Base Protection Lab (BPL)
Presentation to BMVA
Symposium on Security and
surveillance: performance
evaluation
ONR Program Officer: William “Kip” Krebs, 703-696-2575, william.krebs@navy.mil
Alternate POC: Annetta Burger 703-696-1330, annetta.burger.ctr@navy.mil
December 12, 2007
Objectives
• Conduct basic research to provide more open public
access to recreational and other non-restricted
facilities on military bases and to improve the overall
base safety and security utilizing advanced video and
signal based surveillance.
• Create test bed in Hawaii to evaluate whether novel
sensors (video cameras, radio frequency identification,
seismic, LIDAR, microwave, and infrared sensors) in
combination with behavior analysis software can
identify patterns of behavior.
Page 2
PMRF BPL System Diagram
PMRF Base Protection Laboratory (PBPL)
Data Collection (Integrated Sensor Systems)
RFID
MW / IR
Lidar
Seismic
Video
Textual
Others
Alert
Delivery &
Situation
Data
Development
Platform
Sensor Data Links (Wireless)
Sensor Data Processing
Data Storage &
Archiving
Simulation &
Playback
Behavioral Analysis
Middleware
Remote Users
and Developers:
– SAIC Kauai
– SAIC Maui
– SAIC Arlington
– UH Manoa
– Novasol Oahu
– Object Video
– MHPCC Maui
– Others
Firewall
Internet
External (Wide Area) Network
Base
Security
Data Fusion &
Tracking
- Automated Behavior
Analysis (ABA)
- Statistical Anomaly
Detection (SAD)
- Agent Based Modeling
(ABM)
Alert
Generation
Production System – Data Analysis and Management
Page 3
Current BPL Sensor Configuration
22°00’51.66”N 159°46’56.28”W
• Outdoor Test Bed
– 4.5km by 1km area
– Linked by wireless
communications
• Open Architecture
• Hardware Configuration
– Mobile sensors enable
optimum sensor coverage for
data collection exercises
• Software Configuration –
modular, flexible and reusable
– Object-oriented software
– Based on Java Jini
architecture
– Communication through a
“blackboard”
Page 4
Sensors
RFID System – UltraWideBand
2 LIDAR motion trackers
5 License Plate Readers
8 Low Light Cameras
4 Video Cameras
Seismic Array (2000 feet)
2 MW/IR Fence Posts (500 feet fence)
Page 5
Data Collection
• Data Collection
– Scripted Scenarios for Abnormal Activity
• 4 Days data of confederates
– Normal Data
• 2 Days data of base personnel and recreational visitors
• Sensor Collection Results
– 12 video cameras with advanced video analytics software
• detected and tracked objects of interest without problems
– LIDAR – converted for intrusion detection and alarm sensor
• Detected and provided accurate alerts
– Microwave and Infrared Detection Fences
• 100% detection and 0% false alarms for motion detection
– RFID
• Limited coverage to be improved with tuning antennas and replacing fixed
sensors with mobile units
– Seismic
• No data available due to compatibility issues
• Sensors should be available Jan08
Page 6
Proposed RFID Coverage
2D coverage (coordinates)
Seen by three or more receivers
Provides (x, y) with 3m or better accuracy
1D coverage (a point between two sensors)
Seen by two receivers
Provides a point (xΣ , yΣ) on a line
between the two sensors.
0D coverage (presence in an area)
Seen by one receiver
Provides the coordinates of the
sensor (xS , yS) that sees the entity
No detection (no information)
Seen by none of the receivers
Page 7
RFID Track
Page 8
Video Tracks
Page 9
LIDAR Sensor
1000 feet
Page 10
LIDAR Tracks
map overlay
System Administrator Display
- pedestrian and vehicle traffic
Page 11
Challenges
• Develop a reliable, plug-play, robust test bed to meet
researcher requirements.
• Develop common standard data sets that vary in
difficulty that can be used to assess algorithm
performance.
• Develop valid and reliable metrics to evaluate and
compare behavioral algorithm performance.
Page 12
Future Plans
• Create common data sets and metrics.
• Distribute data sets to research community to test
whether behavioral algorithms can detect “normal” and
“anomalous” behavior for the prediction of threats and
advance warning using a variety of sensors.
• Test and evaluate sensor options to optimize early
detection of threat behavior and reduce security
manpower requirements.
Page 13