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Metrics of a System for Disaster Relief
Metrics of a System for Disaster Relief

Metrics of a System for Disaster Relief - PowerPoint Presentation

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Metrics of a System for Disaster Relief - Description

Lynne Grewe California State University East Bay lynnegrewecsueastbayedu Presentation by Funda Erdin Disaster Recovery Issues Disaster Incident DefinitionProtocol Categories of Data representing Incident ID: 540199 Download Presentation

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incident data visualization capture data incident capture visualization personnel metrics biotarget direct identity location milliseconds jms chars amp search

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Presentation on theme: "Metrics of a System for Disaster Relief"— Presentation transcript

Slide1

Metrics of a System for Disaster Relief

Lynne GreweCalifornia State University East Baylynne.grewe@csueastbay.eduPresentation by Funda ErdinSlide2

Disaster RecoverySlide3

Issues

Disaster Incident Definition/ProtocolCategories of Data representing IncidentMethods of Data CaptureData and Uncertainty Computer RepresentationFusion Processes to Reduce Data Size.Storage and Data Distribution NeedsPersonnel Roles and related Security Needs

Data Presentation

Communication

Needs and Performance

Administration and Incident Control ToolsSlide4

Previous Work

Currently, mostly disaster relief is performed without any computer management tools as shown in imagesProtocols (NIMS/ICS)Describe human interactions … not as quantifiable as neededSpecialized ComponentsSome previous work concentrates on very specific issues (e.g. ambulance routing)

C3 related

work

Command, Control, Communications – C3, US military related work, goals are not disaster reliefSlide5
Slide6

Our System: DiRecT(Disaster Recovery Tool)

VisualizationUncertainty VisualizationDistributed InfrastructureCommunications Application of Mobile AgentsProtocol StructureClient ControlSlide7

DiRecT

OverviewSlide8

DiRecT Server

EJB components for persistence and business logic JMS and Mobile agents for instant-memoing JMS for incident updates Oracle database for persistenceSlide9

DiRecT Field & Incident Command

Clientscreate a new incidentmanage multiple incidentsrequest resources, personnel and equipment for a given incident

assignment of personnelSlide10

DiRecT Admin Client

Activation / Deactivation of incidentsCreation of new personnel, equipment and resources.Assigning personnel to incidentsFulfilling resource requestsPurging incidents from the databaseSlide11

Incident

Tracking of victims, personnelHazardous materialsNatural hazards responseSearch-and-rescue missionsFire controlAir, rail, ground, and water transportation accidentsIncidents with multiple casualties…and others.Planned human events, e.g., large crowd gatherings, concerts, etc.Slide12

Incident CreationSlide13

Beginning of IncidentSlide14

Incident Data

Many kinds of data possible, different operating units (firefighters, police, etc) may want different kinds of data.DiRecT’s Data CategoriesBioTargets (victims)Search AreasEquipmentPersonnel

Hazards

ImagerySlide15

Data and Uncertainty Metric Goals

Quickly enter in dataCapture the essence of the underlying dataAllow for longer more narrative (open) forms of data capture optionally.Have quantitative metrics when possible to make visualization easier and storage efficient.Have metrics easily understood by all types of possible users.Have metrics be intuitive when possible.Slide16

BioTarget Data Metrics

Capture common dataQuantizeCapture uncertainties.Data measured: IdentityLocationHealth

SafetySlide17

Biotarget Data Capture

IdentitySlide18

Biotarget Data Capture

LocationSlide19

Biotarget Data Capture

HealthSlide20

Biotarget Data Capture

Safety / StatusSlide21

Search Area Metrics

Represent areas of search (or past search)Typical geometries – rectangular, circularCapture uncertainties.Data measured: Geometry size, shape, location, searching or searchedSlide22

Search Area Data Capture

Give identity through nameLabel as searching or searchedGive geometry and associated certainty of thisSlide23

Equipment Data Metrics

Represents various kinds of equipment and resources in the fieldCould be lots of different kinds of equipmentData measured: Identity, type, locationSlide24

Equipment Data Capture

Give identity through nameLabel Category or type in your own if not listedLocation same as biotarget data captureRight screen shows listing of current equipment in Incident.Slide25

Personnel Data Metrics

Represents various personnel in the field (firefighters, police, etc).Data measured: Identity, personnel type, locationSlide26

Personnel Data Capture

Give identity through nameType indicates unit personnel belongs to.Location same as BioTarget data captureSlide27

Hazard Data Metrics

Represents hazards in the scene.Many kinds (fire, water, wind, etc).Data measured: Identity, locationSlide28

Hazard Data Capture

Give identity through name, type, optional description, condition and certaintyCondition – scale of 0 to 100 indicating level of containment & severity. 0 is contained/low level problem. 100 is not contained/criticalSlide29

Imagery Data Metrics

Represents raw imagery type data collected about incident.Many kinds possible – photographic imagery, infra-red, maps, etc.Data is ALREADY quantifiedProblem here is to register the data against our Incident Visualization Grid so it can be fused.Data measured: File upload, User entered Registration pointsSlide30

Imagery Data Capture

Name of image layerActivate layer or notData fileRegistration informationSpecified by user by clicking with mouse on upper-left and lower-left location ofimage boundaries.Opacity control

Optional description

Rotation controlSlide31

DiRecT Visualization

DiRecT take these data and certainty metrics and performs visualizationSlide32

Some Visualization Cues

Opaqueness-TransparencyIcons/GlyphsColor (pseudo-coloring or color representation)Brightness/IntensityTextureAtmospheric EffectsAdding/Altering GeometryLayers

Focus

Pop-up textual information

Animation

Morphing

Time Fading

Sounds (volume, key, duration, fade)Slide33

Biotarget Visualization

IconicColorTransparencyLocationBloom

indicates

BioTarget

idenity

type

Indicates combined Health

and Safety w/Certainty

indicates identity and presence certainty

indicates location information

indicates location certaintySlide34

Biotarget Color

C

H

C

S

ALTERED COLOR

ICON

100

100

Unchanged – RED

50

100

Unchanged – RED

75

75

Some Uncertainty – ORANGE

50

50

Significant Uncertainty – ORANGE YELLOW

0

0

Very Much Uncertain - YELLOW

Color of Icon = F(

Health,Saftey

, Certainty)

Red = Max(

ColorSafetyR

,

ColorHealthR

)

Green =Min(

ColorSafetyG,ColorHealthG

)

This visualization is intuitive.

Red –alarm/high concern. Green – safe Yellow –caution/uncertain.Slide35

Example

Visualiztion

Image, map,

BioTargets

, Search Areas, Equipment, Hazard and Personnel

.Slide36

Search Area Visualization

Colorsearching searchedShapeTransparencyLocationSlide37

Equipment Visualization

Iconic &Color Medical Hazard WaterTransparencyLocation&BloomSlide38

Personnel Visualization

IconicTransparencyLocation&BloomSlide39

Hazard Visualization

Iconic &Color Water Explosion ChemicalTransparencyLocation&BloomSlide40

Visualization Control

Control clutterBetter DecisionsView only desired dataSlide41

ContrastSlide42

Biotarget

Before

Highlight

<= 60% healthSlide43

AreaSlide44

Filter

BeforeCertainty > 60%Slide45

Infometrics – basic statistics about Incident.

CountSearch

Search and highlight for biotargets Health <=60%Slide46

Count

Count in Area BioTargetsSlide47

DiRecT Infrastructure Issues

Remote method invocations Transparent fail-over Back-end integrationTransactions Clustering Dynamic redeployment Clean shutdown

Logging and auditing

Threading

Object life cycle

Resource pooling

Security

Caching

CommunicationsSlide48

DiRecT ServerSlide49

DiRecT Communications

We can’t in the time allowed look at all the components of InfrastructureLook at communications modulePerforms a kind of “Instant- Memoing” for asynchronous communications in the field.2 implementations

Will look at Performance metricsSlide50

Instant MemoingSlide51

Implementation 1 : Messaging via JMSSlide52

Implementation 2: Mobile Agents – using AgletsSlide53

Aglets over JMS

Aglets can very easily and efficiently send private messages, while with JMS it is not so simple.Aglets is explicitly asynchronous while JMS can be made asynchronous through durable subscriptionsEach mobile agent can carry different a encoding/decoding algorithm.Agents can be controlled and can react dynamically to unfavorable situations on a host JMS reliable, mature technology.Slide54

Size of Message

Avg Time in Milliseconds for 10 messages

Aglets

(Milliseconds)

15KB class file + 16 chars data

51.3

JMS

(Milliseconds)

16 chars data

49.7

Aglets

(Milliseconds)

15KB class file + 32 chars data

54.1

JMS

(Milliseconds)

32 chars data

49.9

Aglets

(Milliseconds)

15KB class file + 64 chars data

56.7

JMS

(Milliseconds)

64 chars data

50.3

Aglets

(Milliseconds)

15KB class file + 564 chars data

91.2

JMS

(Milliseconds)

564 chars data

52.8Slide55

Performance Aglets over JMS

JMS Superior, especially as message size grows.Aglets have some other possible advantages.Slide56

Future Work

TestingSystem IntegrationPDA, other devicesPredictive & Planning (AI)Other forms of MediaUser-specified/assigned visualization queues