Freshwater Monitoring System Design In Real-Time For Fish Cultivation

Abstract

The increased demand for fish supply in aquaculture highlights the need for sophisticated and accurate monitoring systems to ensure optimal water quality. In this context, Internet of Things (IoT) technology and fuzzy logic have become promising solutions to improve efficiency and effectiveness in freshwater fish farming. This research aims to develop a real-time freshwater monitoring system that integrates IoT and fuzzy logic. This system will enable monitoring of critical parameters such as temperature, pH and water turbidity with a high degree of accuracy. Implementation of IoT sensors that are connected to one centralized network and use fuzzy logic to process the data obtained. The research also involved developing an intuitive user interface to manage the system. The developed system is able to provide real-time monitoring with a high level of accuracy. Users can easily access and analyze the generated data through the user interface provided. The design of monitoring freshwater conditions for intensive aquaculture can be prepared using pH sensor devices, turbidity sensors, and temperature sensors using ESP2866 modules to connect to IoT. From the results of 20 days of system trials, it was found that the system can determine the condition of fresh water with good readings with average level of accuracy for pH sensors of 97%, turbidity sensors of 92% and temperature sensors of 96%.