Diapositiva 1

Towards policies for data insertion in dynamic data driven application systems: a case study sudden changes in wildland fireUniversitat Autnoma de Barcelona, EspaaRoque Rodrguez, Ana Corts and Toms Margalef

1

AgendaProblem statementOverviewSAPIFErt - Real time data injectionPolicy for data injectionExperimentsConclusions and Future Work2Problem statementForest fires are one of the most worrisome natural disasters, destroying thousands of acres of forests and nearby urban zones, affecting plant, animal and human life.

The forest fires are a fact of nature, and have been serving as means of self-regulation of forests. However, these phenomena have become more frequent during the last years.

32 PUNTO) FOREST FIRES ARE A FACT OF NATURE, AND IT HAS BEEN SERVING AS MEAN OF.

Y PHENOMENA DEBERIA SER PLURAL (THESE PHENOMENAS ARE BEING) O TODO SINGULAR THIS PHENOMENA IS BEING MORE.Problem statement Fire propagation simulators are a very useful tool to help combat forest fires.Those are based on mathematical and physic models, and with their help, we can mitigate the damage, optimize resources and save lives. But

4THESE FIRES. TOOLS ARE THE . (TOOLS, PLURAL SI DESPUES DECIS SIMULATORS).THESE SIMULATORS ARE BASEDImprove prediction results.Research Goals

Reduce execution time.Inject data at execution time.Applying Dynamic Data Driven Applications Systems conceptit is a paradigm whereby application/simulations and measurements become a symbiotic feedback control system. DDDAS entails the ability to dynamically incorporate additional data into an executing application, and in reverse the ability of an application to dynamically steer the measurement processDra. Frederica Darema5

Calibration Stage Prediction StageTwo Stages Propagation Prediction

SimuladorParameters

Simulador

Hypothesis: the environmental conditions are similar in the two stages6Tiempo de calibracion

EN LA PREGUNTA CAN WE USE. YO PONDRIA SIN THE: CAN WE USE CONVENTIONAL SUMULATORS.Calibration Stage: SAPIFE CrossGenetic AlgorithmSelectionMutationIndividual BBcp1Bcp2Individual AAcp1Acp2Child AB1Acp1Bcp2Child AB2Bcp1Acp2

Population

New populationElitismGenerationscenarios=individuals

Best PopulationS2F2MBestProbabilityFireSimFireSimFireSimFireSim7

Method Evaluations

Prescribed FiresSynthetic Fires

Error Ratio

Real Fires

California Fires

Catalunya Fires

Greece Fires

8Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

Fire Spread Evolution4 to 6 minFire Spread Evolution6 to 8 min

Fire Evolution Analysis Hypothesis: the environmental conditions are similar in the two stages

9Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

Fire Spread Evolution10 to 12 minFire Spread Evolution12 to 14 min

Fire Evolution Analysis Hypothesis: the environmental conditions are similar in the two stages

10Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

SAPIFE

Data Collection & Processing System

Urgent HPC

Weather StationWeather BalloonGenetic Algorithm StatisticalMethod

SimulatorSimulatorSatellite Image Photo Image

Dynamically Injected DataFire SimulatedTraining DataData baseInput ParametersData StreamFire ManagerReal time11Calibration Stage: SAPIFErt CrossGenetic AlgorithmSelectionMutationIndividual BBcp1Bcp2Individual AAcp1Acp2Child AB1Acp1Bcp2Child AB2Bcp1Acp2

Population

New populationElitismGenerationscenarios=individuals

Best PopulationS2F2MProbabilityFireSimFireSimFireSimFireSim120 360 40 45 50 WindDir bounded range0 360 WindDir valid range

Best PopulationData injection

Weather StationWeather Balloon 7 0.99 0.00 8.00 78.00 0.00 21.00 7 0.99 0.00 4.00 37.00 0.00 21.00 7 0.99 0.00 3.00 45.00 0.00 21.00 7 0.99 0.00 7.00 34.00 0.00 21.00 7 0.99 0.00 5.00 40.00 0.00 21.00 7 0.99 0.00 9.00 38.00 0.00 21.00 7 0.99 0.00 5.00 42.00 0.00 21.00 7 0.99 0.00 4.50 37.00 0.00 21.00 7 0.99 0.00 6.50 39.00 0.00 21.00 7 0.99 0.00 5.00 25.00 0.00 21.00WindDir 45WindSpeed 9 0mph 20mph WindSpeed valid range0mph 20mph7 9 11 WindSpeed bounded range13Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

X 20X22X21GASMapPrediction Data Injection

MapMapMap3Wind Speed10GASP

X1X2X3X4X5X6X7X8X9X10X 11X 12X13X14X15X16X17X18X 19X23X24X25

GASPrediction P

14

Policy for Data Injection Change Factor of a given Variable (CFV )timespeedCalibration StageXlXlccXlppCFV

timespeedPrediction StageChanges in the behavior of this variable is negligibletimespeedPrediction Stage15Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

X 20X22X21GASMapPrediction CFV Estimation

MapMapMap3Wind Speed10GASP

X1X2X3X4X5X6X7X8X9X10X 11X 12X13X14X15X16X17X18X 19X23X24X25

GASPrediction P

16Freeway Complex Fire

Injection map every 60 min Injection wind data every 5 min17Results

CFV_threshold= 2.5

18Conclusions We observed that data injection in real time can improve the prediction results significantly when conditions are dynamic and changes are sudden.

We gain time and flexibility for changing situations.

We also conclude that the data acquisition frequency directly aects the prediction results, as well as the precision on the detection of sudden changes.

19Traducir al espaolSAPIFEEEEEEEEE Y NO SAFIPE!!!

BE ABLE TO PROVIDE. Me parece que es asi y no of privinding

Y despues de la coma, , SAPIFE3 has shown to be able. un but o algun conector????FeedbackOutputDrive Process+ or frequency+ or - precision

Input ParametersMonitoring

Weather StationsRemote SensingMeasurementsSAPIFErttimespeedtimespeedApplying DDDAS Concept20Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

Thank You!!!

21Falta traducir!

Results

Injection map every 30 min Injection wind data every 5 minWind samples data for CFV estimation is 322

Policies for Data Injection

corr=0.97CFV_threshold=1.523Ventajas y desventajas (poner mas oscuro, esta en gris y casi no se nota)

We have another method of prediction: The statistical one.What does it do? Well, it Runs a whole range of values, and does the combinatory analysis of every each of them, compares them to the real fire and selects the most probable map of the fire.

What is the advantage? As it runs the full scope of possible values, it reacts very well when conditions change.

And what is the problem with this?As the statistical method needs to run the combinatory analysis of every set of input data, the number of simulations to do is ENORMOUS. And this is slow. Very slow.

PROS Y CONS NO SE VEN!

PROS y CONS: creo que faltaria poner el sujeto en estas oraciones, viste que en ingles son ms exigentes en esto. Yo, ante la duda de cuando estara bien poner el sujeto y cuando no, optara por ponerlo siempre, ya que sabs que mal no va a estar....

it covers all possible parameter value combinations (exhaustive method).It is good for changing....CONSIt requires....It needs.... (spending more time)

Results

Injection map every 30 min Injection wind data every 5 minWind samples data for CFV estimation is 3

CFV_threshold= 3.0

24Results

Injection map every 30 min Injection wind data every 5 minWind samples data for CFV estimation is 3

CFV_threshold= 3.0

25Results

Injection map every 60 min Injection wind data every 5 minWind samples data for CFV estimation is 626Decision Support System