Design Of Intelligent Navigation System Based On 5G Technology For Parking And Car Finding In The Chemical Parking Lot

With the development of my country’s industrial production and social economy,the road transportation of hazardous chemicals is increasing,and the dangerous goods vehicles in the factory area are dense.If there is no matching parking guidance system,the driver will park the dangerous goods vehicles on both sides of the road in the factory because of the small space in the factory,the difficulty of turning around,and the inability to accurately understand the parking situation in the factory.It is easy to cause accidents such as collisions and rollovers,and there are serious safety hazards.In view of the current situation of difficult parking in the chemical plant area,this paper designs an intelligent navigation system for parking and searching for a car in the parking lot of the chemical plant area based on 5G technology.The system uses ultrasonic sensors to detect parking space information,and the local Lo Ra network 5G transparently transmits the parking space information to the Alibaba Cloud Io T platform.The AMQP protocol is used as the communication bridge between the Io T platform and the server.Spring Boot and Maven build the server program,and the MUI framework builds the client program,which realizes the offsite induction of the parking lot and the car-finding navigation in the field.Aiming at the problem of effective berth information prediction in the parking process,a berth prediction method based on sparrow optimization neural network is proposed.Combined with wavelet decomposition,the time series is decomposed and reconstructed,and the weights and thresholds of BP are continuously adjusted by the sparrow algorithm.Overcoming local optima and introducing a dynamic fuzzy learning strategy improves the quality of the solution.The validity of the proposed algorithm is verified by using the historical data of a parking lot.The average absolute error and root mean square error of the algorithm are 6.2230 and 4.6295,respectively,and the accuracy is better than other intelligent optimization models,which can effectively predict the remaining parking spaces.In view of the lack of on-site navigation in the parking lot,taking into account the computing power of mobile phones,Dijkstra is selected as the basic algorithm for the research,and the storage structure,search direction and search range of the Dijkstra algorithm are optimized in combination with the actual parking situation in the chemical plant area.Under the condition of ensuring the optimal path,the running time of the algorithm is reduced.Finally,based on the hardware of the system terminal equipment,the overall test of the intelligent navigation system designed in this paper is carried out,and the function of the intelligent navigation system is verified to meet the expected design requirements,thus completing the overall system design.