RFID Data Processing with a Data Stream Query Language

Abstract

An RFID system consists of RFID readers with antennas, host computers, and transponders or RF tags which are RFID technology provides significant advantages over recognized by the readers. An RFID tag is uniquely identraditional object-tracking technologies and is increasingly tified by a tag ID stored in its memory and can be attached adopted and deployed in real applications. RFID applicato almost anything. Such IDs are specified through the EPC tions generate large volume of streaming data, which have (Electronic Product Code) standard [4]. In addition, RFID to be automatically filtered, processed, and transformed technology can also be used in conjunction with sensors that into semantic data, and integrated into business applicameasure varieties of physical measurements, such as sentions. Indeed, RFID data are highly temporal, and RFID sors for temperature, humidity, blood pressure, etc, which observations form complex temporal event patterns which provide extra information for the entity uniquely identified can be very differentfor various RFID applications. Thus, it by the RFID tag. is desirable to have a general RFID data processing frame-RFID technology makes it possible to i) collect large work with a powerful language, for the end users to examount of data for tracking and identifying physical obpress a variety of queries on RFID data streams, as well jects along their history [19] and ii) real-time monitor physas detecting complex events patterns. While data stream ical objects and their environment [20]. While RFID obsermanagement systems (DSMSs) are emerging for optimized vations are simple primitive events (consisting of reader's stream data processing, they usually lack the language con-EPC code, observed tag ID and the observation timestamp), struct support for temporal event detection. In this paper; RFID observation streams from multiple readers form comwe discuss a stream query language to provide comprehenplex event patterns mostly temporal in nature [19, 20]-sive temporal event detection, through temporal operators to represent business application logic. This poses a sigand extension of sliding-window constructs. With the intenificant challenge for RFID data processing for the followgration of temporal event detection, a DSMS has the capaing requirements of: i) automatically filtering, interpreting bility to serve as a powerful system for RFID data processand transforming raw RFID observation data into semaning. tic business logic data; ii) real-time monitoring and querying physical objects and their environment; iii) the capability to process high volume RFID data streams; and iv)

A Framework for Human Resource Information Systems Based on Data Streams

“…Bai and his colleagues first discussed the use of on-demand time stamps for idle waiting prone (IWP) operators [14], but didn't cover unary operators, brashness, and the results of other experiments we've discussed here. Others have discussed related techniques to support composite event semantics [14] and RFID applications [15,16].…”

Semantic-Based RFID Data Management

“…temporal aspects. Bai [17] studied limits of using SQL to detect temporal events in a database and illustrated a SQL-like language to query such events in an efficient way. Ban [21] presented a location-oriented indexing which traces paths registered by RFID readers through a novel representation model.…”

“…The first one concerns run-time processing of data streams [16,17,18,19]. Most current approaches, however, track only very basic information, namely raw data produced by RFID readers.…”

RFID-assisted Product Delivery in Sustainable Supply Chains: A Knowledge-based Approach

“…Most current approaches for run-time processing of RFID data in supply chains [21,2] manage only very basic information, namely raw (EPC, location, time) triples produced by RFID readers, where EPC (Electronic Product Code) is the unique product identifier, while location and time mark each RFID reading event.…”

“…Canonical EPCglobal RFID identification has been extended [16,7], providing semantic-based value-added services whose deployment and outcomes have been grounded in an advanced "green supply chain" setting. Semantic Web languages such as OWL 2 and DIG [3] are used for building the linguistic and semantic infrastructure underlying a networked and capillary exchange of information among chain actors aimed at overcoming restrictions imposed by existing RFID solutions. Key features are: (i) to leverage a hybrid wireless communication platform for enabling a distributed, backward compatible data management system; (ii) to provide decision support exploiting semantic-based annotations accompanying and describing goods aimed at optimizing the reliability and sustainability of the whole supply process.…”