Leveraging spatio-temporal redundancy for RFID data cleansing

Radio Frequency Identification (RFID) technologies are used in many applications for data collection. However, raw RFID readings are usually of low quality and may contain many anomalies. An ideal solution for RFID data cleansing should address the following issues. First, in many applications, duplicate readings (by multiple readers simultaneously or by a single reader over a period of time) of the same object are very common. The solution should take advantage of the resulting data redundancy for data cleaning. Second, prior knowledge about the readers and the environment (e.g., prior data distribution, false negative rates of readers) may help improve data quality and remove data anomalies, and a desired solution must be able to quantify the degree of uncertainty based on such knowledge. Third, the solution should take advantage of given constraints in target applications (e.g., the number of objects in a same location cannot exceed a given value) to elevate the accuracy of data cl...

• Type: Conference
• Year: 2010
• Where: SIGMOD
• Authors: Haiquan Chen, Wei-Shinn Ku, Haixun Wang, Min-Te Sun
• Keywords: Database, RFID, RFID Data, RFID Raw Data, SIGMOD 2010