| China’s aquaculture production ranks first in the world,of which traditional pond culture accounts for a large proportion.However,in recent years,traditional pond aquaculture has gradually exposed many problems such as low productivity,serious environmental pollution,and excessive reliance on the human experience.With the promulgation of policies such as the banning on fishing in the Yangtze River,the traditional pond aquaculture industry is facing with greater crisis,thus leading to more urgent needs for transformation and upgrading.Captive breeding is a new type of aquaculture mode,which has a variety of advantages including low requirements for regional environment,wide adaptability,and significantly saving water resources,reducing labor costs,increasing production notably,large energy consumption reduction space,and broad development space.However,the current degree of automation and mechanization of the captive breeding model is still low,which limits the mass promotion and application to a certain extent.In this work,the captive ponds were taken as the research object,and an automatic control system was designed for the key links and bottlenecks in aquaculture to achieve real-time collection of water quality data,water quality status control,product feeding,oxygen supply,and pollution removal.The main contents of the paper are listed as follows:(1)The overall structure and scheme design of the automatic management and control system were finished.Based on the demand analysis of the aquaculture management and control platform,the overall structure of the captive automatic management and control system was designed,including the main control module,water quality monitoring module,feeding module,oxygen supply module,cleaning module,video monitoring,and communication modules,etc.The system had a variety of information transmission methods,and could realize aquaculture management and control through a touch screen,mobile phone APP,and other means.(2)The investigation of aquaculture water quality data preprocessing,correlation analysis,and water quality prediction was finished.Aiming at problems such as abnormal data and noise of water quality sensors,the wavelet filtering algorithm was selected to filter water quality data.Based on the measured multi-source sensor data,correlation analysis was carried out to determine the degree of correlation between various water quality parameters.In order to reduce the impact of dissolved oxygen sensor failure on aquaculture,an artificial neural network method was used to establish a dissolved oxygen water quality prediction model,based on the strong correlation between dissolved oxygen and temperature,p H,and turbidity.(3)The design and implementation of aquaculture management and control software.The management and control software such as captive pond lower computer software,an Android studio IDE based mobile APP and touch screen software were designed to monitor water quality and conduct system control.On the basis of the above software,real-time collection of information in captive ponds,timing/conditiontriggered aquaculture management and control can be realized,and captive pond system information can be synchronized on multiple local and remote devices,meanwhile the instructions can be issued remotely or locally.At last,the experiments showed that the system was suitable and efficient for captive pond. |
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