smart 3d cities and situational awareness applications...
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L U C I A D P R E S E N TAT I O N
S M A R T 3 D C I T I E S A N D S I T U AT I O N A L AWA R E N E S SA P P L I C AT I O N S W I T H O R A C L E E X A D ATA A N D J E T
Luciad Smart 3D Cities and Situational Awareness Applications OVERVIEW
• Luciad provides software solutions for Geospatial Situational Awareness and Visual Analytics.
• Industry: Aviation, Defense, Maritime, Public Safety & Homeland Security, Utilities & Logistics and civil domains.
CHALLENGES / OPPORTUNITIES • Highly interactive applications with 200M+ point data sets • Database generated heat maps with sub-second
response times • Fluent access to arbitrary sized 3D city databases • Thin client • Easily scalable SOLUTIONS • LuciadRIA V2016.1, LuciadFusion 2016.1 • Oracle Exadata X6-2 • Oracle Database 12.1 • Oracle Database, Real Application Clusters • Oracle Database, Spatial and Graph Option • Oracle Database, In-Memory Option • Oracle Database, Partitioning Option • Oracle Linux
RESULTS • Dataset of 175M points • 20x faster response times for spatial queries • sub-second response times for most queries. • Sustained throughput of 100.000+ records per second
for 20x the number of users.
• Database with 565,000 buildings • 25x more requests per second for 3D City DB
• Highly scalable: Double the resource, double the
performance without effort
• Exadata optimized certification
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LUCIAD →SDK’s →Interactive applications →(Geo)spatial Situational Awareness →Visual Analytics →Domains:
Defense Security Aviation Public Sector
→www.luciad.com →dev.luciad.com →3d.luciad.com
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CHALLENGES Key challenges for situational awareness with big data
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CHALLENGES
→Data gets bigger
→Analysis needs to be faster
→Client gets thinner
→End-user is more demanding
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USE CASES Examples of challenging applications tackled with Luciad and Oracle
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USE CASES
Smart City Insurance Sailing dashboard
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SMART CITY →CityGML of Berlin
565,000 buildings →3DCityDB
Oracle Spatial DB →Tiled queries →Interactive access on thin client →Test scalability and response time
Exadata vs traditional installation Linear scaling
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INSURANCE USE CASE →175,000,000 Insured assets →Heat Maps
Complex,process intensive →Interactive based on filters from the client →Download 200K points per second
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INSURANCE USE CASE →Grid-query →Client requests and receives tiled images
Caching →Scales very well
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2 2 1 SELECT pixel_x, pixel_y, count(*) density FROM ( SELECT FLOOR((x + 75) / 3 * 64) pixel_x, FLOOR((y - 40) / 3 * 64) pixel_y FROM INSURED_ASSETS WHERE x >= -75 AND x < -72 AND y >= 40 AND y < 43 ) GROUP BY pixel_x, pixel_y
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SAILING DASHBOARD
→Rich HTML5 application Luciad WebGL components Local interactive analysis JET libraries integration
→Cloud based analysis on historical data
→Use-case of the future!
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CONCLUSION The good, the bad and the performance
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CONCLUSION
→Data gets bigger Oracle Spatial DB Oracle Exadata
→Analysis needs to be faster Oracle Spatial DB Oracle Exadata
→Client gets thinner LuciadRIA
→End-user is more demanding LuciadRIA
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