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Fire Detection in the Urban Rural Interface through Fusion Techniques
Evangelos Zervas
Odysseas Sekkas
Stathes Hadjiefthymiades
Christos Anagnostopoulos T.E.I. Of Athens, Department of Electronics
Pervasive Computing Research Group, Department of Informatics and
TelecommunicationsUniversity of Athens, Greece
MASS-GHS07, 08.10.2007, Pisa, Italy
Fire Detection in Urban Rural Interface (URI)
Early work in the framework of SCIER (FP6-IST) (Sensor & Computing Infrastructure for Environmental Risks)
zone ofinterest
Fire Detection in URI: Architecture
Local Alerting Control Unit (LACU)
•Early fire detection•Fire location estimation•Alerting function
Citizen Owned Sensors Publicly Owned Sensors
Types of sensors:
•Temperature•Humidity•Wind flow•Cameras
Physical Model
Temperature ( T )
Fuel mass function ( F )
after 30sec. from ignition
Fire is s ens ed on ly few
er met ers from
the ignit ion po int
Binary hypothesis problemML Criterion:The “No Fire” Case
sensor measurement for sensor j
Gaussian with mean μ(h)
Mean μ(h) depends on:•time (hours/month),•empirical models,•forecasting,•sensor readings that are more up-to-date
[Walter’s model]
[Drop the D highest and lowest temperature measurements out of K available]
sensor measurement noise (zero mean)
ML Criterion: The “Fire” Case
random variable qj measures the excesstemperature due to fire
Gaussian with mean μq(h)
We consider a heat radiation modelwith mean μq(h) depending on:•ΔH (excess temperature at fire location)•x (distance of the sensor from the fire front)•a (exponent obtained from the physical model)
Receiver Operating Characteristics (ROC)
Parameters:
μ(h) = 300K,σs= 3 K,σn= 0.5 K,σq= 1 K,a= 2.3,ΔH= 700K
Receiver Operating Characteristics (ROC)
R: monitoring area of temperature sensors for creating a dense lattice of sensors for fire early detection
R
Current Work in SCIER
Use of (fuzzy) Neural Nets and/or BN for classification using data from temperature and humidity sensors,
Use of alternative criteria, i.e. CUSUM sequential algorithm,
Use information fusion at a higher level (Computing Subsystem) taking into account the vision sensors.