Design And Implementation Of Internet Of Things System For Aquatic Product Breeding Supervision

With the rapid development of China’s economy,people’s living standards have greatly improved,people’s attention to food safety is also increasing.Ensuring food safety involves many aspects,one of which is quality supervision.Different foods have different requirements for quality supervision.For aquatic products,their characteristics include sensitivity to water quality,star shaped distribution of aquaculture bases and ponds,and the general need for nationwide aquaculture regulation.These characteristics make aquatic product regulation have specific requirements for the Internet of Things.Firstly,it requires low cost,real-time performance,and high efficiency.Secondly,it requires the prediction function of core water quality indicators.Thirdly,it requires the design of a large-scale regulatory network.Although there are currently some Internet of Things related to food regulation,there are relatively few networks that can meet the requirements of aquatic product regulation,which poses a constraint on high-quality aquatic product regulation.In response to the above issues,this paper designs and implements an Internet of Things system for the supervision of aquatic product aquaculture,mainly focusing on water quality supervision of aquatic products.The main work of the paper includes the following two aspects:1.Network design and implementation of the Internet of Things system for aquaculture supervision.Firstly,in response to the needs of national aquaculture base supervision,a national aquaculture base supervision system networking scheme based on the future network architecture was proposed,and its connectivity and data transmission rate were tested.The test results show that the network performance of this networking solution meets the needs of nationwide transmission and real-time monitoring of regulatory data.Secondly,in response to the star shaped distribution and distant distance of aquaculture ponds in aquaculture bases,a LoRa based IoT for aquaculture base supervision was designed,which achieved the collection,uploading,and real-time monitoring of the four core indicators of water quality in aquaculture bases:temperature,pH value,oxygen dissolved concentration,and turbidity.2.Design and implementation of the Internet of Things system software for aquaculture supervision.Firstly,a new water quality prediction algorithm is proposed to meet the regulatory requirements for aquatic product quality.The food quality of aquatic products highly depends on water quality,and accurate prediction of water quality is the first important function of aquatic product monitoring.This paper conducts research on oxygen dissolution concentration and turbidity,and designs a prediction model algorithm based on improved tuna algorithm and optimized BP neural network.The proposed algorithm mainly optimizes the weight factor and individual optimal position calculation of the tuna algorithm,improving prediction accuracy and achieving accurate prediction of oxygen dissolved concentration and turbidity.Secondly,a breeding supervision platform was designed to meet the visualization and presentation requirements of the regulatory system.Through experimental verification and performance analysis,a series of functions such as real-time monitoring,indicator prediction,and data management have been effectively implemented,effectively verifying the main functions of the regulatory platform in the Internet of Things system for aquaculture supervision.