[RFID Middleware Design and Architecture | IntechOpen

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Winmecc 4.4 download. RFID Technologies: Emerging Issues, Challenges and Policy Options

 
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This explains the opinion other users have about WinMecC, ranging from “Highly recommended” to “Very dangerous”. Opinions by other users – Press the Read reviews button. Technical information about the app you are about to uninstall, by pressing the Properties button. Press the Uninstall button. A confirmation page will come up. Confirm the uninstall by clicking the Uninstall button. Press Next to start the cleanup. RFID middleware design and components will be discussed further in the next sections.

Multiple hardware support: The middleware must provide a common interface to access different kinds of hardware offering different features. Synchronization and scheduling: There should be intelligent scheduling and synchronization among all the processes of the middleware. This minimizes the latency and improves the efficiency of the middleware. Real-time handling of incoming data from the RFID readers: The middleware should handle the huge amount of data captured by the connected readers in real time without read misses.

Interfacing with multiple applications: The middleware should be capable of interacting with multiple applications simultaneously, by catering to all the requirements of the applications with minimal latency.

Device neutral interface to the applications: The application developer should only use the generic set of interfaces provided by the middleware independently of the type of hardware connected to the system. Scalability: The middleware design must allow easy integration of new hardware and data processing features.

It provides the following advantages:. It handles and processes the raw RFID data before passing it as aggregated events to the applications;. A layer of the RFID middleware incorporates all the device drivers of different hardware and exposes to the application standard interfaces to access this hardware.

If the application was provided with all the device drivers of all connected readers, it will be a hard job to manage and interface each of the devices. The application developer will then need to understand all the hardware specific internals and operations.

Also, the application, if provided with the huge amount of raw tag data reported by the readers, will find it very difficult to process the data in real time. A RFID middleware provides a standardized way of dealing with this flood of information, which processes the raw data and provides the application with clean and filtered data.

As shown in Fig. RFID middleware components. It maintains the device drivers of all the devices supported by the system, and manages all the hardware related parameters like reader protocol, air interface, and host-side communication. The data processor and storage layer is responsible for processing and storing the raw data coming from the readers.

Examples of processing logic carried by this layer are data filtering, aggregation, and transformation. This layer also processes the data level events associated with a specific application. The middleware management layer helps managing the configuration of the RFID middleware, and provides the following capabilities:.

RFID readers are typically abstracted as a logical reader which is either a collection of several readers or a part of the reader. This grouping mechanism is used where there is a need to have a set of readers capturing data from a particular area such as a warehouse with many loading docks. The advantage of this is that the application can query a small number of logical readers rather than having to aggregate events from each of the individual readers.

There are two standardized interaction models used to define the communication between the middleware and the applications. An application can operate at synchronous mode when requesting services on demand or asynchronous mode when it registers for information to be sent to it when certain conditions are met. RFID middleware usually provide some kind of data filtering, because sometimes it might be required to report only certain type and value of the tag data to the application.

The application needs to provide a set of defined patterns to the middleware. The middleware then allows only data that matches the pattern to be reported to the application.

There have been some proposals and research work involving middleware design and RFID data processing. It adjusts multiple readings of a tag, and performs tasks such as archiving data, and inventory control Ishikawa et al. This modular structure allows innovation to be promoted by independent groups of people, which helps avoiding the creation of a single monolithic specification that attempts to satisfy all needs for everybody Clark et al.

The EMS allows adapters to be written for various types of readers, collecting EPC data from readers in a standard format, allowing filters to be written to smooth or clean EPC data, allowing various loggers to be written, and buffering events to enable loggers, filters and adapters to operate without blocking each other.

Reader Interface : Allows readers and adapters to communicate events detected by the Auto-ID readers. Event Loggers Event Consumers : Allow for varied processing of events; store the information in the database, store events in a memory data structure, and broadcast the events to remote servers.

Event Queues Event Forwarders : Handle multiple reader event loggers with synchronous implementations. It provides the same interface as a database, but offers much better performance. The RIED should be a high-performance in-memory and a multi-versioned database. The TMS manages tasks, just as the operating system manages processes, and provides an interface for task management.

Task examples include data gathering, remote task scheduling, personnel alerts, and remote upload. The TMS should be a platform-independent system requiring little memory processing power, should automatically upgrade the tasks it executes, and should present a well-defined, interoperable external interface to schedule, monitor, and remove tasks.

Tasks should also be written in a platform-independent language using a simple well-defined SDK. Savant middleware key components. It is a multi-layered middleware that consists of five main layers shown in Fig. The physical layer deals with the hardware consisting of readers, tags and other sensors. This abstraction allows extending the middleware capabilities in the advent of introduction of new RFID technology Prabhu et al.

The protocol layer: The ability to support multiple tag protocols and add new ones is becoming imperative in middleware designs. It also deals with protocol specifics such as byte-based, block or even page reading and writing, structure and length of the command frames, partitioning of the tag memory space, checksums, etc Prabhu et al.

The data processing layer deals with processing data streams generated by the network of readers. All of these discrepancies are processed as exceptions and a variety of altering systems are available for resolution such as emails, messages, and user defined triggers Prabhu et al.

The purpose of this layer is to provide data in a suitable format to the application layer for decision making Prabhu et al. The data presentation layer presents the data as per the requirements of end-users or different applications requirements.

It facilitates data visualization for decision making. This layer supports two components the portal and the database connector. The portal provides the users with an interface to subscribe to the information of interest. The databases get populated in an asynchronous fashion in a trickle mode — a process with least priority so as to avoid the edge hosts getting locked up Prabhuet al. WinRFID exploits the. The IBM WebSphere is a sensor enabled product that allows sensor data aggregation and analysis, deriving insights from sensor data and integrating those insights with the SOA business processes.

The software provides the use of intelligent business rules that manage complex event identification and processing IBM Corporation, This solution expands device services allowing a single platform to support multiple sensor types, and supports workflow tooling for sensor data integration with business processes IBM Corporation, Therefore, it delivers new and enhanced capabilities to create a robust, flexible, and scalable platform for capturing new business value from sensor data.

The IBM sensor and actuator solutions framework Eisma, It is a critical RFID infrastructure component that allows a safe, secure, and efficient data and device integration from the edge of the enterprise into enterprise application systems. It has a dynamic, service provisioning architecture that enables scaling from small pilots to large deployments with high data volume Sun Microsystems, b. The RFID Management Console provides a browser based management interface, which allows configuration of various attributes and parameters of the middleware.

The Sun middleware exposes to the application, the hardware as logical readers. These logical readers may be a collection of one or more physical readers that the application can select and apply the various processing parameters to the group Sun Microsystems, a.

All of these middleware designs aim at providing a scalable solution for gathering, filtering, and providing clean RFID data to the end-user. However, there are still many open issues. The reliability of RFID data needs to be improved since inaccurate data could misguide the application users. The accumulation of RFID data generated in high volumes, may lead to slower queries and updates, therefore efficient RFID data management solutions such as data transformation, aggregation, and dissemination should be investigated.

Raw RFID data is not of significant value until it is aggregated with other data to obtain appropriate inferences, and transformed into a suitable form for application level interaction. Also, the applications with high security requirements are increasingly using RFID; therefore support for data security and confidentiality is needed. However, such support should maintain a desirable system performance.

RFID also raises the privacy concerns because of its potential to leak proprietary information and ability to track private information such as the spending history of a consumer. Technical solutions must be implemented to ensure that private data is not compromised with Sheng et al. While the Savant middleware architecture provides features for cleaning the data and interfacing with different kinds of RF readers, it has limited built-in functionality for addressing business rules management, dealing with all types of sensor devices and providing data dissemination, filtering, and aggregation.

As compared to the related work described herewith, the distinguishing aspects of our FlexRFID middleware solution are as follows: the FlexRFID design aims to provide the applications with a device neutral interface to communicate simultaneously with many different hardware devices, creating an intelligent RFID network. It also provides an interface to access the hardware for the management and monitoring purposes.

The FlexRFID provides all data processing capabilities along with the security and privacy features included in the data processing layer and enforced by a policy based management module for the business events, referred to as the Business Rules layer. The design also permits seamless integration of different types of enterprise applications.

Such approach allows incredible flexibility in the selection of devices, lets companies build their enterprise solutions without handling low-level programming, and allows creating an intelligent sensor network, where RFID readers are choreographed with other devices. There are diverse makes and models of devices, which require a middleware layer that monitors, manages, coordinates, and obtains data from the different devices.

In FlexRFID, these functions are taken care of before processing the raw data and applying business logic to them. Our approach is to use a Device Abstraction Layer DAL that abstracts the interaction with the physical network of devices.

The Device Abstraction Layer of the FlexRFID middleware is responsible for interaction with various devices and data sources independently of their characteristics. UHF, HF , power supply, type, and memory size of a device. The Device Abstraction Module DAM of the DAL provides a common interface to access hardware devices with different characteristics such as protocols, air interface, and host-side communication interface e.

The DAM exposes simple functions like open, close, read, write, etc. The DMMM configures the devices as specified by the upper layers, and also monitors and reports their status Ajana et al.

A diverse set of applications across an organization are interested in the captured information. The captured data are therefore broadcasted by the data dissemination service to all the interested entities. In addition, different applications require different latencies. For example, low latency for the notifications is desired by the applications that need to respond immediately to objects’ events. In contrast, some legacy applications need to receive batched updates on a daily schedule Floerkemeier et al.

For example, it is common that an application is only interested in an event when an object enters or leaves a certain area. Other applications may only need a total count of objects belonging to a specific category rather than a serial number of each object detected. The data aggregation service provides such kind of functionality Floerkemeier et al. Raw data present little value until they are transformed into a form suitable for application-level interactions.

So, from an application perspective, it is desirable to provide a mechanism that turns the low-level captured data into the corresponding business event. For example, a detection of a number of tagged books at the exit door of a library can be automatically translated into a books checked out event. This requirement is taken care by the data transformation service Floerkemeier et al.

The volumes of data generated by the different devices require significant data filtering to extract the most important information. Also, different applications are interested in different subsets of data captured.

There are filtering policies available in the FlexRFID middleware policy repository of the BRL, therefore the data filtering service filters data depending on the filter characteristics provided by the application. This offers flexibility in handling multiple filtering formats Floerkemeier et al. Multiple devices may generate duplicate readings of the data, for example tags in the vicinity of a RFID reader are read continuously.

This results in a large amount of repeated data, and therefore duplicate removal service prevents the reporting of these duplicate data. The application specifies a time window, so that the same data read within it are only reported once Ajana et al.

Usually the rate at which the devices insert data in the channel buffer is slower than the read rate of the applications. However, in case the application is not responsive enough or not executing, the channel buffer gets full, and leads to buffer overflow problem. The data replacement service allows the application to specify the action to be taken in case of channel buffer overflow. The application specifies the data replacement policy stored in the BRL policies repository, which will be executed by the data replacement service Ajana et al.

RFID based tracking solutions could trigger RFID tags attached to the personal belongings to reply with their ID and other private information, therefore increasing the potential of unauthorized surveillance mechanism that would pervade large parts of our lives.

FlexRFID design supports dedicated privacy enhancing feature through the privacy module. The business rules of this module are stated in the privacy policy of the BRL Ajana et al. The BRL is a policy-based management engine that defines the rules that grant or deny access to resources and services of the FlexRFID middleware, and enforces different types of policies for filtering, aggregation, duplicate removal, privacy, and different other services.

This is achieved by determining the policies to apply when an application requests the use of a service in the BEDPL. When an application needs to access a service that is protected by the Business Rules Layer, the request passes through the Middleware Policy Enforcement Point MPEP which asks the Middleware Policy Decision Point MPDP whether to permit or deny access to the service by applying the privacy rule, and how the service will be processed depending on its type.

The MPEP gives the MPDP the authority of decision making; whether or not to grant the application access to the service based on the description of the application attributes, and. The MPDP makes its decision based on the applicable policies stored on the system. Indeterminate is returned when there is an error in processing the request and Not Applicable when no policy that applies to the request could be found Ajana et al.

Policies are operating rules used to maintain order, security, consistency, or other ways of successfully achieving a task. Examples of policies that should be available in the Business Rules Layer are: Access policy, data replacement policy, quality of service policy, and privacy policy.

Different types of applications using the FlexRFID middleware may define rules to detect events and process them using the services provided by the middleware. Primitive events such as observations from readers may lead to actions such as change of location. Sequence events consist of a sequence of primitive events of the same type, defined by the order and closeness of intervals. Composite events are a combination of primitive events and sequence events, and may lead to actions such as aggregation of data.

Here we present some examples of rules enforced by their corresponding policies Ajana et al. The filtering rule filters data according to predefined policies by the applications.

For example, multiple readers may generate duplicate readings. To filter this, the filtering policy will scan data within a sliding window to find if there are duplicate RFID tag readings from multiple readers, and delete the duplicate if it exists.

A policy for duplicate removal could specify that if readings from reader Rx and Ry have the same tag ID value within time T, then one of them is dropped. For example, Reader R1 is mounted at a warehouse departure zone and will scan objects before their departure. The data aggregation rule is used to detect a sequence of ordered events and generate an aggregation relationship. This sequence of events will aggregate as a containment relationship between the pallets and the truck.

Privacy threats in an RFID application can include covert reading, tracking over time, and individual profiling. The privacy rule specifies whether an application has the right to access RFID tag data, can track them over time, and use them to generate events.

The AAL provides various applications with an interface to the hardware devices, through which the applications request the set of services provided by the FlexRFID middleware with hidden complexity Ajana et al.

In the late s, libraries began using RFID systems to replace their electro-magnetic and barcode systems. The RFID self-check systems are increasingly becoming popular since they allow patrons to check-in or check-out many items, rather than one at a time. This reduces the number of library staff needed at the circulation desk. Inventory related tasks could also be done in a fraction of the time, as a portable reader can read a whole shelf of books, and then report which are missing or misplaced.

Moreover, as books are dropped in the book return station, the reader reads the tag and uses the automatic sorting system to return the book back to the shelves.

A RFID tag can be used for both identifying items and securing them, and there is no need to purchase additional tags for security or use security strips separately.

As patrons leave the library, the tags are read to ensure that the items have been checked out. If the item is not checked-out, the RFID readers placed near the exit detect the presence of the tag and trigger an alarm Ayre, A significant impediment to library use of RFID is privacy concerns associated with an item-level tagging.

The tag contains static information that can be easily accessed by unauthorized readers. The privacy issues are generally described as tracking and hotlisting. Hotlisting allows building a database listing the items and their corresponding tag numbers and then using an unauthorized reader to get who is checking out items on the list. Therefore, libraries implementing RFID should use and configure the technology to maintain the privacy of patrons Ayre, Smart library management applications require data to be automatically read, analyzed and written back.

Every patron is issued a RFID tagged library card that stores both personal information and information of the library items borrowed. Then, depending on the permissions, the application updates the borrowing status of the patron and the internal library database or rejects the request.

This prototype aims also at helping library staff to track items placed at the wrong places, and identifying most read documents in the library. This allows the visualization of important events and alerts in real time. The most important events are: item check-in, item check-out, shelf management, and item theft.

In order to illustrate the value and maturity of the FlexRFID middleware, the smart library prototype makes use of its services such as filtering, duplicate removal, transformation, aggregation, and is tested with different devices such as bar code readers, RFID readers, and sensors.

The smart library prototype is developed using Microsoft Visual Studio. RFID technology has gained greater prominence and a higher level of adoption due to its recent advancements and decreasing costs across the years. RFID tags are placed on objects so that they can be uniquely identified. Such a visibility of accurate data brings opportunities for improvement and transformation in various processes of the supply chain, and allows a wide range of organizations to realize significant productivity gains and efficiencies Ajana et al.

Ajana et al. RFID promises to revolutionize supply chains and usher in a new era of cost savings, efficiency and business intelligence. Some of the main benefits of integrating RFID in SCM are: Automatic non-line-of-sight scanning, labor reduction, enhanced visibility, asset tracking, item level tracking, traceable warranties and product recalls, quality control and regulation, and ability to withstand harsh environments Ajana et al.

Major issues that inhibited the adoption of RFID in SCM are: the cost of tags, tag readability, the need for new data structures for RFID data management, data ownership and sharing, standardization, business process changes, and privacy Ajana et al. Demand Management: The use of RFID allows eliminating inaccuracies in data due to human errors, and provides timely data both at the item level and in aggregate about the market demand of a particular product.

Order Fulfillment: Order fulfillment is a key process in meeting customer requirements and improving the effectiveness of supply chain. RFID can reduce the cost of operations in order fulfillment, and enables suppliers to automatically and accurately determine the location of an item, to track its movement through the supply chain, and to make instantaneous business decisions. SCM applications target many aspects depending on supply chaining processes. One of these major aspects is inventory control.

We focused on the use of FlexRFID middleware to provide input to existing tools and applications of inventory control. Streaming: RFID devices are becoming cheaper and widely deployed and it is now increasingly important to perform continual intelligence analysis of data captured.

To relieve the SCM applications from dealing with the streaming nature of data and the fact that the data might be redundant, even unreliable in certain cases, the FlexRFID middleware is able to process such unreliable real time sensing data before delivering it to the backend system. To benefit from such visibility, the SCM participants have to be able to identify the interested situations and react to such situations when they happen.

The events associated with the triggers have to be reported in a timely manner and notification has to be sent to interested SCM participants. Integration: The design of FlexRFID middleware allows it to scale and support different devices and data sources that may be used at numerous points of inventory control such as Point of Sale PoS , and smart Shelves. Report RFID data about location and inventory level in real time so that the inventory control application could place an automatic order whenever the total inventory at a warehouse or distribution center drops below a certain level.

Report and aggregate accurate data at the PoS that will be used by the SCM application to monitor demand trends or to build a probabilistic pattern of demand that could be useful for products exhibiting high levels of dynamism in trends.

Reduction of the Bullwhip effect, which means an exaggeration of demand in upward direction in a supply chain network. FlexRFID will provide accurate and real time information on actual sales of items that can be used for decision making and that will diminish the magnitude of the bullwhip effect.

Reducing bullwhip effect would benefit industries where instances of supply-demand imbalances have high costs attached to them. Capturing data that gives total visibility of product movement in the supply chain.

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