Inventing the Shrimp Seasoning Grinder
Transforming Seafood By-Products into Vietnam’s Favorite Seasoning

Aquaculture has long been a backbone of Vietnam’s seafood industry, but for shrimp farmers in Nam Dinh province, water quality fluctuations remained an unpredictable and costly challenge. Many farmers faced sudden mass shrimp deaths due to poor water conditions, often caused by low oxygen levels, extreme pH fluctuations, or increased salinity.

 

Traditional water monitoring methods required manual testing, which was time-consuming, reactive rather than preventive, and often inaccurate. Witnessing this inefficiency firsthand, I set out to build Aqua Track, an intelligent real-time water monitoring device that would measure critical water parameters, predict future fluctuations, and provide farmers with instant access to data online.

 

Phase 1: Developing the Real-Time Monitoring System

The core idea behind Aqua Track was to continuously track and analyze key water parameters, including:

• 🫧 Dissolved Oxygen (DO) – Essential for shrimp survival

• 🌡 pH Levels – Fluctuations can stress or kill shrimp

• 🧂 Salinity – Must remain within an optimal range

• 🌫 Turbidity – High levels indicate poor water quality

• ⚡ Total Dissolved Solids (TDS) – Affect shrimp metabolism

I developed a sensor network that could collect real-time data, process it, and transmit it to an online dashboard where farmers could monitor their ponds from any device. Instead of relying on outdated manual water testing, farmers could now receive instant alerts when conditions became unsafe.

 

Phase 2: Integrating AI for Predictive Monitoring

Real-time monitoring was an improvement, but I wanted to take Aqua Track a step further, not just detecting problems, but predicting them.

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To achieve this, I designed and integrated sensor signal processing circuits with an LSTM-based (Long Short-Term Memory) machine learning algorithm. This AI model analyzed past and real-time data to forecast potential risks, such as oxygen depletion or dangerous pH drops, allowing farmers to take action before problems escalated.

🔹 Example Scenario: If oxygen levels dropped at a rate that could lead to hypoxia in six hours, Aqua Track would send an automatic alert, advising farmers to activate aerators before shrimp were harmed.

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Phase 3: Field Testing in Nam Dinh Shrimp Farms

After months of development, I deployed Aqua Track prototypes in multiple shrimp farms in Nam Dinh, a province known for its aquaculture industry.

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The results were astounding:
✔️ 90% Accuracy in predicting harmful water conditions
✔️ 75% Reduction in Shrimp Mortality Rate as farmers were able to respond proactively to water quality issues
✔️ Significant Increase in Yield & Profitability, as healthier shrimp meant better growth rates and fewer losses

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Impact: A Smarter Future for Aquaculture

With Aqua Track, shrimp farming was no longer a guessing game. Farmers now had:
✅ Real-time insights into water conditions
✅ Predictive alerts to prevent mass losses
✅ A sustainable, data-driven approach to aquaculture management

 

What started as a simple idea to improve shrimp farm efficiency became a technological breakthrough that reshaped water quality monitoring. With Aqua Track, aquaculture entered a new era of precision, sustainability, and profitability, one data point at a time.