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Transcript of Open Source DataTurbine for Tsunami Detection in Indian Ocean and other Environmental Observing...
![Page 1: Open Source DataTurbine for Tsunami Detection in Indian Ocean and other Environmental Observing Systems Sameer Tilak, Tony Fountain, Peter Shin, Brian.](https://reader035.fdocuments.net/reader035/viewer/2022062318/55149c71550346ea6e8b5799/html5/thumbnails/1.jpg)
Open Source DataTurbine for Tsunami Detection in Indian
Ocean and other Environmental Observing
Systems
Sameer Tilak, Tony Fountain, Peter Shin, Brian McMahon, ArunAgarwal, K. V.
Subbarao, Peter Arzberger
![Page 2: Open Source DataTurbine for Tsunami Detection in Indian Ocean and other Environmental Observing Systems Sameer Tilak, Tony Fountain, Peter Shin, Brian.](https://reader035.fdocuments.net/reader035/viewer/2022062318/55149c71550346ea6e8b5799/html5/thumbnails/2.jpg)
Streaming Data Middleware
Common programming layer for real-time systems Enables integration of real-time components Provides abstractions over vendor-specific products Supports in-network processing (buffering, time synch …)
Make data streams first class objects Addressable Efficient operations
Monitoring, QA/QCEvent detectionReplication and subscription Reliable transport
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Open Source DataTurbine Initiativehttp://www.dataturbine.org
• In-network buffered data management and archiving for streaming data
• Scalable support for in-network intelligent routing, data processing, filtering, and topology management
• Robust bridge environment between diverse data sources and distributed data destinations
• Optimized for high-speed streaming data
• All-software solution (Java)
• Used in NSF, NASA, NOAA, DOE projects
• Developed by Creare Inc., http://www.creare.com/
• OPEN SOURCE SOFTWARE - Apache 2.0 License, Jan 07
• NSF support from SDCI program (funding started on Sept 07)
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System Architecture
Open Scalable, Modular architecture based on OGC-SWE standards
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Real-World Deployments
GLEON
CREON
Animal Tracking
Earthquake Engineering
Smart Buildings
NASA etc. etc.
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Open Ocean ForecastOpen Ocean Forecast
Offline
Onlin
e
Modeling and Prediction
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Tsunami Sensors Incois uses data streams
from tide gauges, bottom pressure readers (BPRs), and seismic stations to detect possible tsunami activity
Potential events are checked against precalculated mathematical models to aid in decision making
Integrating all of this data into a single DataTurbine server that can be mirrored and used for event detection
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Seismic Stations National International
Tsunami Buoys National International
Tide Gauges National International
Observation Network in Indian Ocean (Earthquake & Sea Level)
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BhujBhopal
Bokaro
Chennai
DehradunSamla
Dharamshala
DELHI
HYDERABAD
Goa
Pune
Shillong
ThiruvananthapuramMinicoy
Vishakapattinam
DiglipurPort Blair
Campbell Bay
Network of 12 Deep Ocean Assessment and Reporting Systems (DOARS) for detection of Tsunami Waves
Buoy under Lab Test
TB4TB1
TB5
TB6
TB3
TB2TB7
TB8
TB9
TB10TB12
TB11I N D I A
Network of 17 Seismic stations with Central Receiving Stations at IMD Delhi and INCOIS, Hyderabad for monitoring the seismic activity
KANNIYAKUMARI
MAGDALLA
JAIGARH
RAMESHWARAM
PONDICHERRY
NIZAMPATNAM
AERIAL BAYANDR
OTH
CAMPBELL BAY
KAVARATTI (+1)
VERAVAL
ENNORE
EXISTING TIDE GAUGE STATIONSPROPOSED TIDE GAUGE STATIONS
CHANDIPUR
CHENNAI (+1)
MACHALIPATNAM
VISHAKHAPATNAM
PARADIP (+1)
BEYPORE
MINICOY
COCHIN (+1)
TUTICORIN (+1)
NAGAPATNAM (+1)
MANGALORE (+1)
KARWAR
GOA (+1)
MUMBAI (+1)
PORABANDAR
VADINAGAR
OKHA
KANDLA
NANCOWRY
PORT BLAIR (1+2)
RANGAT BAY (2)
GARDEN REACHDIAMOND ARBOUR (+1)HALDIA (+1)SAGAR
KAKINADA
VIZHINJAM
PIPAV
5 Coastal Radars 2 Current Meter Moorings 26 Surface Drifters2 XBT LinesSurface, Met-Ocean observing platformsObservations from other Systems on Internet
Network of 50 Tide Gauges for monitoring the progress of Tsunami Waves
Seismic Network Bottom Pressure Recorders Tide Guages Complementary Observations
Tsunami and Storm Surges Observational Network
Infrastructure Details
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Generation
Propagation
Run up Heights and
Inundation
Seismic Deformation
Bathymetry
Coastal Topography
Tsunami N2 Model
Epicenter (Assumed Epicenters)Depth of Fault Top Edge (0, 20, 40, 60, 80, 100)
Magnitude (5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5)
Fault length (log L = 0.55 M – 2.19) Fault width (log W = 0.31 M – 0.63)
Displacement (log D = 0.64 M – 2.78)Strike angle (Parallel to Trench – Worst Case)
Dip angle (45 deg – Worst Case)Slip angle (90 deg – Worst Case)
Database of
Scenarios
Models Cannot be run during the
event due to large computing time
and non-availability of Fault Parameters in real-time from Seismic Wave Form Data
Hence for Tsunami Forecasting,
database of pre-run scenarios is
essential
Tsunami Modelling for Operational Early WarningTsunami Modelling for Operational Early WarningTsunami Modelling for Operational Early WarningTsunami Modelling for Operational Early Warning
GLOBAL RELATIONS BETWEEN SEISMIC FAULT PARAMETERS ANDMOMENT MAGNITUDE OF EARTHQUAKES – Papazachos B C, etal
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PRIME student at Univ. of Hydebrad
• Set up a DataTurbine server at INCOIS with their tide gauge, bottom pressure reader (BRP) and seismic data streams feeding into it as sources.
• This server is mirrored to a DataTurbine server at the University of Hyderabad, where RDV is used to view the real time sensor data from INCOIS. Goal is to automate the process.
• Test to prove the setup is working.
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AccomplishmentsSet up DataTurbine server at INCOIS and UoH
(mirrored)
Developed parser for various sensors. Real-time data acquisition and processing system was deployed at INCOIS for a variety of sensors including NOAA data.
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15
GLEON 1 San Diego USA
March 2005
GLEON 2 Hsinchu TW
October 2006
GLEON 4Lammi FI
March 2007GLEON 3 Townsville AU
March 2006
People and groups in GLEON
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A Typical GLEON Site Infrastructure
Portable Lake Metabolism BuoyNorth Temperate Lakes LTER
Wisconsin
Instrumented Platforms make high frequency observations of key variables and send data to the field-station
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Status of DataTurbine GLEON Deployments
Lake Sunapee, NHLake Erken, Sweden Northern Temperate Lake, Wi
Cellular Link Freeway Serial Radio Link
Thanks to GLEON community!
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Coral Reef Environmental Observatory Network (CREON)
UCSB NOAATaiwanGBR
Source: Stuart Kininmonth, AIMS
Source : Fang-Pang Lin, NCHC
http://www.coralreefeon.org/
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Network of Underwater Cameras at Kenting
Collaboration with NCHC, Thanks to Fang-Pang Lin, Ebbe, and other staff members
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Integration with Tile Display Wall (TDW)
TDW at UCSD showing real-time streaming data from underwater cameras at Kenting
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Acknowledgements INCOIS staff members, India
University of Hyderabad, India
• Open Source DataTurbine Initiative Team and community
• Funding Agencies• NSF• Gordon and Betty Moore Foundation
• GLEON, CREON, communities
• Corporate Partners