Research On Pelagic Fishing Decision Making Support System Based On Internet Of Things

The pelagic fishing decision making support system based on the Internet of things is of great significance to significantly enhance the unified management of pelagic fishing fleets,to improve the fishing efficiency of pelagic fishing vessels,and provide information services for the pelagic fishery.This study aiming at the two key link of decision support about optimization of fishing forecast accuracy and scheduling pelagic fishing vessels in pelagic fishing operation.Analyzes existing problems of pelagic fishery industry in the current status through multi-source data fusion technology to improve the resolution and availability of large-scale marine environmental data.To conduct the thorough research to the fleet scheduling model.Established the pelagic fishing decision support system based on Internet of things.The development and design of the pelagic fishing decision making support system based on the Internet of things are completed and the main functions are realized,to provide decision support service for ocean fishing practices by the separate and superimposed display of different data layers finally.Reduce the operation cost and for increasing the income of fishermen also enriched the residents' demand for aquatic products.The main work of this paper is as follows:(1)A marine environment data acquisition system by solar tracking photovoltaic marine environment monitoring buoy based on STM32 was designed.According to the actual needs of decision making support system for data and the actual working environment of the buoy carriers function for the specific design,including the special sensor,designed to maintain a long-endurance photovoltaic power supply system,etc.In addition,the network optimization for ocean buoy cloth be discussed,to reduce the buoy cloth redundancy,and improve the efficiency of data link transmission.(2)Introduced a marine environmental data combining method from different sources by using SCM to improve the resolution of large-scale data.Introduces a kind of the marine environmental monitoring electricity buoys point data into the satellite remote sensing method of Marine environmental data for ocean buoy ocean waters site sparse and the characteristics of low resolution satellite remote sensing to the marine environment data.To improve the resolution of the large-scale remote sensing data.Used the relationship between environmental factors and spatial distribution of fisheries to optimize the accuracy of fishing forecast model finally.(3)A scheduling optimization model of ocean fishing fleet based on the Internet of things was proposed.The scheduling optimization of the voyage route of the ocean fishing fleet is finally realized by comprehensively considering the task index,operation target,fleet resource allocation and other decision-making factors of the fleet.So improves the fishing efficiency of the whole fleet and reduces the transportation cost and increasing the economic benefits.