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Craig Holmes Brad Klippstein Andrew Pottkotter Dustin Osborn.

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Presentation on theme: "Craig Holmes Brad Klippstein Andrew Pottkotter Dustin Osborn."— Presentation transcript:

1 Craig Holmes Brad Klippstein Andrew Pottkotter Dustin Osborn

2 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 “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.

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5 Bird/Bat Calls Embedded Recognition System Bird SystemBat System Hardware 10 bit ATMega 328 A/D microcontrollerAR125 Ultrasonic Receiver Microphones StandFR125-III Field Recorder Four UEM-88 Mini Shotgun Microphones MAYA-44 PC Software Bird Call LibrarySPECT'R Software Raven-XSCAN'R Software MatlabSonoBat Software

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7 Incoming Unknown Bird Call Take First 512 Data Points from Call Apply Hamming Window to Data Points Derive Fourier Transform of Data Points Find the Magnitude of the Fourier Transform Multiply by the Mel Frequency Scale Gather Mel Frequency Cepstral Coefficients Apply Discrete Cosine Transfrom to MFCC's Place First 9 Coefficients in MFCC Bank Move to Next 512 Data Points from Call Once through all 220,500 Data Points of Call, Send MFCC Bank to Correlation Algorithm for Matching

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

9 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]

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12 Incoming Unknown MFCC Bank Calculate Pearson's Correlation Coefficient with first database call Calculate Next Pearson's Correlation Coefficient for next known call Repeat calculating correlation coefficient for all database calls Output call with highest correlation as best match If all calculated correlation coefficients below threshold then unknown call

13 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 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 Correlation Coefficient of.6411

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17 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 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 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.

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