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

AGENDA

1.Luciad 2.Challenges 3.Use cases

→Smart City

→ Insurance

→Sailing dashboard

4.Conclusion

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LUCIAD Who are we

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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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CONCLUSION

→Very scalable for big data

→Lot’s of configuration and tuning options →Performance

→Exadata optimized:

LuciadRIA LuciadFusion