Design And Implementation Of Intelligent Ship Monitoring System Based On LoRa

With the application of the Internet of Things,cloud computing,and information technology in intelligent scenarios,ship intelligence has become a new focus of attention from all walks of life in the world.Ship intelligence aims to realize the interconnection of everything in the “mobile city on the sea” and is a new development in the digital development of ships in the future.Trend,has huge development potential.The ship monitoring system belongs to the core category of smart ships and is the foundation of ship digitization and intelligence.Because traditional ship monitoring systems have problems such as coverage blind spots,high power consumption,high cost and difficulty in deployment,they cannot meet the requirements of ship intelligence development..This subject introduces LoRa(Long Range)technology to the monitoring of intelligent ship equipment,and conducts research around the design and implementation of LoRa technology and intelligent ship monitoring system,and conducts detailed research on the overall framework of the system and the deployment of LoRa gateways.The ship monitoring system is implemented in hardware.Finally,the stability and reliability of the system and algorithm are verified through design experiments.The main research contents are as follows:First,complete the overall scheme design of the ship monitoring system.In response to the needs of intelligent ship monitoring,through analyzing the communication principle of LoRa technology,the composition of the ship monitoring system is introduced as a whole.The system is divided into three parts: parameter perception layer,gateway transmission layer and cloud server layer.Among them,the parameter perception layer is responsible for collecting ship environment and equipment status information;the gateway transmission layer is responsible for forwarding and downlink data;the cloud server layer is responsible for processing sensor data.Second,design and implement LoRa-based wireless communication hardware modules.The hardware framework is introduced.The main control module of the terminal node and the gateway device uses the STM32 series processing chip,the LoRa RF module of the terminal node uses the SX1262 RF chip,and the LoRa module of the gateway device uses the baseband processing chip SX1302 and the RF front-end chip SX1250.At the same time,complete system schematic design,PCB design and physical plate making.Third,in view of the difficulty of LoRa network gateway deployment,a particle swarm-based LoRa gateway deployment optimization algorithm is proposed.The algorithm takes the energy loss rate of the entire network to establish a mathematical model,transforms the deployment problem into a problem of finding the extreme value of energy loss,and uses a particle swarm algorithm to solve the gateway deployment location.The simulation results show that the algorithm used in this paper has low computational complexity and fast convergence,which can solve the deployment problem of LoRa network gateway in ship monitoring.Fourth,complete the software design of the monitoring system.The system software design includes detailed procedures for two-way communication between terminals,gateways,and cloud platforms,and defines LoRa network communication protocols,including uplink and downlink communication data structures.At the same time,LoRa terminal initialization,data transmission and reception,network access process design,gateway software design and The software design process of the cloud platform.Finally,a LoRa monitoring system was built by simulating the ship environment,and the system function and gateway deployment algorithm were verified.First,simulate the ship environment to test the performance of the LoRa hardware module,and all indicators meet the expected goals;then build the system for function and integration tests,the test results show that the system has the expected functions;finally test the performance of the LoRa network to verify the algorithm performance,and the results show that the gateway The optimization algorithm is flexible and reliable.