RFID Data Analysis and Evaluation Based on Big Data and Data Clustering

Abstract

The era people live in is the era of big data, and massive data carry a large amount of information. This study aims to analyze RFID data based on big data and clustering algorithms. In this study, a RFID data extraction technology based on joint Kalman filter fusion is proposed. In the system, the proposed data extraction technology can effectively read RFID tags. The data are recorded, and the KM-KL clustering algorithm is proposed for RFID data, which combines the advantages of the K-means algorithm. The improved KM-KL clustering algorithm can effectively analyze and evaluate RFID data. The experimental results of this study prove that the recognition error rate of the RFID data extraction technology based on the joint Kalman filter fusion is only 2.7. The improved KM-KL clustering algorithm also has better performance than the traditional algorithm.