bSpace: A Data Cleaning Approach for RFID Data Streams Based on Virtual Spatial Granularity

摘要：

RFID holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight, and can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data have to be collected, filtered, and transformed into semantic application data. RFID data, however, contain false readings and duplicates. Such data cannot be used directly by applications unless they are filtered and cleaned. To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a “smoothing filtering. In this paper, a new “smoothing filtering approach named bSpace is proposed, which is based on the concept of virtual spatial granularity. For providing accurate RFID data to applications, bSpace uses a Bayesian estimation algorithm to fill up false negatives, and uses the rules which we define to solve false positives.

关键词： RFID Data Stream Data Cleaning Virtual Spatial Granularity

作者: Baoyan Song Pengfei Qin Hao Wang Weihong Xuan Ge Yu

作者单位: School of Information Science and Technology, Liaoning University Shenyang, Liaoning, China School of information science and engineering , Northeastern University Shenyang, Liaoning, China

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）