Comparison of RFID data processing using dimensionality reduction techniques

Radio Frequency Identification Technology (RFID) used in wide range environment. The volume of RFID data is enormous, the management and extraction of data is complex and time consuming process. RFID data processing can be performed after applying dimensionality reduction techniques. The proposed APCA is efficient one to handle the huge and noisy data. We had taken the two different sets of RFID data for applying this dimensionality reduction technique. The compression and execution time is calculated for these data sets. We have considered principal component Analysis (PCA) and advanced principal component analysis (APCA) and compared both the results in terms of dataset size and response time. Experiment results show that, APCA has better performance when process the RFID data.