Transcript UrbanFlood

UrbanFlood
The Common Information Space:
A Framework for Early Warning
Systems
Bartosz Baliś, Tomasz Bartyński, Marian Bubak,
Grzegorz Dyk, Tomasz Gubała, Marek Kasztelnik
Motivation: Early Warning Systems
against natural disasters
Complex distributed systems
 Mission and time-critical
 Involve resource-intensive computations and data
analysis
 Require compositions of resources into complex
scenarios

◦ Sensors monitoring objects and natural phenomena
◦ Apps for data analysis & simulation
◦ ICT infrastructure (hardware + software)
Example: Urban area flood
simulation
Goals

Develop a framework facilitating
development, deployment and execution
of EWSs: the Common Information Space

EWS development
◦ EWS reference model
◦ EWS development framework

EWS deployment
◦ EWS blueprints
◦ EWS-factory-as-a-service

EWS execution
◦ CIS runtime services for resource allocation, selfmonitoring, self-healing, mission-critical operation, and
urgent computing
CIS Architecture and EWS
reference model
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CIS as a system factory
System instance
System factory
invoke
System
blueprint
configurations
Service factory
Service factory
Service
Service
configurations
customize
Virtual appliance store
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Case study: Flood Early Warning
System
Protection of urban areas against floods due to
dike failures
 Real-time monitoring of embankments using
wireless sensors
 A casade of models for:

◦ Anomaly detection
◦ Risk assessment
◦ Impact prediction
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Dike anomaly detection

Anomaly detection using neural cloud
classification
Dike breach risk computation
Distribution of probability of dike
breach is calculated
 Depending on the current water level

Flood simulation
Life Safety Model

Loss of life estimate
due to flood
Initial state of the world 
Post-event summary 
(red color = deceased)
Virtual Dike
Computer model of a dike
 Simulation of dike behaviour
 Useful for „what-if” experiments
 Also for testing the real EWS
(„emergency drill”)

Flood Early Warning System
workflow
Dike
Data
flow
Control
flow
Sensor
Cabinet
Alternate path
Virtual
Dike
AnySense
Service
AI Anomaly
Detection
action
Reliability
Analysis
Abnormal?
High risk?
Life Safety
Simulation
Flood
Simulation
High
impact?
Flood EWS: implementation
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Example: Flood Simulation Part
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Conclusion
CIS contributes conceptually and technologically
in the following areas:
 CIS as a factory for Early Warning Systems
◦ Proven by the implementation of the Flood EWS

CIS as a geo-ICT technology for spatial
data processing services
◦ CIS adopts guidelines of the INSPIRE directive and
leverages OGC standards for service interfaces

CIS as a runtime infrastructure for
resource-intensive mission-critical systems
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urbanflood.cyfronet.pl
dice.cyfronet.pl/cis
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