Self-Sustaining Fish Tank System Using Arduino Uno

In the field of aquaculture, numerous studies indicate that traditional fishkeeping faces significant challenges due to the manual maintenance required, leading to inefficiencies such as inconsistent cleaning, feeding, and water quality management, that can be improved by integrating automation and smart technologies. This experimental research, conducted in Metro Manila, Philippines, aims to test and refine the Self-sustaining Fish Tank System. By evaluating the accuracy and effectiveness of integrated sensors and automated components, the study seeks to enhance the system's performance in maintaining optimal aquatic conditions. An experimental research approach was employed, utilizing multiple methods including observation for data collection. Quantitative data analysis using descriptive and paired two-test statistical tools assessed the performance of the Self-sustaining Fish Tank System using Arduino Uno. The study's findings highlighted significant improvements in sensor reliability and consistency during operational tests with and without fish. Specifically, the water level sensor demonstrated enhanced responsiveness during pump activations, while the pH sensor stabilized effectively with fish present. The fish feeder consistently dispensed food every 12 hours, ensuring reliable feeding throughout the study periods. The study concludes that variations in sensor performance, particularly in pH and turbidity measurements, highlight the need for continued refinement to ensure consistent control across different environmental conditions. Future research should explore advanced sensor integration for improved accuracy and reliability, especially for critical parameters like water quality. Additionally, the adoption of IoT-based solutions with wireless modules is recommended for enhanced real-time monitoring and remote control via mobile apps or web interfaces.