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Flight Path Tracking by ultrasound detection Measure impact of human infrastructures Diagnostic the efficiency of crossings structures D. Mauuary M. Charbonnier Partnership : EGIS Environnement (H. Pouchelle) CHIROPTERES ET INFRASTRUCTURES DE


  1. Flight Path Tracking by ultrasound detection Measure impact of human infrastructures Diagnostic the efficiency of crossings structures D. Mauuary M. Charbonnier Partnership : EGIS Environnement (H. Pouchelle) CHIROPTERES ET INFRASTRUCTURES DE TRANSPORT TERRESTRE 1 Strasbourg, SFA, Decembre 2013

  2. About us ?  Founded by DM, Signal and Image processing PhD, INP Grenoble, Post Doc in IFM Kiel, publications in IEEE, JASA, Nature,...  Startup created in 2010  5 employees  R&D Bioacoustic Hardware and software solutions for wildlife researchers 2

  3. Summary  Technique  Field results  Perspectives  The « iBat City » project 3

  4. Technique  Motivations for flight path tracking • Bat population are data defficient • The bat detector needs a lot of understanding and processing effort by biologist that are acousticiens nor signal processors • Ultrasound acoustics brings a huge quantity of data (what about the usefullness of these data in terms of ecological knowledge) • real lack of dialogues between researchers from different fields ( acoustics, biologist, ecologist, ethologist, neurologist, signal processors, mathematicians, computer scientist, electronics designer, ... ) 4

  5. Technique  Motivations for flight path tracking • MICROSCOPIC SCALE : understang the exact behavior of each individuals at the Detection distance of an acoustic array • MESOCOPIC SCALE : understanding the day life migration and habitats at the scale of a whole habitat territory • MACROSCOPIC SCALE : understanding the population size and global effects (due to climate change or habitat size permanent reduction) 5

  6. Technique The principle of Flight Path Tracking by ultrasound detection  We use an array of 2 to n communicating sensor  Sensors can be ultrasonic microphones, hydrophones or infra red cameras Tetrahedron shaped antennas with four sensors  Animals detection, localisation, classification in aerial and submarine field 6

  7. Technique Voix 1 Voix 2 Voix 3 Voix 4 Schematic representation of the The sound arrive with a time difference on each sound arrival on the antenna microphones  Animals which moves by echolocation emit pulses to locate themself in their environment  These ultrasounds are frequently emitted (sometimes several times per second) so they are a excellent means of locating an individual  These pulses are registered by the microphones but they reach them with a time difference 7

  8. Technique  If We know the positions of each sensors and the distances between them we can calculate thanks our powerful algorytms the position X,Y,Z of each pulse  The result is the pulses localisation which allows us to reconstrct the bat trajectory (with a precision of 10 cm in certain condition)  Know where and when the pulses are emitted allow us to compare the animal trajectory to its environment perception. 8

  9. Technique The quality of the localisation dependent of:  The antenna geometrical shape and quality of the sensors  The environment (acoustic reverberation, signal versus noise)  Species studied (power emission , signal characteristics,) 9

  10. Résultats Feew results of impact studies  A406 Mâcon : Bat underpass  Bourges : Bridge over a highway Laurent Arthur ( Bourges Museum) http://www.museum-bourges.net/chauve-souris-etudes-39.html  Rambouillet : Net in forest Laurent Tillon (ONF national forest office France ) 10

  11. Résultats Problematic : does structure let pass the bats and how they cross it ? Data treatment plot ( x, y z ) Measuring site Flight path in a 3D environment for a better Brut Trajectory understanding and simulation 11

  12. Résultats Trajectories of seven pipistrelles (Pipistrellus kuhlii ) which pass under the highway to join the other forest. 12

  13. Résultats Bourges : How guide the bats on a bridge to avoid they crash on the higway ? A wooden fence was installed to direct the bats on bridge . This trajectory shows that the bat dont want to take the bridge !! 13

  14. Résultats Rambouillet : Identification of corridor used by the bats to move across the forest ? Installation of a net on an aerial corridor 14

  15. Résultats Bats arrive by small lateral corridors and pass over the forest path to use a larger corridor. Generally they repere the net and avoid it. We can observe a raise of pulsse some seconds before they change of direction. Left graft Myotis bechsteinii ; right graft Plecotus sp 15

  16. Résultats First Batbridges in France From European « Meetings business and Biodiversity », Eiffage, January 31, 2012 16

  17. Applications and Possibilities Improvement of biological and behavioral knowledge :  Highlight microscopic migration flows  Flight in relation to the environment  Species behaviors  Altitude  Speed  Synchronization between motor and sensory system  Environment perception  And more … 17

  18. Applications and Possibilities  Diagnostic the efficiency of crossings structures according to their intrinsic and environmental characteristics  Batbridge, Corridor, Underpath, Net....  Informations: avoidance distance, speed, frequency of pulse, structure proximity  Animal perception of the structure related to its size, shape, position  Calcul the impact of human infrastructures  Buldings, Highway, Light polution, Noise polution....  Demonstrated a correlation between trajectory and visual disturbance / noise ( Dries P.J. Kuijper, 2008 ; Emma Louise Stone 2009 )  Highlighting details of how corridors (direction of growth and density correlated) 18

  19.  The iBat city project : deploying ultrasound sensors at an urban scale  Using smartphone as acoustic sensor up to 20 Khz : low frequency bats ( Tadarida and Nyctalus )  Deploying a wifi ultrasound sensor for species up to 120 Khz  Estimating the path trajectories at large scale : MESOSCOPIC not MICROSCOPIC  Calculate the correlation between roosts, displacement and anthropegenic activities 19

  20.  Key success factors :  A smart phone apps (windows, android, ios)  Participation of citizens : creating social /cultural events with music, science, and challenges  50, 100, 200, 1000 sensors ?  What is exactly the exact number of sensors to measure flight path densities (MESOSCALE point of view point)? 20

  21.  iBat city challenges :  Distribute the software freely for volunteers  Working with NGO (LPO-Isère)  Use dense networks of microphones  Measuring noise level in a distributed manner  Searching sponsors and research partners... 21

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