adaptive multi-sensor integrated security system (amiss) august 1998

Adaptive Multi-sensor Integrated Security System

(AMISS)

August 1998

Los Alamos National Laboratory 2

AMISS Agenda

• AMISS Overview• Source Detection and Location• Path Tracking Anomaly Detection• Multi-sensor Data Fusion• Shape Recognition and Identification• Reasoning/Data Mining• Remote Operation• AMISS Integrated Exercise


AMISS Vision

Develop and demonstrate state-of-science adaptive technology to determine potential threats and anomalous situations and ascertain appropriate action to increase facility security, safeguards, and safety.


AMISS Strategic Objectives


AMISS Strategic Objectives

• Provide continuous, adaptive real-time detection and categorization of all activity• Assist security personnel• Enhance material movement monitoring• Reconstruct threatening events• Ensure compliance


AMISS Tactics

• Develop test bed• Learn correct/acceptable facility operating

conditions and detect unusual behavior• Build techniques for active facility• Build portable capabilities • Provide feedback to security personnel


AMISS Challenge


AMISS Architecture

Whole Is Greater Than The Sum Of The Parts


AMISS Schematic


AMISS Architecture


Source Detection And Location

• Long-term vision– Detect, identify, and locate multiple sources

and track movement and activity

• Initial goal– Detect and locate single moving source in a

room


Source Location Problem

• Detector gives imperfect information• Source moves around room• Inconsistent signals (candle flickers)• Background changes • Detectors are non-directional• Shielding or occlusions


Source Location At A Glance

• Isocounts as single bands with known source strength


Simplistic Source Location

• Overlapping isocount Bands gives X,Y,Z and strength


Source Location Solution• Estimate X, Y, Z background levels• Radiation detection model for rectangular detector

and spherical source• Optimization algorithm

– Kalman Filter– Constrained optimization

• Elements of uncertainty– Counting statistics– Occlusion, shielding– Varying background– Directional detectors


Source Location Future

• Improve Location Accuracy with known source strength• Locate Multiple Sources • Deduce multiple source strength• Deduce Nuclear Signatures• Decrease uncertainties– Location– Source Strength– Source Material


AMISS Architecture


Path Tracking Anomaly Detection

• Automated process using data collection to locate individual movement to detect and determine anomalous behavior patterns


Path Tracking Anomaly Detection Current Technology

• Unsupervised neural network• Clusters spatial-temporal patterns• Learns individual behavior• Defines normal behavior – X, Y locations in sequence– Broader patterns


Path Tracking Anomaly Detection AMISS Innovative Technology

• Determine anomalies from examples of normal behavior - more secure• Real-time• Provide explanation facility• Learns quickly• Customized by changing sensitivity

parameters


Path Tracking Anomaly Detection Future• Facility Security

– Identify number of people in a room– Identify open doors– Examine time– Determine expected behavior– Expand to larger areas

• Other domains– Verification of dismantlement activities– Assist IAEA inspections– Ensure unattended monitoring


AMISS Architecture


Multi-sensor Data Fusion

• Combining multi-sensor data to provide more accurate, descriptive, and useful information for higher-level reasoning and display


Multi-sensor Data Fusion Challenges

• Different sensor characteristics– Different data collected – Various accuracy– Various reliability– Different resolutions– Varying speed


Multi-sensor Data Fusion Current Research• Uses proven graph theory technique,

including edge trimming• Robust sensor suite – Handle sensor failure– Redundancy for level of assurance

• Fuse active and passive infrared and video to identify and locate personnel• Experimental code complete• Evaluation phase starting


Multi-sensor Data Fusion Future

• Integrate into AMISS • Research other methodologies• Add new sensor types• Framework for future development


AMISS Architecture


Shape Recognition and Identification - Initial Concept• Profile Evaluator for image identification

within controlled environment for entry control


Shape Recognition and Identification - Current Technology

moment p,q = x p y q f(x,y)x,y


Shape Recognition and Identification - Current Technology

y = W i X i z = tanh (y)

• Neural Net


Shape Recognition and Identification - Current Results

ERROR RATESActual1 Camera

Estimated3 Cameras

Tailgating .1700 .0049Crouching .0000 .0000Person +Object .0625 .0002Normal .0870 .0007


Shape Recognition and Identification


Shape Recognition and Identification Future


Shape Recognition and Identification - Future

• Detect and identify a complete inventory of objects in a scene– New Feature Extraction - Image Understanding– Better hardware – Post processing classification


AMISS Architecture


Reasoning/Data Mining

• ADaptive Virtual Integrating senSOR (ADVISOR)

• Provide continuous, integrated facility status reasoned from real-time and historical data and human input.


ADVISOR Expertise


ADVISOR Benefits

• Provides continuous real-time detection of procedure violations and anomalies• Reduce information overload and tedious

data analysis• Consistent rule interpretation and application• Continuous information integration• Continuity of knowledge • Provides detailed explanation capability• Active role, advisory role or combination


ADVISOR Objectives

• Knowledge engineering to obtain human expert experience • Integrate policies and procedures• Dynamic adaptation• Learn normal facility status


ADVISOR Components

• Real-time reasoning and control (current)• Data mining • Real-time integrated with data mining


ADVISOR Decisions


ADVISOR Decision

Is Joe supposed to move that material in that location?

YES


ADVISOR Future

• Develop System Health reasoning diagnostics• Expand to multiple buildings and facilities• Countermeasures (e.g. know when being

fooled)• New domain applications• Develop and integrate data mining


AMISS Architecture


Remote Operation

• World Wide Web (www)– Remote (e.g. global)– Secure (SSL)

• Remote alarm (e.g. notify guard through pager)• Potential to take action immediately• Operate several facilities


Remote Operation Capabilities

Shut Door Dispatch Guard

All OK Human hint to confirm ADVISOR Thought

ACTION

ADVICE/STATUS QUERY HUMAN EXPERT

CONFIRM ACTION

• Bringing it all together - remotely


AMISS


Potential Application Areas

•MC&A at DOE Facilities•Treaty Verification•IAEA– Remote (unattended) monitoring – Environmental monitoring – Covert and/or underground facilities

•Other – Critical infrastructure– Recent national and international incidents


AMISS Future

• Confidence versus redundancy• Aging facilities• Robust and hardened• Adaptable, portable, scalable• Address emerging requirements• Define measurable performance measures• Further reasoning development• Integrate to entire facility


AMISS Experimental Site — TA-18


AMISS Exercise - Conceptual Demo


AMISS Exercise - A Day In The Life

• Identify and locate personnel and material• Alert unauthorized activities, material

shielding, and unauthorized movements• Track paths of interest and detect anomalous

behaviors• Provide real-time facility status decisions

based upon all available data sources• Provide security personnel with effortless

facility status view



1. Unlock High Bay– Alarm unauthorized entry

2. Security Sweep High Bay– Alert attempted sweep against protocol pattern

3. Experiment Entry Procedures– Alert improper approvals, personnel, materials,

or schedule



4. Perform Experiment– Alert improper procedures with material– Alarm invalid exit while material shielded

5. Experiment Exit Procedures– Alarm unauthorized material removal

6. Secure High Bay


AMISS Integrated Exercise


Partnering To Solve Problems

NN-20Advanced TechnologyPush State-Of-The-ScienceIdentify Gaps & Fill ThemProvide Vision/Path ForwardLeverage OpportunitiesAnticipate Customer NeedsProvide Alternate Methods To Address Current & Emerging Challenges

NN-40Define NeedsIdentify Challenges

NN-50Define NeedsIdentify Challenges


Differences from Radiation Instrumentation Problems

• Instrumentation imperfections– Moving source within integration interval– Sensor sensitivity decreases with angle and

distance– Minimal detector technology


Radiation Detection

• Identify “Unusual” background changes• Factors in developing “Decision Rules”– Recognizable source strength– Recognition time– Time between events– Acceptable error rates• False positive• False negative


Radiation Detectors

• Gamma Detector– Gamma hits cause Fluorescence– Light flashes counted


THE AMISS TOOLBOX

SensorsVirtualSensors

ExpertSystems

AnomalyDetection

DataMining Brain Interface

videocamera

PIRs

palmreader

AIRs

sourcelocation

pathtracking

objectrecognition

multiplesensorfusion

DOErules

LANLrules

site specificrules

safetyrules

PTAD

multiplepeople

source

eventdriven

database

personelprofiles

SNMprofiles

sensorprofiles

expertsystem

neural network

mixture ofexperts

case-basedreasoning

demo

sitespecific

dialogue

security

Component Communication

each component has equal status and every component can communicate withevery other component


PTAD

multiplepeople

source

eventdriven

C_API dataformat

PTAD Specific Code

Communication Code

tracker hot_spot

C_API dataformat

source Specific Code

Communication Code

source variance

AMISS COMPONENT COMMUNICATION

Anomaly Detection

each component contains the same communication software


PIR/AIR

Video

Portal Monitor

Rad Detectors

Bar Code

Palm Reader

Database

PTAD

Face ItRad Tracker Sentry

Expert System

Web Interface

Blob Tracking

DEMO FLOW DIAGRAM


Expert System

ROOM STATE

Video Tracking

MOTION DETECTION

Sentry

Data Base

PTADFace It

PEOPLE STATE

Rad Tracker

SOURCE STATEACCESS CONTROL

Palm Reader

AIR

Video

PIR

RadDetectors

Bar CodeReader

Web Browser

INTERFACE

adaptive multi-sensor integrated security system (amiss) august 1998

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