Research On Target Monitoring System Based On Passive RFID

People's yearning for creating a smart living environment has led to the rapid development of the Internet of Things(Io T)technology.Io T technology has successfully promoted the intelligence of many traditional products and industries.Among many emerging applications,context-aware applications such as activity recognition,identity recognition and quantity recognition have attracted more and more researchers' attention.Typical context-aware technologies mainly include: sensorbased context-aware technology,Wi Fi-based context-aware technology and radio frequency identification(RFID)based context-aware technology.Among them,RFID-based context-aware technology has the characteristics of small size and reusability,so it has been widely used in academic research at home and abroad.However,RFID-based systems are susceptible to external interference during data collection,which directly affects the performance of the system,so we need to explore it more deeply.This thesis is mainly based on RFID target monitoring technology and related applications for research.First of all,this thesis explains the relevant research background,outlines the typical context-aware technologies and analyzes their differences,advantages and disadvantages.Secondly,the composition and working principle of the RFID-based context-aware system are introduced.Finally,this thesis proposes two scenarios based on RFID context-aware technology.With the rise and popularization of smart medical care,people's demand for rehabilitation medical services will gradually increase,and home rehabilitation is receiving more and more attention.This thesis designs and implements an upper limb rehabilitation monitoring system based on RFID.The system obtains the original phase signal of the action according to its arranged tag array,then divides the signal segment related to the action,extracts the feature value to construct the data set,and finally uses the convolutional neural network(CNN)to identify rehabilitation actions,and can recognize the action angles for auxiliary rehabilitation monitoring.Traditional monitoring technology mainly relies on cameras,but this technology has the risk of privacy leakage.Therefore,this thesis designs and implements an RFID-based monitoring system for areas of interest to monitor privacy areas as an auxiliary monitoring function.The system divides the area of interest into: safe area,warning area,and dangerous area.First of all,the system collects the original phase signals when someone in different areas,and then undergoes signal preprocessing and feature value extraction.Finally,the k NN algorithm is used to realize the identification of each area,and further realize the monitoring of the area of interest.This thesis has conducted many tests and analyses on the above-mentioned system,and the average accuracy of the above-mentioned system is 97.8% and 97.3% respectively,which fully verifies the feasibility of the above-mentioned system.