RFID Data Warehousing and OLAP with Hive

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

The ability to track and trace individual items, especially through large-scale and distributed networks, is the key to realizing many important business applications such as supply chain management, asset tracking, and counterfeit detection. Networked RFID (radio frequency identification), which uses the Internet to connect otherwise isolated RFID systems and software, is an emerging technology to support traceability applications. Despite its promising benefits, there remain many challenges to be overcome before these benefits can be realized. One significant challenge centers around dealing with uncertainty of raw RFID data. In this paper, we propose a novel framework to effectively manage the uncertainty of RFID data in large scale traceability networks. The framework consists of a global object tracking model and a local RFID data cleaning model. In particular, we propose a Markov-based model for tracking objects globally and a particle filter based approach for processing noisy, low-level RFID data locally. Our implementation validates the proposed approach and the experimental results show its effectiveness.

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 has been considered the “next revolution in supply chain management” (Srivastava, 2004, p. 60). Current research and development related to RFID focuses on the manufacturing and retail sectors with the aim of improving supply chain efficiency. After the manufacturing and retail sectors, health care is considered to be the next sector for RFID (Ericson, 2004). RFID technology’s potential to improve asset management in the health sector is considerable, especially with respect to asset management optimization. In fact, health expenses have increased substantially in Organization for Economic Co-operation and Development (OECD) countries in recent years. In Canada, the public health budget amounted to $91.4 billion (CAD) for the year 2005–2006 compared to $79.9 billion in 2003–2004 (CIHI, 2005). Moreover, the health care industry has been the focus of intense public policy attention. In order to curb this upward trend, the public heath sector in Canada is subject to strict budget constraints. Among the different alternatives for reducing expenditures, the improvement of asset management within the different health institutions appears to be worthwhile. RFID technology seems to be a viable alternative to help hospitals effectively manage and locate medical equipment and other assets, track files, capture charges, detect and deter counterfeit products, and maintain and manage materials. In other words, health care organizations would benefit particularly from RFID applications. The main objective of this study is to investigate the potential for RFID technology within one specific supply chain in the health care sector.B ased on a field study conducted in a large nonprofit hospital, this article tests some scenarios for integrating RFID technology in the context of two warehousing activities. We will first introduce the context of the health care sector and the current applications of RFID technology in that sector. The next section presents the methodological approach that was used in the study. The research findings and their implications are then discussed. Finally, some closing remarks are made.

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) technology is used to identify RFID-tagged objects automatically. An RFID system generally consists of three components: an RFID tag, an RFID reader, and a backend system. An RFID tag is a small device for identification, which is attached to or embedded in an object. It has an unique identifier and may optionally hold additional product information for the object. An RFID reader is a device used to interrogate RFID tags. It can be fixed or portable. It passes communication messages between an RFID tag and a backend system. A backend system stores and manages the online data which are associates with RFID tags. Since the communication between an RFID tag and an RFID reader occurs without optical line of sight, RFID tags can be read much longer and much faster than other automatic identification and data capture (AIDC) technologies such as Bar-codes and smartcards. Thanks to these advantages, RFID technology has various applications.

The purpose of the study is to evaluate the effectiveness of Radio Frequency Identification (RFID) technology in library management system and services in Bangladesh. This study followed survey and interview methods of data collection through a structured questionnaire. The population of study was all nine libraries in Bangladesh where RFID technology has been installed. The study reveals that all nine libraries are using RFID technology, namely, anti-theft detection Electronic Article Surveillance (EAS) gate, staff-work station and RFID tag. In addition to these, some of them are using kiosk, converter, level printer, book drop station, digital library assistance (DLA) and RFID smart card for entrance. The significance numbers of library users employ the RFID system and services and it is increasing gradually, but some of the RFID machines like level printer, book drop station and DLA are under-utilized because of lack of trained staff, patron’s doubt on new technology and less demand on using them in house-keeping library operation.

The purpose of this paper is to explore and describe the costs and process of implementing radio frequency identification (RFID) technology to manage and control the rotation of returnable transport items. Owing to the novelty of using RFID in logistics and supply chain management, in-depth case studies were conducted at two global firms in the retail industry to investigate how and why organisations implement and assess RFID technology. These case studies provide insights into how RFID benefits have been attainable in practice, and indicate that the cost of introducing RFID technology is not generally a barrier. As a result, this paper proposes an inductively derived stage model of the RFID implementation process. In this, implications for management are identified and discussed to guide managers in the process of implementing RFID technology.

Hospitals represent a significant part of healthcare systems and account for no less than 60% of the entire healthcare service in most of developed countries. Therefore, improving service in hospitals is an important element to the process of healthcare reform. Better use of resources, more consistent quality, and a higher service level are the keys to rationalise the huge expenditure in healthcare systems due to higher growth in demand. Even though massive spending has been directed towards hospital improvement in Ireland, services provided in Irish hospitals are ranked relatively low comparing to the other European countries. Growth of population, aging, European Union regulations, and demanding patients place more pressure on healthcare researchers to provide innovation solutions for Irish hospitals. In the last two decades, the use of technology had a significant impact on hospital performance in terms of responsiveness, quality, and management practices. Radio Frequency Identification (RFID) technology has been successfully implemented in a number of hospital systems in many developed countries. It is an emerging technology for applications such as managing and tracking patients, equipment, and drugs. Integrating RFID technology into hospital systems allows a dramatic enhancement in hospital efficiency and effectiveness measures to happen. This paper gives a comprehensive review on the up-to-date applications of RFID technology in hospital systems. It includes a classification of RFID applications at different areas of hospitals. Inclusive analysis of the impact of RFID implementation on the overall performance of the hospitals is presented. As new technology, this paper looks into the challenges and problems facing the management in employing the technology. Recommendations on potential impact of using RFID in Irish hospitals are discussed.

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.

PurposeThis paper aims to explore and describe the impact of radio frequency identification (RFID) technology on inventory accuracy within a production and assembly plant, and to propose a model for assessing the impact of the technology on inventory accuracy.Design/methodology/approachThe empirical investigation, based on case study research, focuses on an RFID implementation at a supplier of injection‐moulded, surface‐treated plastic to the automotive industry. This implementation is one of the few item‐level, open‐loop RFID implementations in the automotive industry.FindingsThe empirical paper provides insights into, how inventory accuracy has been improved and made attainable in practice by implementing RFID, and indicates that the technology ensures inventory inaccuracy will be kept at a minimum. As a result, an analytical model is presented which identifies the impact of RFID technology on inventory accuracy.Research limitations/implicationsThe case study and context need to be considered when generalising upon the findings. Furthermore, it is hoped future research could further develop the model presented and test it against implementation practice.Practical implicationsRFID technology provides practitioners with the opportunity to eliminate waste, and improve production and assembly performance. The research provides practitioners with experience of, and insights into how a production and assembly plant has improved inventory accuracy by implementing RFID technology. In particular, practitioners are provided with a model which enables them to assess the impact of RFID on inventory accuracy.Originality/valueThis paper contributes to the RFID community by providing empirical insights into the impact of RFID technology on inventory accuracy, but also more broadly into logistics and operations management research.

Radio Frequency Identification (RFID) is an automatic identification (Auto-ID) Technology, which is most commonly used now days in healthcare for tracking and identifying objects. In the context of assistive environment, statistical query analysis over the history of Data generated from RFID Applications as well as real time monitoring of the patients or the elderly people (people who need assistance) are really important. But Data generated from these types of healthcare applications can be very large, if each individual object becomes RFID-Tagged. As a result, the RFID technology is also imposing a greater challenge to provide efficient query responses over these Data. In this paper, we show how to apply traditional Data Warehousing techniques to model these massive amounts of RFID Data. In short, we describe how to construct an RFID Warehouse so that important query analyses can be performed very efficiently. We also show how to process a continuous stream of RFID Data to answer real time queries using Sliding Window techniques. By the help of using synthetic Datasets, we conclude that querying over Data Warehouse is much faster than traditional Relational DBMS. We also find that the aforesaid performance improvement is expected to be much higher as the size of the Dataset increases.

Even invented and applied initially during the World War II, RFID (Radio Frequency IDentification) technologies [1] have attracted much attention recently. Precisely speaking, RFID technologies have been applied very widely in some proprietary or closed systems, for example, animal control [2], portal control (access badges), etc. in last decades. The main advantages of RFID application are, storing item data in an electronic way even for further update, data access by electromagnetic wave in a wireless manner, and allowing quick multiple accesses to RFID tags. Based on the diverse applications, different spectrum bands are allocated, for example, LF (125 134.2 kHz and 140 148.5 kHz) for animal control, HF (13.56MHz) for electronic ticket, and UHF (868 MHz-928 MHz) for logistics, etc. Most of the frequencies are located in the ISM (Industrial, Scientific and Medical) bands [1]. However, RFID was emphasized again mainly because of the need of supply chain [3]. By proposing a standard for the format of electronic data used for goods items, of which EPC (Electronic Product Code) [4] is an example, the products can be registered at once when they are shipped out from the factories in one country, and be released when they are checked out at the counter of a supermarket in the other country in the world. These products might have been transferred through Customs of many countries and carried by different traffic means. When being through these check points, the related data stored in the tags are updated. This is called “product tracking” and is to be carried out in an “Internet of Thing (IOT)” [5]. This Chapter is to have a review on the technology theme – how to provide low-cost RFID Tags, when RFID technology is to be applied into the logistics area where the RFID tags are supposed to be not re-usable and to be as “zero-cost” as possible. Generally speaking, there are three major parts composing a RFID Tag’s total cost, namely, antenna, chip and assembly for them. The cost of antenna, in addition to the design phase, is mainly dependent on the manufacturing process. Therefore, manufacturing process should be focused if antenna’s cost, then the tag, is concerned. This is the theme of this Chapter. Not like the other antenna applications, for example, wireless LAN or mobile phone, in which antennas need to be compliant to the end products’ appearance by following the market trend. In the tag antenna industry, on the contrary, it does not need to design or modify the tag antenna often. The tag antenna just needs to electrically match the chip used in the beginning of design. It is not necessary for tag providers to prepare a wide product spectrum in the market. Again, not like the mobile phone industry, RFID tag’s players just

As the expanding of the production scale, the efficiency and the stability of the manufacturing line begin to dominate the key role in manufacturing industry accompany the material monitor. It is learned that effective and correct operation will save a lot of producing cost. Therefore, in this paper, a monitor and control system framework architecture based on Radio Frequency Identification (RFID) technology is presented according to specific manufacturing requirement of discrete product line in China. In this system, the RFID technology is supposed to be combined with real time database and Programmable Logic Controller (PLC) etc. It is applied to enhance the automation of the manufacturing with RFID technology. A case in point is the application of the framework in one clothing factory. The feedback indicates that with the help of the RFID technology based system the productivity of cloth producing has been increased. It not only provides a stable manufacturing process and an accuracy management method for producing timely, but also increases the automation level of the manufacturing line. It can be reconfigured to determine the production facility's positions automatically.

Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse objects. To obtain or manipulate the data from relational databases, the user must be familiar with SQL and must also write an appropriate and valid SQL statement. However, users who are not familiar with SQL are unable to obtain relevant data through relational databases. To address this, we propose a Natural Language Processing (NLP) model to convert an NLQ into an SQL query. This allows novice users to obtain the required data without having to know any complicated SQL details. The model is also capable of handling complex queries using the OLAP cube technique, which allows data to be pre-calculated and stored in a multi-dimensional and ready-to-use format. A multi-dimensional cube (hypercube) is used to connect with the NLP interface, thereby eliminating long-running data queries and enabling self-service business intelligence. The study demonstrated how the use of hypercube technology helps to increase the system response speed and the ability to process very complex query sentences. The system achieved impressive performance in terms of NLP and the accuracy of generating different query sentences. Using OLAP hypercube technology, the study achieved distinguished results compared to previous studies in terms of the speed of the response of the model to NLQ analysis, the generation of complex SQL statements, and the dynamic display of the results. As a plan for future work, it is recommended to use infinite-dimension (n-D) cubes instead of 4-D cubes to enable ingesting as much data as possible in a single object and to facilitate the execution of query statements that may be too complex in query interfaces running in a data warehouse. The study demonstrated how the use of hypercube technology helps to increase system response speed and process very complex query sentences.