Abstract
Recirculating Aquaculture Systems (RAS) represent a high-density, controlled-environment fish farming method that requires constant monitoring of critical water quality parameters to ensure high water quality and fish stock health. Manual monitoring is labor-intensive and prone to error, creating a significant risk of catastrophic loss. This work presents the design and implementation of an automated monitoring system built on a Raspberry Pi platform that integrates multiple sensors (temperature, pH, conductivity, water level, and pumps' functionality) to provide continuous, real-time data acquisition. A key feature is a software-based outlier rejection algorithm that enhances data integrity, and the code is freely available on the GitHub platform for further development. The collected data has been published on the ThingsBoard IoT platform for visualization and historical analysis via the HTTPS protocol. Furthermore, the system implements a proactive alerting mechanism using the Pushover notification service to deliver instant mobile alerts when parameters deviate from predefined thresholds. Commercial solutions cost in the order of thousands of euros, have high maintenance and operational costs, and pose integration and compatibility challenges. This solution provides a reliable, scalable, and cost-effective method for maintaining optimal conditions in a RAS, with hardware costs of less than EUR 150.