for disaster management

Transcription

1 a project using SoA technology for disaster management N. Lewyckyj December 4 th 2008

2 OSIRIS is a EC FP6-IST project OSIRIS: Open architecture for Smart and Interoperable networks in Risk management based on In-situ Sensors 32 months project Web architecture using OGC standards and open source services Numerous types of smart sensors involved (fixed/mobile, µ/macro, stand alone/networks, wired/wireless, automatic/manual, on-site/remote) 13 partners, incl. 4 end-users 1

3 Osiris sensor web Architecture: main objectives Development of an open and flexible architecture of environmental sensor networks Integration, ti plug&play l of sensors or networks of sensors into a web services architecture Providing an easy access and a wide share of information and services. Capable of reconfiguration and evolution : different phases of crisis and additional sensors plug-in. No sensor development - Only integration of existing systems 2

4 3 4 demonstrations will demonstrate the OSIRIS capabilities

5 Forest fires 4

6 Forest fire scenario Location : South of France End-user : Entente interdépartemental de la Zone Sud (13 departments, t ~ firemen) Real fire on a hill (used to secure the zone before the fire season) Deployment : normal intervention team and material + 4 type of sensors provided by OSIRIS Demonstration : First week of March 09 5

7 LEGEND SATELLITE COM WIRELESS COM WIRED COM Forest fire global deployment Mobile Central Data RAW DATA COMPRESSED Ground Processing Control Centre (CDPC) Station in Mol REAL TIME IMAGERY ARS SENSOR MONITORING / SUPERVISION UNPROCESSED DATA PROCESSED DATA ARS MONITORING / SUPERVISION SWE OSIRIS TRUCK SWE SWE BU BU WIRELESS SMART IMAGING SENSOR PC BU MAP FOREST FIRE HOUSES BU Firemen : 19 Trucks : 3 ROAD OPERATOR DISPLAY 6 POSITIONNING SENSOR SYSTEM BU

8 Description of the airborne RS system within OSIRIS ARS SYSTEM RS platform AB3 Satellite Data link receiver COMPRESSED SYNCHRONIZED DATA Central Data Processing Centre (CDPC) at VITO (Mol) µ-paf OGC-standards Manned aircraft with video camera 7

9 Manned system: Providing 30 cm GSD Acquisition in NADIR Data downlink in real-time Video stream => reprocessed to georeferenced composite images Simulation of the HALE UAV 8 Possibly small UAV systems : Autopilot t with flight plan (way points) VITO Perform on demand changes in the flight planning using web services (automatic way) Perform static survey Able to fly above real fire (> 5000 Ft) GEOCOPTER

10 Georeferenced images provided in real time from video stream 9

11 Georeferenced images generated in real time from video stream MercatorLow.mpg 10

12 Air pollution 11

13 Air pollution Scenario Location : City of Valliadolid (Spain) End-user : AUVASA Simulation atmospheric release Deployment e : Mobile air quality sensors on buses, fixed air quality sensor network, small UAV, dispersion Model Demonstration : 26/11/

14 Light micro-uav: The THALES SPY ARROW Main characteristics: TOW: 0,5 kg Mission duration: 30 minutes Flying speed: km/h Manual and autonomous flight Mission supervision from standard PC Easy to use: One-Man system Standard take off or catapult launching from ground vehicle (to come) Easy sensors adding (UAV is polystyrene made) Typical missions: Long range and furtive day observation and surveillance Samples collecting (NBC) 13

15 Hardware: Sensors integration Chemical / hygrometer / temperature sensors Camera Autopilot GPS Barometer 14

16 15 Thales Spy arrow µuav system

17 The UAV allows real-time - air quality measurements Use of a small UAV (THALES) for : - Video imagery of the site - NO 2 concentration measurements in the air - Meteorological parameters Meteorological data used in real-time in a Puff model (VITO) to asses the pollutant dispersion in the air. Simulation done in real-time in Belgium => Validation of the prediction using the UAV + fixed and mobile measurements in Valliadolid (GMV) 16

18 Thank you for your attention 17