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Bird and Bat Call Embedded Recognition System

Bird and Bat Call Embedded Recognition System. Craig Holmes Brad Klippstein Andrew Pottkotter Dustin Osborn. Purpose. Wind Turbines have become a great source of alternative “green” energy Lake Erie and North West Ohio have the potential to be a great source of wind energy.

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Bird and Bat Call Embedded Recognition System

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  1. Bird and Bat Call Embedded Recognition System Craig Holmes Brad Klippstein Andrew Pottkotter Dustin Osborn

  2. Purpose • Wind Turbines have become a great source of alternative “green” energy • Lake Erie and North West Ohio have the potential to be a great source of wind energy. • North West Ohio also happens to be one of the largest migratory bird fly-ways in the country • Before wind turbines can be installed questions need to be answered about the effect they will have on the avian population in the area

  3. Purpose • “As wind energy facilities becomes substantially more numerous and as wind development continues to grow, fatalities and thus the potential for biologically significant impacts to local populations increases” –National Wind Coordinating Collaborative • The BBCER strives to create a way to identify what avian species are being impacted by the wind turbines and to allow for conclusions to be made about what effect they are having on the species.

  4. BBCER

  5. Components

  6. Bird Recognition Side of System

  7. Recognition Algorithm

  8. Mel Scale • “Scale of pitches judged by listeners to be equal in distance from one another”[1] • Converts Hertz scale to Mel scale.

  9. Mel Frequency Cepstral Coefficients • Cepstral: Fourier Transform of the log spectrum. [1] • Mel Frequency Cepstrum (MFC): Representation of the short term power spectrum of sound, based on a linear cosine transform of a log power spectrum on a nonlinear Mel scale of frequency.[1] • Mel Frequency Cepstral Coefficients (MFCC): Coefficients that collectively make up an MFC[1]

  10. Original Call

  11. MFCC’s

  12. Correlation Algorithm

  13. Pearson’s Correlation Coefficient • Measures the correlation between two linear dependent variables. • Signified by r (rho) and can take on values between -1 to 1. Where -1 signifies perfect negative correlation, 0 is no correlation, and 1 is perfect positive correlation. • The previous example of American Crow and American Coot yield an r value of 0.4650

  14. Bird Results • With our system we are able to successfully identify an ‘unknown’ bird call that has been recorded through the UEM-88 mini-shotgun microphones and interfaced to the PC with the MAYA-44 USB device.

  15. Results Continued… Correlation Coefficient of .6411

  16. Bat Recognition Side

  17. Bat Recognition • Together the AR125 and FR125-III record the ultrasonic bat calls from the field. • They then work with the SPECT’R, SCAN’R, and SonoBat software to determine the species of which the call came from. • The system has been tested and has successfully identified species of bats in the field.

  18. Bat Recognition • There are three software programs that we purchased for bat call analysis • SPECT’R • SCAN’R • SonoBat. • SPECT’R is used to perform spectral analysis, digital tuning, and hard-disk recording of echolocation calls. • SCAN’R is a snapshot characterization and analysis tool which is used to distinguish between bat calls and unwanted noise. • SonoBat can be used to analyze and compare high-resolution full-spectrum sonograms of echolocation calls.

  19. Future Recommendations • Because of the Microcontroller, that we purchased, memory limitations , we are unable to successfully record an audio call with enough data points to be ran through our algorithm. • In the future we recommend purchasing a microcontroller with at least 512kB SRAM to get a correctly sampled call plus room to store the code. • We also recommend making the system wireless so that the system could be placed in the field and left to record bird calls overnight or for long durations.

  20. Questions???

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