Abstract: Abstract: Aquaculture plays a vital role in our social and economic life, but its long production cycle, high labor intensity, low production efficiency, large waste of resources, and severe susceptibility to disease, significantly restrict the healthy development of the aquaculture industry. Facing a growing consumer market, traditional farming methods are increasingly unable to meet the demands of the public, creating great uncertainty in this crucial industry. This paper aims to develop a holistic management system for the crab farming, by combining technologies such as internet of things (according to the three-layer architecture of service layer, application layer and executive layer) and big data to systematically monitor and control aspects across the entire system. The system mainly includes the following aspects: 1) Aquaculture center water quality and environment sensor network: A distributed sensor network is required for continuous and real-time monitoring of key water quality parameters (including dissolved oxygen, pH value, and temperature), and such a system would be arranged within the water, together with underwater cameras, to provide a constant stream of data for processing. Additionally, information from a second network of local meteorological sensors (such as temperature, humidity, wind direction, wind speed, barometric pressure, rainfall and illumination) will be gathered, and when combined with the underwater data, a complete data monitoring network will be formed based on the internet of things technology. 2) Intelligent control network of farming center: Aquaculture equipment mainly includes aerators, feeders, and so on, with management approaches to these being low-tech, not optimized and wasteful currently. Through real-time analysis of water quality data, the growth cycle of aquatic crops, and their active morphological data can be fed into a learning model, which will determine the optimum oxygen content at any given moment and allow real-time precise control of the aerator. Furthermore, predicting the hunger time of the aquatic species will enable accurate feeding regimes, greatly avoiding wastage of precious resources and improving production efficiency. Users can remotely browse data in any place with network coverage through a computer browser or mobile phone App. The server of the entire system is hosted at the Shanghai Ocean University's network management center, deployed on the server website, mobile phone App service background, and so on. The system adopts embedded single-chip microcomputer (STC15F2K60S2) as the bottom layer controller chip, and communicates with the sensor by RS485 protocol. Each subsystem network uses ESP8266 WIFI module to connect AP(access point) station and the video surveillance uses EZVIZ cloud platform. PLC (programmable logic controller) is the control part for the aquaculture equipment. The system has passed the actual debugging in the Chongming crab breeding base, which belongs to Shanghai Ocean University, and all the indicators meet the requirements. The accuracy of each parameter reaches the detection standard. Up to now, the system is stable in operation and can meet the requirements of aquaculture. By testing, the communication success rate of the whole system is more than 98%, and the average relative errors of dissolved oxygen, temperature and pH value are ±0.016 mg/L, ±0.031 ℃, and ±0.023, respectively. It is worth promoting the application. This system can provide guarantees to promote the growth and sustainability of this key industry, in addition to brand building of aquaculture and the rapid transformation and upgrading of the industry. As a demonstration of modern aquaculture, especially in the fields of industrialized aquaculture, seedling raising and cage culture, the system can provide scientific guidance on the production and management of aquaculture for the farmers. At the same time it will be good for the construction of the big data platform of the whole industry chain.