  Various studies have been developed to monitor the gaping behavior of
bivalves (oysters) in response to environmental factors. This work aims to
fully automate oyster spawning detection in real-time by building on previous
efforts. The sensor system developed at Jackson State University, Mississippi,
employs the Hall effect phenomenon to accurately measure the gaping of bivalves
accurately. The system uses a Hall effect sensor and a small magnet glued
outside the bivalve shells. The Hall effect sensor reports the magnet distance,
and hence the gape at a rate of 10 Hz, which the user may change. The data
generated is stored on an SD card and supplied to a microcontroller for
transmission to our file server on the Internet. The collected time series data
is transformed to the frequency domain in 10-minute chunks using the fast
Fourier transform (FFT) algorithm. When the data is analyzed in the frequency
domain, the spectral power in the frequency range of 0.3 Hz to 1.3 Hz spikes
several orders of magnitude when spawning occurs. It is then concluded that
using a threshold of 0.1 dB in the frequency range of 0.3 Hz to 1.3 Hz, and
spawning could be predicted 100% of the time.
