Name
Abstract | ||
|---|---|---|
Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3390/s111009863 | SENSORS |
Keywords | Field | DocType |
RFID,duplicate reading,automatic identifications,data filtering | Data mining,Data stream mining,Data filtering,Data stream,Computer science,Supply chain management,Radio-frequency identification,Database | Journal |
Volume | Issue | ISSN |
11 | 10 | 1424-8220 |
Citations | PageRank | References |
8 | 0.64 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hairulnizam Mahdin | 1 | 16 | 6.61 |
| Jemal Abawajy | 2 | 1927 | 117.32 |