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This study builds an automatic monitoring system for the fish pond culture environment. The purpose of this study is to reduce culture costs, including those resulting from labor costs and natural disasters, and make it easier for culturists to manage their fish ponds. With the proposed system, physical indicators of water quality are extracted by temperature, dissolved oxygen, and pH sensing modules; the heater, submerged motor pump, air pump, feeding trough, and LED illuminating lamp are controlled to improve the water quality and reduce labor. The wireless sensor network (WSN) is used as the signal transmission architecture between the sensor nodes, the control nodes, and the computer, where the human–machine interface is used for display, recording, and operation. In order to make the system more efficient and accurate, the fuzzy theory is used for fuzzy inference of the sensed signal, which enables the controlled load to be optimized and combined with the WSN so that the real-time information of the fishponds can be made available to culturists through mobile devices or remote platforms. The grid and storage battery are used as an uninterruptible power supply (UPS) to alternately power the sensors. The experimental results show that the fish pond culture environment can be accurately and stably monitored. The proposed monitoring system is constructed using a network of sensors, and it achieves precise judgment and real-time control. Based on the current situation, the system instantly turns on the hardware device to change the environment as needed.

Employing a Fuzzy Approach for Monitoring Fish Pond Culture Environment