In 2008, I completed a project called "Abundance estimate techniques for conch" as part of a Masters degree in Environmental Biology. This project investigated the techniques used by the Department of Environment (DoE) in the Cayman Islands to estimate the population density of queen conch (Strombus gigs) in the 30 square km of shallow sounds around Grand Cayman, Cayman Brac and Little Cayman. These methods are described at http://doe.ky/marine/conch/conch-survey/, where the number of conch are counted in 24 square meter quadrats in different sites around the islands. It is currently estimated that 860 sites, or 0.02 square km, are surveyed each year. To be frank, my Masters thesis didn't prove an awful lot apart from the uncertainties in the DoE's current conch population estimates are very large because of the relatively small area sampled, but the project has stayed with me.
The main problem with the current DoE method is that it takes around 20 minutes to measure a single 24 square metre quadrat, this means it takes 286 hours, or 35 working days, to measure 860 sites. Posit, emerging technologies can be used to increase the rate of sampling. If a camera can move around the region taking photographs or video, image recognition software can be used to estimate the conch density. The first iteration of this project aims to take photographs of the seabed every 10 seconds, this well greatly increase the number of quadrats sampled to around 12,000 in 35 working hours. Arduino modules are a low-cost, low-power platform that can be used to collect data while Raspberry Pi technology uses more refined methods to analyse and store data, both these systems will be used in this project.