Efficiently managing uncertain data in RFID sensor networks

Radio Frequency Identification (RFID) is a modern wireless data transmission and reception technique for applications including automatic identification, asset tracking and security surveillance. As barcodes and other means of identification and asset tracking are inadequate for recent demands, RFID technology has attracted interest for applications such as logistics, supply chain management, asset tracking, and security access control. However, the cost of RFID limits their potential for the replacement of trillions of barcodes each year. The only possible solution is a fully printable chipless RFID tag. A novel RFID system comprised of a chipless RFID tag and an associated reader is reported in the thesis. The chipless tag is a fully-passive microwave circuit and uses spectral signatures for data encoding. The tag consists of a multi-resonator coupled to transmitting and receiving antennas. To accommodate multiple bits, the tag operates over the ultra wideband (UWB) frequency spectrum. UWB antennas are used to receive the interrogation signal sent from the reader and transmit the signal back to the reader after performing modulation of the frequency spectra with the multi-resonator. Modulation is performed in both amplitude and phase of the spectrum. A chipless tag up to 35 bits which operate over 3-7 GHz band has been designed. After the successful design of the chipless tag, three prototype readers have been developed. The Gen1 reader was designed to validate the chipless RFID concept using 6-bit chipless tag reading based on amplitude-only detection in S-band; the Gen2 reader is an upgraded version of Gen1 with both amplitude and phase detection capability; and the third generation reader is a UWB reader capable of reading up to 35-bits in the UWB band. The integrated reader is a complete system with analog RF and digital control sections loaded with graphical user interface (GUI) and software protocol. Both the hardware and software design of the RFID reader and field trials of the designed chipless RFID system have been validated in the real world environment. An investigation into antenna systems in order to enhance reading range up to 70 cm has also been performed. The unique features of the developed chipless RFID system are: (i) a low cost, fully printable tag and (ii) secure, remote and non-line-of-sight operability. The importance of this concept lies in the fact that chipless RFID tags become comparable to barcodes in terms of the substrate material used and the cost of fabrication. The main application of this chipless RFID system is in short-range tagging of extremely low cost items such as the Australian polymer banknote.

Real-time location systems (RTLS) such as radio frequency identification (RFID) have been shown to improve safety, save cost, and increase patient satisfaction in a healthcare setting especially in the emergency department (ED). Hospital administrators have realized the potential of these applications for improved workflow and operations and are positively adopting it despite the substantial implementation costs of such technologies. Our group has reported several studies with RFID data in the ED showing the relationship between RFID determined patient contact times and length of stay (LOS). In this study, we use ED RFID data to determine the relationship between the total LOS in ED to the overall patient satisfaction obtained from a survey report. ED survey results from 35 questions were obtained from patients after discharge. An observational cohort study was performed in the ED using RFID data from Jan 1 – Dec 31, 2017 matched with the ED survey participants. A total of 2595 survey data was used for logistic regression analysis with the RFID data. Results show that higher treatment LOS influenced overall patient satisfaction negatively. The results provide new insights into designing ideal patient-care team interactions to reduce overall LOS while providing optimal ED care, thereby improving patient satisfaction.

Radio Frequency Identification (RFID) technology is used in many applications for monitoring object movement. The use of RFID in supply chain management systems enables to track the movement of products from suppliers to warehouses, store backrooms, and eventually points of sale. The vast amount of data resulting from the proliferation of RFID readers and tags poses challenges for data management and analytics. RFID data warehousing can enhance data quality and consistency, and give great potential benefits for Online Analytical Processing (OLAP) applications. Traditional data warehouses are built primarily on relational database management systems. However, the size of RFID data being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hive is an open-source data warehousing solution built on top of Hadoop which is a popular Big Data computing framework. This paper presents alternative RFID data warehouse designs which can handle a large amount of RFID data and support a variety of OLAP queries. The proposed approaches are implemented on Hive and evaluated for query performance in cloud computing environment.

Radio frequency identification (RFID) applications are emerging as key components in object tracking and supply chain management systems. In next future almost every major retailer will use RFID systems to track the shipment of products from suppliers to warehouses. Due to RFID readings features this will result in a huge amount of information generated by such systems when costs will be at a level such that each individual item could be tagged thus leaving a trail of data as it moves through different locations. We define a technique for efficiently detecting anomalous data in order to prevent problems related to inefficient shipment or fraudulent actions. Since items usually move together in large groups through distribution centers and only in stores do they move in smaller groups we exploit such a feature in order to design our technique. The preliminary experiments show the effectiveness of our approach.

Radio Frequency Identification (RFID) is an emerging wireless object identification technology with many potential applications such as supply chain management, personnel tracking and healthcare. However, security vulnerabilities of the RFID system have been a serious concern for its wide adoption in many applications. Although much work has been done to provide privacy and anonymity, little focus has been given to ensure RFID data confidentiality, integrity and to address the tampered data recovery problem. To this end, we propose a lightweight stenographic-based approach to ensure RFID data confidentiality and integrity as well as the recovery of tampered RFID data.

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.

As an information of combining RFID and wireless data communication technologies, Internet of Things is making things all over the world connected. RFID (Radio Frequency Identification) technology is the most basic key technology in Internet of Things, which combines signal processing, wireless communication, embedded calculation and data management. RFID technology is being widely used in various areas, such as object tracking systems, supply chain management, quick disbursement and so on. Especially, deducing semantic relationships of objects in RFID applications has caught worldwide attention, such as inferring an event reminder "somebody lost things" according to the containment-relationship 1 of objects. However, there are rarely any concrete solutions applied to our practical life. In this paper, we study and implement an RFID based object-relationship recognition system to efficiently retrieve the group-relationship and containment-relationship between objects in real-time. Finally, we give a real scenario to implement our research.

Radio Frequency Identification (RFID) is an automatic data capturing technology and the dirty data stream generated by the RFID readers is one of the main factor limit the widespread adoption of RFID technology. In order to provide reliable data to RFID application, it is necessary to clean the collected data before they are subjected to warehousing. In this paper we are going to construct the elegant hospital environment using RFID and developed the cellular based approach algorithm to clean the duplication anomaly. First middleware approach is applied to deal with low complex anomalies and in next stage deferred approach is followed to deal with high complex anomalies based on business context. Simulation shows our cleansing approach for duplication removal deals with RFID data more accurately and efficiently. Thus we can bring down the health care costs, optimize business processes, streamline patient identification processes and improve patient safety.

Radio Frequency IDentification (RFID) technology successfully integrates radio transmitter and receiver, small size memory space and control circuitry to remotely store and retrieve data via wireless RF transceiver. As low-cost RFID tag can be massively manufactured by semiconductor industry, new applications associated with RFID technology have emerged rapidly such as inventory tracking, book storage and management, and airport baggage handling. Generally an RFID system is composed of many RFID tags (or tagged objects), at least one RFID reader, and one backend application system with database. An RFID tag gains its operation energy from query signals that are radio waves transmitted by RFID reader. Once a tag responds the query with its stored information to RFID reader, usually a unique identity number or string, the RFID system can recognize the tag carrier and perform required business logic operation. As RFID technique is widely used in supply chain management, the corresponding RFID application systems are expected to process and manage large amount of tagged objects at a predefined period of time regularly. Therefore, for large-scaled RFID applications, tag reading throughput is very critical since it will affect the total data processing time. To measure tag reading throughput of a RFID system, two performance criteria are usually adopted: tag reading delay and reader energy consumption [5]. As RFID reader and tag always communicate over a shared wireless channel, it is very easy to have signal collisions during a normal tag identification process when multiple tags exist in reader’s interrogation area. Signal collision results in query or data retransmission and eventually increases communication overhead and time delay of tag identification. Hence, an efficient tag collision arbitration mechanism is very important and critical for RFID systems to achieve effective performance. Existing RFID tag identification schemes can be classified into aloha-based solutions [3, 10, 12-13, 16, 21, 23-24] and tree-based solutions [1, 2, 4, 6-9, 14-15, 17-20, 22]. In aloha-based schemes, a reader estimates the number of tags in its interrogation area and broadcasts the total number of timeslots to each tag. Then each RFID tag randomly selects its own timeslot to transmit its ID without knowing which timeslots have been selected by other tags. By distributing tag responses to distinct timeslots instead of getting all tag responses at the same time, aloha-based schemes effectively reduce the probability of signal collision. However, aloha-based schemes have tag starvation problem in which certain tags may not

Modern identification procedures such as radio frequency identification (RFID) are able to provide transparency in applications including supply chain, logistics and equipment management. The benefits of visibility and fast identification provided by RFID technology especially in supply chain management (SCM) reduce the risk of counterfeiting (Gao et al., 2004). There are two mainly ways in which RFID technology supports a visible and fast identification processes: 1) RFID allows for new, automated and secure ways to efficiently authenticate physical items; and 2) As many companies invest in networked RFID technology for varying supply chain applications, the item-level data can be gathered in any case (Lehtonen et al., 2006). Despite these benefits, RFID technology is still not widely implemented. The main reasons are, firstly, the difficult are, firstly, the difficult technical aspects of implementation resulting in high setup costs, secondly, growing security and privacy concerns. Our focus in this paper is to discuss the second reason for the low take-up of RFID technology, that is, security and privacy concerns. We argue that without applying maximum security and privacy, trustworthiness between supply chain partners will be minimal. As a result, the effectiveness and collaboration of traditional supply chain environment with RFID technology cannot be achieved. Given that humans cannot read the RFID tags on items and the tags themselves maintain no history of past readings, the challenge of security and privacy in this technology is related to the nature of RFID tags and their functionality (Juels, 2005). A retailer inventory that is labeled with unprotected tags may be monitored and read by unauthorised readers. The inventory data holds significant financial value for commercial organisations and their competitors. Once data has been accessed by unauthorised users, it can be cloned on empty tags, giving rise to the counterfeiting issue. Counterfeiting in the form of cloned or fraudulent RFID tags is the consequence of a lack of security measures and trustworthiness among the supply chain partners when RFID technology is used to automate their business transactions. Privacy violations stem from the fact that when goods are tagged, the manufacturers, retailers and consumers will be able to track the goods beyond point-of-sale (POS) because they have associated data. Even if the tags only contain product codes rather than unique serial numbers, a consumer’s taste in brands “constellation” can betray their identity.

In recent years, there have been many attempts to connect the latest RFID (Radio Frequency Identification) technology with EIS (Enterprise Information System) and utilize them. However, in most cases the focus is only on the simultaneous multiple reading capability of the RFID technology neglecting the management of massive data created from the reader. As a result, it is difficult to obtain time-related information such as flow prediction and analysis in process control. In this paper, we suggest a new method called `procedure tree`, an enhanced and complementary version of PathTree which is one of RFID data mining techniques, to manage massive RFID data sets effectively and to perform a real-time process control efficiently. We will evaluate efficiency of the proposed system after applying real-time process management system connected with the RFID-based EIS. Through the suggested method, we are able to perform such tasks as prediction or tracking of process flow for real-time process control and inventory management efficiently which the existing RFID-based production system could not have done.

As a promising technology for tracing the product and human flows, Radio Frequency Identification (RFID) has received much attention within database community. However, the problem of missing readings restricts the application of RFID. Some RFID data cleaning algorithms have therefore been proposed to address this problem. Nevertheless, most of them fill up missing readings simply based on the historical readings of independent monitored objects. While, the correlations (spatio-temporal closeness) among the monitored objects are ignored. We observe that the spatio-temporal correlations of monitored objects are very useful for imputing the missing RFID readings. In this paper, we propose a data imputation model for RFID by efficiently maintaining and analyzing the correlations of the monitored objects. Optimized data structures and imputation strategies are developed. Extensive simulated experiments have demonstrated the effectiveness of the proposed algorithms.

Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops.

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies for pervasive systems. Both of them have deployed in many areas. RFID and WSN, have their own advantages, are always deployed respectively. Integration of RFID and WSN is given little attention. In this paper, the system integrated RFID and WSN is designed. The Management software is also implemented. This flexible prototype is applied in warehouse to verify the feasibility.

The explosion in recent interest in radio-frequency identification (RFID) tags stems primarily from advances in information processing in supply chain management. Given their processing power and memory capabilities, RFID tags can be used in a wide range of applications including those where barcodes can and cannot be used. Although the potential exists, it is hampered by the relatively high unit cost of implementation and issues related to privacy and security. As with any technology, unit cost of RFID tags and their related systems is bound to come down. As for security and privacy issues, the main impediments are limited processing power, memory, and external power to operate these tags. In spite of these resource constraints, recent years have seen a plethora of new authentication protocols that promise to alleviate security and privacy concerns associated with the use of RFID tags. We evaluate a few protocols that have been suggested for use in passive RFID-tagged systems and identify vulnerabilities that may be present. When appropriate, we present modifications of existing protocols to prevent identified vulnerabilities.