r/Aquaculture

Hi all,

We are a US startup working on a small dissolved-oxygen monitoring and prediction system for aquaculture, and wanted to share it here.

It has a DO probe connected to a pond-side device, with an app/cloud dashboard. It supports WiFi or eSIM and can run on DC power or solar power. The main thing we’re testing is a machine learning model for 24-hour DO trend prediction. In our field testing, we saw around 0.35 mg/L average error overall, and around 0.45 mg/L during dawn periods, which are usually the tricky low-oxygen hours. The system also gives simple AI suggestions around aeration, feeding, and water exchange.

It’s still early, so I’d really appreciate feedback from people working with fish, shrimp, RAS, ponds, or aquaponics.

Feel free to comment or DM me. Happy to share more and learn from your setup.

I am looking to setup a 300 gallon freshwater prawn mini farm in my shed as a summer project. I think I have an aerator picked out but I am having trouble finding the exact specs for a water pump/filtration system. All the resources I am finding are inconsistent or don't show enough details for me to build something out.

Can anyone provide good resources/info for a freshwater prawn setup? again, it will be a 300 gal tank.

thanks

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Hi r/aquaculture community,

Im Alex,I have an Integrated Masters, graduate in Marine Biology (Ichthyology specialization)

from University of Thessaly, Greece, currently exploring career paths in

aquaculture with a data-driven focus.

A little bit about myslef, I currently work as Quality Assurance in a Seafood Factory processing plant for nearly 3 years. I have taken certified courses in Python, R, ISO 22000 and finishing Biostatics and currently learning SQL.

To be honest, I'm at a crossroads.

I started in QC because I wanted to start from somewhere. And I learned A LOT -

regulations, safety protocols, how a factory actually runs. But after

3 years, I realized I was doing the same tasks on repeat. No growth,

no real problem-solving.

So about a year ago, I started teaching myself data skills - Python,

R, SQL. Not because it was trendy, but because I noticed something:

all the QC data we collected was just... sitting there. Nobody was

analyzing it. And I thought, "What if someone could actually USE this

data to improve farming?"

That's when it clicked. I don't want to leave aquaculture. I want to

approach it differently.

**The reality check:**

I'm not a "pure" data scientist. I'll never be as good at machine

learning as someone who studied CS from day one. But I have something

they don't: I actually understand aquaculture. I know what fish

farmers care about. I've seen the problems from the inside.

So here's where I'm stuck:

1. **Imposter syndrome is real** - When I see job descriptions asking

   for "5 years Python + advanced SQL + Tableau," I wonder if I'm

   wasting my time. Am I competitive enough?

2. **The fish-or-fowl problem** - I'm not a "true" biologist anymore,

   but not a "true" data scientist either. Companies want one or the

   other. Do they value the hybrid?

3. **Geographic reality** - I'm in Greece. The aquaculture data jobs

   are in Norway/Nordic countries. Is it worth relocating? Or am I

   better off pivoting to general data roles and losing my domain expertise?

4. **Path confusion** - Should I:

   - Apply for junior analyst roles in aquaculture (even if I'm under-qualified)?

   - Take a generic data analyst job to build stronger technical skills first?

   - Build a portfolio project to prove I can actually DO this?

   - Go all-in on certifications (AWS, Tableau, etc.)?

**What I AM looking for:**

- Real talk from people in the industry

- "Here's what actually worked for me when I was in your shoes"

- "Here's where you're being unrealistic"

- Honest takes on whether this transition is viable or if I'm chasing a dead end

Has anyone here done a similar transition? Marine background → data role?

What was the actual experience vs. what you expected?

Thanks for reading. Genuinely appreciate any insights.

—Alex