Farm-level water quality is a critical determinant of performance and survival in shrimp production systems. This study presents a low-cost, open-source hardware monitoring platform integrated with a fuzzy‐logic Water Quality Index (WQI) to provide real-time, actionable insights for producers of Litopenaeus vannamei. The system uses commercially-available sensors for dissolved oxygen (DO), temperature, and pH, linked to an Arduino-based platform and customized fuzzy‐inference engine to compute a WQI that translates raw sensor data into a single management indicator.
Deployment in three production tanks over a 90-day grow-out revealed that the WQI successfully identified early declines in DO and temperature stability that preceded observable shrimp stress and growth reductions. Compared to conventional periodic manual sampling, the system captured fluctuations hourly, alerting farm staff to sub-optimal conditions (e.g., DO falling below 4 mg/L, temperature drift > 1 °C/h) and enabling timely corrective actions (e.g., aeration adjustment, partial water exchange). Results indicated a 12 % improvement in final average shrimp weight and a 7 % reduction in mortality relative to baseline ponds without real-time monitoring.
From a cost-efficiency perspective, the open-source system was built for under US $1,200 per pond (hardware and installation) — significantly less than many commercial water-quality monitoring solutions — making it practical for small to mid-scale farms. The fuzzy logic WQI framework enhances interpretability for non-technical farm staff and supports scalable expansion to additional parameters (e.g., turbidity, ammonia, nitrate) and species.
This approach aligns with the trends of precision aquaculture and automation in farming practices and offers a scalable pathway for integrating smart monitoring in pond and recirculating-systems operations. For producers, this technology delivers an affordable decision-support tool to improve yield, reduce risk, and promote sustainability in shrimp aquaculture.
Keywords: Shrimp farming, water quality monitoring, open-source sensors, fuzzy logic, precision aquaculture