Investigating the Benefits of Information Management Systems for - - PowerPoint PPT Presentation

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Investigating the Benefits of Information Management Systems for - - PowerPoint PPT Presentation

Jun 08, 2023 41 likes •484 views

RiskAware. capability through technology Investigating the Benefits of Information Management Systems for Hazard Management Ian Griffiths, Martyn Bull, Ian Bush, Luke Carrivick, Richard Jones and Matthew Burns Aims of CBRN IM To seamlessly

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  • RiskAware. capability through technology

Investigating the Benefits of Information Management Systems for Hazard Management

Ian Griffiths, Martyn Bull, Ian Bush, Luke Carrivick, Richard Jones and Matthew Burns

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  • RiskAware. capability through technology

Aims of CBRN IM

  • To seamlessly acquire, process and

deliver data, information and knowledge

  • To provide best possible picture of

CBRN situation now and into future

  • To support the decision maker in

making optimal decisions

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  • RiskAware. capability through technology

Application

  • Military
  • Homeland security
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  • RiskAware. capability through technology

Overview of CBRN IM Systems

  • Example operational systems

– JEM/JWARN

  • US DOD

– NARAC

  • US DOE

– ARGOS

  • Multinational
  • PRIME

– Prototype Response and IM Engine – Prototype system developed by RiskAware to demonstrate, test and evaluate concepts and capabilities

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  • RiskAware. capability through technology

Overview of CBRN IM Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Challenge Planning Simulated Real world GIS

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  • RiskAware. capability through technology

Overview of CBRN IM/DS Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms GIS Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Simulated Real world Challenge Planning

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  • RiskAware. capability through technology

PRIME Demo

Challenge Sensor model Fusion Hazard Response

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  • RiskAware. capability through technology

Overview of CBRN IM Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms GIS Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Simulated Real world Challenge Planning

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  • RiskAware. capability through technology

CB Challenge For Studies

  • Standard evaluation

– Use standard T&D model with sensors & effects – Monte Carlo sampling of inputs

  • Advanced simulated challenges using

CB Challenge Generator

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  • RiskAware. capability through technology

Example Output

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  • RiskAware. capability through technology

Sample Time Series Output

10 20 30 40 50 60 70 80 90 100 20 40 60 80 100 Time (s) Particle Count Sampler 1 Sampler 2 Sampler 3 Sampler 4

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  • RiskAware. capability through technology

Cases Considered 1: Bagram

Long term placement – threat could be anywhere Placement for 3 months – believe base is targeted Placement for 1 month – concern

  • f release

near base entrance Placement for 1 week – intelligence

  • f attack

from insurgents NE of base

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  • RiskAware. capability through technology

Cases Considered 2: Bristol

Threat to area surrounding key civic buildings Town square surrounded by offices

  • f telecoms

company Vague intelligence

  • f threat of

release in Bristol Intelligence report of release from boat

  • n the river
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  • RiskAware. capability through technology

Overview of CBRN IM Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms GIS Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Simulated Real world Challenge Planning

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  • RiskAware. capability through technology

Sensor Placement Aims

  • CBRN sensors limited resource &

placement needs to provide maximum information for response & protection

  • Approaches

– Automated optimisation – Rules based

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  • RiskAware. capability through technology

SPARTA Overview

  • SPARTA optimises placement to minimise the

casualties for described threats

– Multiple releases considered that match scenario – Placements that provide best overall reduction of casualties across all releases selected

Sampler Reusable data store Effects Calculation Optimiser Results CB hazard model Inputs

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  • RiskAware. capability through technology

SPARTA Overview

  • Analysis has shown

– 1000 model runs required for simpler scenarios – Up to 5000 for complex scenarios

  • SPARTA can provide
  • ptimal placement in

~10 mins for complex scenarios running on a standard laptop

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  • RiskAware. capability through technology

Example Placements

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  • RiskAware. capability through technology

Rules Approaches

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  • RiskAware. capability through technology

Results of Ensemble Model Challenges

%age casualty reduction using SPARTA %age casualty reduction using rules approaches

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  • RiskAware. capability through technology

Results of Ensemble Model Challenges

Approach Average rank for test cases Total %age casualties saved SPARTA 1.12 81 Rule A 3.58 72 Rule B 3.84 71 Rule C 3.98 70 Rule D 4.4 69 Spread in protection area 4.6 69 Place evenly around prot. area 5.48 65 Spread evenly across domain 8 36 A B C D

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  • RiskAware. capability through technology

Results of Advanced Model Challenges

%age casualty reduction using SPARTA %age casualty reduction using rules approaches

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  • RiskAware. capability through technology

Results of Ensemble Model Challenges

Approach Average rank for test cases Total %age casualties saved SPARTA 2.42 86 Rule A 3.14 79 Rule B 3.98 78 Rule C 3.9 77 Rule D 3.6 77 Spread in protection area 4.52 76 Place evenly around prot. area 4.6 72 Spread evenly across domain 7.92 37 A B C D

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  • RiskAware. capability through technology

Sensor Placement Benefits

  • Sensor placement strategies result in improved

protection

– Major casualty reduction over random placement – ~35% compared to 70%-80%

  • Rules can be applied that provide good results
  • Automated optimisation approaches provide

best results

  • Tools such as SPARTA can provide rapid
  • ptimal placement
  • Decision aids for pre-event planning have merit
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  • RiskAware. capability through technology

Overview of CBRN IM Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms GIS Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Simulated Real world Challenge Planning

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  • RiskAware. capability through technology

Fusion & Assimilation Aims

  • Lack of information on source and met
  • Need to exploit any information from

deployed CB sensors

  • Aim to provide best situation awareness

through providing accurate inputs to hazard prediction

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  • RiskAware. capability through technology

Nowcast Assimilation Prototype

  • Developed hazard

now-casting approach

– Fits gaussian mixture model to

  • bservations using

EM algorithm – Rapid – Dynamically updates – Compatible with

  • perational hazard

models

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  • RiskAware. capability through technology

Nowcast Assimilation Prototype

  • Estimates wind speed and direction

– Robust to error in met input – Provides local met observation

Challenge dosage Standard modelling using erroneous met Nowcast total dosage with erroneous met

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  • RiskAware. capability through technology

Evaluation

  • Realistic scenarios using

Bristol with vignettes sampled from 4 threats and 5 met conditions

  • Used high resolution

challenge data generated by Evaluation System

  • Compared

– True release – Standard doctrine – Nowcast

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  • RiskAware. capability through technology

Evaluation

  • Calculated dosage for

each

  • Used MOE metric

– Ideal for comparing contour levels – Thresholded at LCt50

PR OV OB OV

A A A A MOE ,

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  • RiskAware. capability through technology

Evaluation Results

  • Met provided

to all models

  • All performed

well

– Nowcast is best

Approach MOE dist True Rel 0.196 Doctrine 0.216 Nowcast 0.166

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  • RiskAware. capability through technology

Evaluation Results

  • Met error included in

input to models

– 10o-30o

  • Performance worse

for all

  • Nowcast significantly

better

– Handles incorrect met

Approach MOE dist True Rel 0.831 Doctrine 0.771 Nowcast 0.278

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  • RiskAware. capability through technology

Fusion & Assimilation Benefits

  • Can lead to improved hazard prediction

– Nowcast provides better situational awareness than doctrinal approach and even modelled releases from true source

  • Can estimate other useful parameters

such as meteorology

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  • RiskAware. capability through technology

Overview of CBRN IM Systems

Fusion & Assimilation Hazard Prediction Effects and Response Modelling Reach back Weather Sensor Management Sensors Sensor Placement Display (COP) Comms GIS Incident data Analysis Tools Intelligence preparation Information fusion Infrastructure Prediction modelling Consequence management Data sources CBRN IM System Link to Reach back Simulated Real world Challenge Planning

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  • RiskAware. capability through technology

Aids for Response Decision Making

  • What are the benefits of data

assimilation and improved hazard prediction?

  • Can we provide automated real-time

tools to help decision making for the

  • ptimal response?
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  • RiskAware. capability through technology

Aids for Response Decision Making

  • Modelled effects of different response

strategies

  • Used Bagram scenario
  • Compared

– True source, doctrine, Nowcast – With and without input met error

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  • RiskAware. capability through technology

Comparison of Response Strategies – with Accurate Met Input

%age casualty reduction using true source and evaluated mitigation %age casualty reduction using different strategies

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  • RiskAware. capability through technology

%age casualty reduction using true source and evaluated mitigation %age casualty reduction using different strategies

Comparison of Response Strategies – with Inaccurate Met Input

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  • RiskAware. capability through technology

%age casualty reduction using different approaches IPE Burden Measure (1 = full suite warn at all times)

Comparison of Response Strategies and IPE burden for Nowcast

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  • RiskAware. capability through technology

Comparison of Response Strategies and IPE burden for Nowcast

  • In this case evaluated response

performs the best

Strategy Total Casualties Saved Average IPE Burden Measure Evaluated response 2335 0.073 Multiple threshold 1530 0.092 Outer garment 50 0.008 Respirator 1382 0.050 Full suit 2089 0.082

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  • RiskAware. capability through technology

Aids for Response Decision Making Results

  • Strategies applied can make a

difference

– Casualties sometimes reduced by >25%

  • Only simple ones so far considered
  • Automatic evaluation of different

response can provide some benefit

  • More work required
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  • RiskAware. capability through technology

Summary

  • Considered range of key elements in CB IM
  • Implemented as prototypes within PRIME
  • Evaluated using realistic challenge
  • Decision aids considered show benefit

– Casualty reduction – Potential to lead to improved operational performance

  • Suggests CBRN IM can improve situational

awareness and aid decision making

  • Have demonstrated prototype capability for

studying complex effects

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  • RiskAware. capability through technology

Future Ideas

  • Enhance and optimise components within

PRIME

  • Evaluate in

more detail

  • Consider interaction

between them

  • Further quantify

benefits

  • Extend to urban
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  • RiskAware. capability through technology

Investigating the Benefits of Information Management Systems for Hazard Management

Ian Griffiths, Martyn Bull, Ian Bush, Luke Carrivick, Richard Jones and Matthew Burns