Abstract: Conventional extensive irrigation of paddy fields has posed a great challenge on crop growth, natural rainfall, and water resources. It is highly demanding for networked intelligent irrigation systems, with the increase in the area of paddy fields during agricultural modernization. However, the current irrigation system is still lacking in the deployment flexibility of underlying equipment, connectivity, and energy consumption of communication networks, as well as the intelligence decision-making of the whole system. Particularly, the energy consumption of equipment inevitably impacts the serving life of the equipment. In addition, the wired information transmission is used in most irrigation systems, where a large number of cables need to be erected. As such, great difficulties have been brought to the deployment and maintenance of equipment, due mainly to the complex environment in paddy fields. In this study, a precision irrigation strategy was proposed to fully utilize the natural precipitation using the sensor, embedded system, wireless networking, and artificial intelligence. Firstly, a networked precision irrigation system was designed for paddy fields using smart agricultural technology. Specifically, five modules were included: data collection node, irrigation control node, handheld control terminal, PC control terminal, and intelligent communication node. The wireless communication was used to flexibly deploy in the paddy fields with the solar power generation devices. Secondly, the fuzzy control was utilized to establish some of the models, including the most optimal deployment model of communication nodes, the most optimal irrigation decision-making model, a prediction model of crop water consumption and precipitation, as well as a decision-making system of precision irrigation. The design strategy was adopted in the decision-making system using the MATLAB+LABVIEW platform, in order to control the system by mutual cooperation. A new deployment model was proposed to optimize the deployment of communication nodes in the irrigation using the improved moth flame optimization and the Voronoi diagram, thereby improving the communication efficiency of the irrigation network, while reducing the energy consumption of communication. As such, the status and network meteorological parameters in the paddy fields were used as the input of the precision irrigation decision-making system. Finally, the irrigation equipment of the paddy field was adaptively controlled for precision irrigation after the decision-making of the system. Taking the rice fields in Jiangsu, China as an example, a field test was carried out to compare with the simulation. It was found that the intelligent irrigation system reduced the action frequency of irrigation equipment by 26.67%, while the irrigation volume of the system reduced by 40.82%, and the drainage volume reduced by 33.89%, compared with the traditional. Consequently, the operating life of the equipment was improved significantly, while the waste of water resources was reduced under the optimal growth water level of paddy field crops. The hardware and software parts of the system also performed well to meet the requirements of design indicators.