Filtering Redundant Data from RFID Data Streams

Abstract

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.

A Review on Missing Tags Detection Approaches in RFID System

“…Hash functions will hash the ID of the tags, and then we can compare it quickly with the list in arrays. In the array, we can store the count of the unique tag such as in [30]. If the count is less than it supposed to be, there is a case of missing tags.…”

Proactive Redundant Data Filtering Scheme for Combined RFID and Sensor Networks

“…Finally, in 2016, the authors of [21] proposed an approach for filtering RFID duplicated data from RFID data based on a modified Bloom Filter that uses only a single hash function. The proposed approach is interesting but considers only passive tags and is not comparable with our approach to the RFID sensor system.…”

A Review on Complex Event Processing in RFID System

“…In recent years, the use of Complex Event Processing (CEP) has been gaining attention in the research of wireless sensor networks, particularly RFID applications. The primary challenge associated with sensor data is the nature of the application that contains data uncertainty, which is indirectly demanding real-time filtering and data analysis [8], [9]. The conventional CEP inevitably carry a certain degree of uncertainties, such as imprecision and incompleteness caused by the sensor environment and mediators [10].…”