Sensor & Computing Infrastructure for Environmental Risks SCIER FP IST-5 Stathes Hadjiefthymiades (NKUA) 1st Student Workshop on Wireless Sensor Networks Brussels, Oct. 2008

Main Objectives Sensor network infrastructures for the detection and monitoring of disastrous natural hazards. Advanced sensor fusion and management schemes. Risk evolution models simulated on GRID. Multi-risk platform. Public-private sector cooperation.

SCIER architecture

SCIER Sensing Subsystem Sensor Infrastructure –In-field sensor nodes (humidity, temp, wind speed/direction) –Out-of-field vision sensors (vision sensor) Sensor Data Fusion

SCIER Computing Subsystem Computation and Storage Environmental models –Flash Floods (FL), forest fires (FF) –GIS Infrastructure –Storage, analysis and visualization of monitored data, spatial calibration and event localization Predictive Modeling Front-End Subsystem

Local Alerting Control Unit (LACU) Data flow Control flow DataBase Computing Subsystem Alerting Infrastructure JDBC Sensor Infrastructure Sensing system proxy XML LACU Software modules Remote Administration console OSGI

Computing Subsystem Architecture

LACU Fusion Component (FF) Receives sensor data and executes fusion algorithms. Generates fused data with degree of reliability. Fused data fed to the Computing Subsystem.

2 nd Level Fusion Process (FF) in CS Camera data and Fused sensor data from LACUs are processed. Algorithms: – Voting algorithm – Dempster Shafer Theory of Evidence Triggers simulations according to the final probability of fire, flood, etc.

Simulation of several possible futures through the GRID infrastructure. GRID used to simulate many possible future situations (1-100) under different propagation conditions results analyzed to identify the size and shape of the resulting burned area, and provide probabilities for each of the simulated futures. FF simulation modeling

Conditions stored in metadata catalog Engine for parsing and evaluating conditions based on incoming data. Interface with Simulation subsystem triggering model execution based on fusion result Condition evaluation engine Sensor input data Metadata Catalog conditions Fusion Decision FL Modeling

SCIER GRID and FL with web- services Fusion Sensors Storage for: - fire models executables - model input data - model structural data - model output data - Pre-prepared WS + CS scenarios Services GRID SCIER central point Collect data (location+time+value): - precipitation - temperature - humidity - wind ArcGIS Executes fire modelling jobs User interface Simulation PC(s) Executes 1D flood modelling jobs Incorporates pre-calculated flood maps lookup Forwards data to storage Issues simulation jobs Runs web server with UI Web services File share, SQL SQL HTTP

System Validation & Evaluation Testing includes both fires and flooding – Gestosa, Portugal (experimental and controlled burns) – Stamata, Attica, Greece (fires, system deployed) – Aubagne, Bouches du Rhone, S. France (fires and floods, deployment underway) – Brno, Czech Republic (floods, system deployed)

System Validation & Evaluation Gestosa, Portugal (experimental and controlled burns)

System Validation & Evaluation Stamata, Attica, Greece (fires, system deployed)

System Validation & Evaluation Aubagne, Bouches du Rhone, S. France (fires and floods, deployment underway)

Thank you! Project website: