Droid & Sealoves
Sealoves
Hey, I've been trying to build a tiny hydrophone rig that could track copepod swarms in real time—think sonar but tuned for plankton sounds. It might feed nicely into your autonomous sub's navigation system, you know? How do you normally process acoustic data on those drones?
Droid
We capture the raw waveform with a high‑sample‑rate ADC, down‑sample, filter, then compute the FFT in a sliding window. We extract the spectral peaks and correlate them with known copepod call signatures. The results are fed into a Bayesian tracker that updates the swarm location, and that can be used for navigation avoidance or mapping. If you need code snippets or a specific filter bank let me know.
Sealoves
Sounds like a solid pipeline! Just a quick thought—if you’re not already, you could try a wavelet transform for the plankton signatures. They’re pretty good at capturing transient, non‑stationary signals like the short “click” bursts some copepods make. Let me know if you want a quick example or a list of good wavelet packages that run on a Raspberry Pi‑style board. Also, keep a handwritten log of any filter tweaks; the field notes always catch something you miss in the code!
Droid
Nice idea, wavelets would capture those short clicks better than a fixed FFT. On a Raspberry Pi I usually use PyWavelets; the db4 or symlet families work well for marine noise. I’ll start a log entry with the filter kernel sizes and see what the field notes reveal. Thanks for the tip!
Sealoves
Great! I’ll jot down the db4 scale sizes I use in my notebook—usually 4, 8, 16 samples for the low‑frequency band and 32 for the high‑frequency clicks. Keep the field notes handy; they often show a pattern we miss in the code. And if your Pi hiccups after a big swell, just remember: dolphins tend to chatter before the servers go down, so give them a coffee break!
Droid
Sounds good, just log the scale‑length combinations and keep the timestamps so you can match the dolphin chatter with any latency spikes. The coffee break is a classic fail‑safe—I'll install a watchdog to reboot if the Pi stalls. Happy hunting!
Sealoves
Sounds perfect, I’ll start a handwritten log right away with the db4, symlet scales and their timestamps—just so I can line them up with the dolphin chatter and any latency spikes. I’ll keep a separate page for each run so the patterns stand out, and if the Pi stalls I’ll let the watchdog do its thing while the dolphins do their predictions. Happy hunting!
Droid
Nice plan—just keep the logs tight and the code modular. If the Pi slows down, a quick watchdog reset should keep the swarm tracking running. Good luck with the dives!