In the new process of fishery development in Taiwan, the threshold of fish culture technology needs to be broken so that there are new prospects for fishery culture.

Taiwan has entered an aging society in 105 years. Under the addition and multiplication effect of fewer children, the problem of shortage of agricultural labor force is imminent. Therefore, in 106, the Council of Agriculture actively promoted smart agriculture 4.0, hoping that through the innovation of wireless communications and sensors, farmers can also face the management challenges brought about by climate change with limited manpower. The aquaculture laboratory team recently combined with the Lightspot team to demonstrate the research and development results, including: indoor facility culture system, marine vibrio detection system, and UAV water quality monitoring vehicle to exchange new ideas and technologies with the aquaculture industry.

Zeng Zhende, secretary to the director of the Water Test Institute, said that apart from facing population problems, the traditional aquaculture industry also faces the risk of fish diseases and drug use caused by climate change in most open-air farming environments in the country. therefore, we hope to use the technology of big data, artificial intelligence, and the "big shot" of the Internet of things to help fishermen implement effective and accurate production patterns under limited land and water resources.

Wang Yujun, an assistant researcher in the Planning Information Group of the Water Test Institute, explained the development achievements of the Water Test Institute in the past three years: the Internet of things system for intelligent grouper culture, the marine vibrio detection system, and the UAV water quality monitoring vehicle. Among them, in the Internet of things system for intelligent grouper culture, the Water Test Institute has set up an indoor grouper culture model factory in Qigu, and set up water quality monitoring equipment in the culture pond. The system will start aerating equipment and sunshade net for specific information, and immediately respond to the situation in the pond. At the same time, through the underwater image identification system to record the activity status of the fish and control the feeding frequency of the feeding machine, when it is found that the fish are no longer active because of the dispersion of the bait, that is, to judge that the bait is sufficient and stop supplying, in order to effectively control the cost of bait and reduce water pollution. The relevant data will eventually return to the "aquaculture decision visualization subsystem". Managers can grasp the information about the operation of fishing conditions or equipment in the pond through the monitoring platform, so they do not have to go to the fish pond to make culture decisions with the help of the Internet of things.

However, Zeng Zhende also said frankly that although it is convenient for science and technology to assist decision-making, there is still a long way to go to promote the concept and implement machine decision-making in practice, because older farmers rely on personal experience and have a conservative attitude towards new technology and technology, so the Water Test Institute will try to handle more technology and explain that it will be promoted to young farmers. In addition, machine decision-making involves data collection, interpretation, and writing parameters before the machine can execute them effectively. To judge and read useful data and establish a parameter system is the key to the development of the "big shot" technology. Therefore, the data collected by the water test station in the grouper culture area and the established parameter system will also be open to farmers for reference in the future, so that the data can play a role.

All the data will be integrated into the management interface, and the manager can clearly grasp the facility and biological data in the field at a glance for remote control. (photo / Water Laboratory)

Automatic detection system of marine vibrio. (photo / photo taken by reporter Chen Yan and Yin)