How does an F-POD work?

The F-POD takes in sound in the frequency range 17 to 220kHz.

It updates its real-time analysis 4 million times each second and stores a record of 12 features of any click that might have come from a cetacean.

On the PC, dedicated software detects the sequences of clicks that cetaceans make to detect their prey and interact socially.

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How do F-PODs and conventional recorders compare?

  • Conventional sound recorders provide useful data for sound level studies and capture dolphin whistles and baleen whale calls. F-PODs do none of those and the data does not allow the Fourier Transform to be used to determine the frequency spectrum of complex sounds.
  • To collect the same cetacean click data as an F-POD, a conventional recorder must sample at approx. 500kHz, and use 16bit or larger values for each sample, so they will use a fixed 1TB of memory every 10 days or less, compared to generally much less than 1GB for an F-POD.  36 TB/year is a major problem so conventional recorders are often run in intermittent mode.
  • F-POD cetacean click data does not suffer clipping when the sound is very loud – this is handled in real-time processing.
  • F-PODs run for over 4 months continuously (or 8 months on lithium batteries) while conventional recorders sampling at 500kHz require more servicing visits due to battery or memory constraints. An F-POD can log alternate days for more than a year.
  • The F-POD data is optimised for the process of cetacean click train detection that is carried out during post-processing on a PC by the KERNO-F classifier. This is fast, accurate, consistent and free. Methods used on conventional data can be very slow and subjective .
  • The KERNO-F classifier also pulls out the click rates in fast click bursts that are used as social communication in many toothed cetaceans. This is proving to be of real biological significance.
  • The F-POD records the temperature and its angle to vertical every minute.
  • The F-POD housing is very robust and is externally simple so that bio-fouling can be removed easily.
  • F-PODs are buoyant and marked with a web URL so many have been recovered having been lost and subsequently washed up on a distant shore.
  • Data streaming and an integrated acoustic release are under development.

 

Here’s the pathway data, and settings, take through the system:

 

Conventional WAVE file recorders need to operate at 400kHz or above to record porpoises and they then typically record 1TB of data every 10days.

Such WAVE file data allows the use of the Fourier Transform (as FFT) to give frequency spectra. However very short sounds, like cetacean clicks, are not well suited to the FFT which also ‘loses’ half the information it receives. That data is not really lost, but is in a set of phase values that is of such limited practical use that it is rarely even mentioned. But it contains the information on when things happened in the click, i.e. the time domain.

The F-POD data is not suitable for FFT analysis, except in the case of the full waveform capture data.

Data from WAVE file instruments logging above 330kHz can be converted to ‘virtual F-POD files’ to get the advantages of data processing in the F-POD software. The classifier performance is then a long way below the normal performance on real F-POD data but can be useful.

F-POD features

F-PODs key features include: automation, long operation times, robustness, low false positive rates, high sensitivity and precise calibration. An F-POD:

  • stores very high resolution (250ns) time-domain data on each click to enable powerful train detection and species classification, so the need for visual editing of data is generally removed, although some visual inspection of each data file is mandatory.
  • has a simple on-board train detection that selects some clicks from trains so that some representative full waveforms can be saved.
  • detects and characterises short dolphin clicks more efficiently.
  • has automated adaptation to noise so that it does not often max out, even in severe conditions.
  • writes normal files to any micro SD card, up to 32 GB, without any special formatting.
  • for sites with many sonars it can run two real-time sonar detectors that can filter out boat sonars, and record their detections.
  • does not have the ‘drop-out’ of porpoise clicks seen in C-POD data.
  • has an improved hydrophone with less Z-plane variation.
  • has a real-time clock which you can set, e.g. to local time rather than UTC.
  • takes lithium batteries without any modification.
  • has a deep-sleep mode which enables the POD to run for years, sampling every nth minute.
  • can be set to start at a later date to enable ‘daisy-chaining’ of instruments.
  • can be set to switch on and off at different angles to the vertical.

Data differences

FeatureF-PODWav file recorder
Data volume Low. 120GB of F-POD data comprising 18years of continuous logging was collected in the early part of the BlackCeTrends project. It contained 400 million cetacean clicks.High. A similar duration would require >600TB of data storage
Click detect onlyYes. This is the normal mode of operation. Yes. Done using a variable threshold that includes a time constant that can be set at levels (>0.5 ms) that could interfere seriously with any future train detection.
Data format Dedicated file structure that packages metadata with acoustic data to give fast and reliable data management in projects. .FP1 and .FP3 files. Open source formats. Code to unpack these formats is directly available from the FPOD.exe app.Standard .wav file formats.
Data featuresSummary data on ultrasonic (>17 kHz) clicks and tones only. No data on dolphin whistles, etcFrequency range defined by sampling rate and hydrophone. Generally, this will include lower frequencies than the F-PODs so will allow studies of dolphin whistles, broadband calls, low frequency calls, etc.
Full waveform capture.
A simple real-time train detection routine can trigger capture of up to 21 cycles of a click. This has provided the new insights on the frequency slopes of narrow-band-high-frequency clicks in 6 different species already. A waveform can be constructed from this for FTT analysis, but will only be representative for longer clicks such as NBHF clicks.All clicks have the same sampling regime, which is ideal for spectral analysis using the FFT.
Noise monitoringSome noise indices are available but are not yet evaluated.Formal noise metrics usually possible.
Automated analysis
method
Click train detection and classification processes within FPOD.exe software. No beam forming processes.Click spectrum classification. Coherent beam angle sequences from towed pairs of hydrophones add power to the classifier.
Analysis strengthsExtensive experience in many countries of using this system has shown no major discrepancies from visual surveys where those are possible. Gives click rates in trains. This behavioural information is of value. False positive rates from pure automated analysis are low. In SAMBAH the combination of train classification and a previously developed Baltic data encounter classifier – ‘Hel1’ achieved a false positive rate of < 1 FP second per year.Fits traditional spectral analysis approaches.
Analysis weaknessesNo logged information on low frequency sounds.For NBHF species (porpoises and some dolphins) false positives from moving fine sand and other sources can be serious and may not be recognised by human analysts. For dolphins, spectral analysis is generally very weak and requires human editing of most detections, which is very costly, and requires quality control.
Analysis validationMultiple published studies with visual observation have all showed good resultsVery limited observational verification.
Analysis error messagesThe automated analysis flags up error risks in the results from a file.No warnings.
Temperature Recorded every minute No
Angle Recorded every minute. Provides a measure or currents and identifies some deployment problemsNo
Detection
performance
Our tests indicate that for porpoises the threshold is lower and at comparable false positive rates it is much lower. Good independent sea tests would be valuable.Unknown
Sonar filteringYes. To control data volumes, two independent sonar filters can operate in each minute.
No. If data recording is continuous this does not increase data volumes.

Hardware differences

Feature F-PODWAV file recorder
HydrophoneHydrophone with characteristics similar to a B&K 8103 hydrophone.See manufacturer’s website.
Calibration Radial sensitivity at two frequencies for each instrument when made.See manufacturer’s website.
Running time4-5 months on alkaline cells, or approx. 8 months + on lithium primary cells. The new rechargeable OD runs for 14 months when logging alternative minutesGenerally lower and limited by data storage requirements and batteries. Vary between devices. Part of minute only etc. from some systems. This is a major issue for some projects.
Servicing intervalDetermined by running time. Determined by running time or memory size.
RobustnessVery high. Individual hydrophones have withstood being thrown against rocks many hundreds of times and shown no measurable change in calibration! C-PODs returned for calibration after 10years of continuous use are generally close to the standard, but sensitivities show a weak tendency to rise with age.See manufacturer’s website.
Buoyancy Positive. This facilitates deployment and recovery, especially when moorings are interfered with or lost – over 100 recoveries have been made via the http://www.phonehome.org.uk/ website. See manufacturer’s website.

Software/analysis differences

FeatureF-PODWAV file recorder
Software FPOD.exe handles data from the F-POD. Displays filters, analyses and exports. Designed to support rapid accurate validation, with visualization options, editing tools, sampling point allocation, feature reporting etc.
Various: Raven, Pamguard, Ishmael, Audacity, Matlab, R etc.
Software cost Free, including all upgrades Various packages, some free.
Automated analysis speed1 day of data is usually analysed in 1 minute on a PCTypically slower
Analysis time Very low. Visual validation of a sample of data is required. If this passes, which is usual, the data can be used without further time costs.Very high. Visual checking of all detections is commonly needed.
Project supportFree data quality reporting. Design discussion/advice.See manufacturer's websites.
Empirical testingVarious papers have compared POD data with visual data. All have shown good agreement.See manufacturer's websites.

 

 

Comparing PODs to alternative instruments

Comparisons between different instruments are difficult because sensitivity can always be increased by accepting a greater rate or risk of false positives.

This outlines some of the issues and illustrates some of the errors made!

Updated: December 2022

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Comparing recording approaches by device type 

Clicks and recording approaches by device type.

Updated: December 2022

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