This study builds an automatic monitoring system for the fish pond culture environment. The purpose of this study is to reduce the financial losses in fish culture stock resulting from natural disasters, and facilitate better control of the fish pond environment. The physical water quality signals are therefore extracted using temperature, dissolved oxygen and pH sensing modules. The water heater, submerged motor pump, air pump, feeding trough and LED illuminating lamp are controlled to improve the water quality and reduce labor. This study utilizes the self-adaptive data fusion approach via a wireless sensors network framework to remotely monitor the fish pond automatic control system. The experimental results show that the fish pond culture environment can be accurately and stably monitored.