Approximately Filtering Redundant Data for Uncertain RFID Data Streams

2017 ◽  
Author(s):  
Liao Guoqiong ◽  
Zhou Jun ◽  
Hui Ni ◽  
Huang Xiaomei ◽  
Huang Zhiwei ◽  
...  
Keyword(s):  
Data Streams ◽  
Redundant Data ◽  
Rfid Data

scholarly journals An Approach for Removing Redundant Data from RFID Data Streams

Sensors ◽  
2011 ◽  
Vol 11 (10) ◽  
pp. 9863-9877 ◽  
Author(s):  
Hairulnizam Mahdin ◽  
Jemal Abawajy
Keyword(s):  
Data Streams ◽  
Redundant Data ◽  
Rfid Data

scholarly journals Filtering Redundant Data from RFID Data Streams

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Hazalila Kamaludin ◽  
Hairulnizam Mahdin ◽  
Jemal H. Abawajy
Keyword(s):  
Radio Frequency Identification ◽  
Data Streams ◽  
False Positive Rate ◽  
Bloom Filter ◽  
True Positive Rate ◽  
Redundant Data ◽  
Rfid Data ◽  
Positive Rate ◽  
Frequency Identification ◽  
Processing And Storage

Radio Frequency Identification (RFID) enabled systems are evolving in many applications that need to know the physical location of objects such as supply chain management. Naturally, RFID systems create large volumes of duplicate data. As the duplicate data wastes communication, processing, and storage resources as well as delaying decision-making, filtering duplicate data from RFID data stream is an important and challenging problem. Existing Bloom Filter-based approaches for filtering duplicate RFID data streams are complex and slow as they use multiple hash functions. In this paper, we propose an approach for filtering duplicate data from RFID data streams. The proposed approach is based on modified Bloom Filter and uses only a single hash function. We performed extensive empirical study of the proposed approach and compared it against the Bloom Filter, d-Left Time Bloom Filter, and the Count Bloom Filter approaches. The results show that the proposed approach outperforms the baseline approaches in terms of false positive rate, execution time, and true positive rate.

Online Pattern Aggregation over RFID Data Streams

2010 ◽  
pp. 262-273 ◽  
Author(s):  
Hailong Liu ◽  
Zhanhuai Li ◽  
Qun Chen ◽  
Shanglian Peng
Keyword(s):  
Data Streams ◽  
Rfid Data

scholarly journals Reducing False Negative Reads in RFID Data Streams Using an Adaptive Sliding-Window Approach

Sensors ◽  
2012 ◽  
Vol 12 (4) ◽  
pp. 4187-4212 ◽  
Author(s):  
Libe Valentine Massawe ◽  
Johnson D. M. Kinyua ◽  
Herman Vermaak
Keyword(s):  
Data Streams ◽  
False Negative ◽  
Sliding Window ◽  
Rfid Data ◽  
Window Approach

Frameworks of AMHS Simulation Driven by RFID Data Streams

ICLEM 2010 ◽  
2010 ◽  
Author(s):  
Weiping Huang ◽  
Bo Zhang ◽  
Zhili Zhou
Keyword(s):  
Data Streams ◽  
Rfid Data

Supporting real-time supply chain decisions based on RFID data streams

2011 ◽  
Vol 84 (4) ◽  
pp. 700-710 ◽  
Author(s):  
Damianos Chatziantoniou ◽  
Katerina Pramatari ◽  
Yannis Sotiropoulos
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Data Streams ◽  
Rfid Data
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