cens.ucla.edu/
  • California Institute of Telecommunications and
    Information Technology, http//www.calit2.net

  • High-Performance Wireless Research and Education
    Network (HPWREN), PI. Hans-Werner Braun (NSF),
  • Real-time Observatories, Applications and Data
    management Network (ROADNet), PI John Orcutt
    (NSF) http//roadnet.ucsd.edu/
  • Bringing the information superhighway to the
    dirt road and the high seas
  • National Ecological Observatory Network,
  • Infrastructure for Biology at Regional to
    Continental Scales (IBRCS), A community resource
    by AIBS, http//ibrcs.aibs.org/core/index.asp
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