Research On Data Warning And Blind Zone Data Processing Method Based On RFID

The Internet of Things is a "connected device" for connecting and reporting real-world information.It is connected to the network through sensors to record the behavioral services provided by things at any time and any place,and can be used for interpretation,analysis and Data used.As one of the basic applications in the field of Internet of Things,mobile material tracking and monitoring is widely used in intelligent transportation,smart cities,smart earth and other fields.With the rapid increase in demand for material monitoring and material tracking services,many applications require accurate identification of materials,monitoring of material behavior,traditional video surveillance,and GPS positioning.Due to the large amount of raw data,directly processing the collected raw data wastes a lot of system overhead.And it does not effectively identify the monitored object in multi-area monitoring with dead zones.In recent years,all kinds of Internet of Things technologies represented by RFID have entered the researcher's sight because of the advantages of low equipment cost,wide recognition range,non-contact,and high recognition rate.This paper takes the common characteristics of mobile media moving between multiple regions as the entry point,studies data cleaning and data reasoning methods in multi-region monitoring,designs multi-region data early warning mechanism,and designs data reasoning method in this mechanism to obtain monitoring status of mobile media.By adjusting the early warning threshold,the false alarm rate in the presence of blind spots is reduced.The main work of this paper is as follows:(1)According to the characteristics of mobile media in multi-area monitoring,improve the RFID data model,build an event-centric state machine model based on the data model,and introduce the system architecture and system data processing architecture under this model.(2)Combining the stream characteristics of RFID data collection,data is cleaned up on redundant data and missing data in the original data,and effective data is obtained to provide services for the application system.According to the perceptual state of the mobile medium,including the constraint relationship,the effective early warning data is inferred,and the data alert reasoning algorithm is designed by the finite state machine.The experiment was then designed to verify the stability and safety of the system.The experimental results show that the data early warning algorithm can effectively infer the monitoring status of the mobile medium.(3)Based on the problem that the mobile medium has blind spots in the region,the probabilistic processing method is introduced,and the blind area data warning method based on the adaptive window is constructed.By adjusting the warning threshold of the mobile medium,the invalid warning is filtered to obtain reasonable and effective.Monitoring data,and designing experiments to verify the effectiveness and rationality of the blind zone data warning algorithm.