Design Of Remote Monitoring System For Unmanned Bait Ship Based On Cloud Platform

The current stage of crab aquaculture in China is based on artificial fixed-point feeding.The amount of feed and the nutritional structure of the feed are determined by the farmers’ years of breeding experience.There are problems such as high labor costs and low feeding accuracy.In order to improve the automation level and bait utilization rate of river crab farming,this paper designs a remote monitoring system for unmanned bait ships based on cloud platform under the support of the research funding of Jiangsu Modern Agriculture Planning Project and Jiangsu Marine Fishery Science and Technology Innovation Project.The system can monitor and control the operation of unmanned bait ships in real time,and use expert system technology to reason about scientific feed feeding amount and feeding suggestions,which improves the breeding efficiency.The remote monitoring system for unmanned bait ship based on cloud platform mainly includes unmanned bait ship onboard terminal,cloud server and monitoring client.The shipboard terminal collects the working condition information and positioning information of the unmanned bait ship,and uploads it to the cloud server through the GPRS network;the cloud server transmits data to the bait ship and the monitoring client through the network to realize cloud processing and cloud computing and cloud storage;the monitoring client provides real-time data display,historical data query and data analysis on the operating parameters of the unmanned bait ship;in addition,the cloud server infers and calculates the appropriate bait feed based on the river crab breeding information sent by the monitoring client Feeding volume and feeding recommendations.The main research contents of the paper are as follows:1.Analyzed the research status of the unmanned operation ship,cloud platform technology and remote monitoring system,analyzed the functional requirements of the unmanned bait ship monitoring system,designed the overall design scheme based on the cloud platform monitoring system,and introduced the components of the system And the working principle,the key technologies and principles involved in the system are explained in detail.2.A river crab breeding expert system is designed,which is mainly used for feeding crab crab feed.According to the river crab breeding information and environmental parameters provided by the monitoring client,combined with the knowledge in the knowledge base of the expert system,the formula of the bait,the feeding recommendations and the feeding amount are inferred by means of forward reasoning.A BP neural network model was designed to calculate the feeding amount in combination with the growth weight and feeding rate of the crab.The neural network takes the water temperature,acidity and alkalinity and dissolved oxygen parameters of the aquaculture waters as input,and the influence coefficient of environmental parameters on the feeding amount as the output,to achieve scientific feeding.3.Under the cloud platform,complete the development of the server and database.Design the database table structure to complete the cloud storage of data.The server is developed with multi-thread technology and completes the data communication with the bait boat and the monitoring client according to the custom communication protocol to ensure the reliability of the communication.The unmanned bait ship’s onboard terminal is designed with hardware and software to realize the data collection,processing and interaction of the onboard terminal.According to the analysis of the functional requirements of the monitoring client,the data management,remote control,data communication and human-computer interaction interface of the monitoring client are designed separately.4.Under the condition that the hardware function module is guaranteed to meet the system requirements,the entire monitoring system is jointly debugged,and the remote monitoring effect of the PC monitoring client on the unmanned bait ship is emphasized.The test results show that the system can monitor and manage the unmanned bait ship in real time and effectively to achieve the expected goal.