Cel di report master_jan6


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Cel di report master_jan6

  1. 1. SENSOR (RFID) NETWORKS AND COMPLEX MANUFACTURING SYSTEMS MONITORING (COMMSENS): LABORATORY FOR RFID RESEARCH Satish Bukkapatnam Associate Professor Oklahoma State University Stillwater OK REPORT OF WORK CONDUCTED UNDER THE AEGIS OF CELDi STRATEGIC RESEARCH GRANT 2005: “EXPERIMENTAL TEST BED FOR PERFORMANCE EVALUATION OF RFID SYSTEMS” Contributing Members: Jayjeet M. Govardhan Sharethram Hariharan Vignesh Rajamani Brandon Gardner Andrew Contreras Oklahoma State University Stillwater OK
  2. 2. 2 TABLE OF CONTENTS EXECUTIVE SUMMARY ....................................................................................................................3 SECTION 1: INTRODUCTION...........................................................................................................5 SECTION 2: GUIDELINES FOR RFID SYSTEM DESIGN AND DEPLOYMENT PART 1: TAG AND READER DESIGN GUIDELINES..................................................................................10 SECTION 3: GUIDELINES FOR RFID SYSTEM DESIGN AND DEPLOYMENT PART 2: USE CASE MODEL AND ARCHITECTURE OF SAVANT..........................................................28 SECTION 4: SUMMARY OF BEST INDUSTRY PRACTICES & DEVELOPMENTS IN RFID SYSTEMS AND THEIR EXPERIMENTAL INVESTIGATION ...................................................45 SECTION 5: STATISTICAL ANALYSIS AND DESIGN OF RFID SYSTEMS FOR MONITORING VEHICLE INGRESS/EGRESS IN WAREHOUSE ENVIRONMENTS............77
  3. 3. 3 Executive Summary In the late fall of 2004, CELDi approved our proposal on developing "Experimental test bed for performance evaluation of RFID systems." This grant has spurred the development of a laboratory for Sensor (RFID) Networks and Complex Systems Monitoring (COMMSENS) research. This lab is spread over 1000 sq. ft. space in the Advanced Technology Research Center (ATRC) of Oklahoma State University. Our initial efforts under this grant were focused on procuring the instrumentation to create an experimental test bay for RFID systems performance assessment. The test bay consisted of AWID and Alien readers and 200 passive tags. Using this test platform, we have successfully validated a systematic approach, based on combining statistical analysis and Electromagnetic principles, for robust design of RFID systems. Publications on the following three topics have emerged as a result of our investigations: 1. Development of Guidelines for Front/Backend Design of an RFID System, 2. Best Industry Practices in RFID System Deployment, and 3. Statistical Analysis and Design of RFID Systems for Monitoring Vehicle Ingress/Egress in Warehouse Environments Furthermore, in order to facilitate a broad dissemination of research undertaken in the COMMSENS on RFID systems and sensor technologies, a new course on RFID applications in manufacturing systems was created in Spring 2005. This course, open to both undergraduates and graduate students at OSU, is one of the first ones offered on RFID applications in production systems. Collaborating with University of Nebraska, we have offered a 6-hour tutorial on RFID fundamentals and Applications at CELDi pre-conference event during Spring 2005. The course content for the next offering of RFID course in the spring of 2005 has been re-designed taking into account an increase in enrollment levels and the need to include the developments that have taken place since the last offering of the course. In fact, many developments have taken place in the recent times that can lead the industries towards efficient adoption of RF and sensor technologies. We strongly feel that more background preparation is necessary in order to bolster the exponential growth of these technologies as well as their adoption in the real world applications.
  4. 4. 4 A research is never complete or successful unless it can reach the end users, namely, the industries. Towards this end, we have initiated partnership projects with GM, FAA Logistics Center, and Oklahoma Department of Transportation. This allows us to share our knowledge of RFID systems and sensor technologies with, in some sense, the business world. We have also initiated dialogues with SUN RFID Center, and RFID component vendors, including manufactures like Alien and AWID, RFID consultants, and academic institutions, particularly, the University of Nebraska. We have also been successful in attracting 12 students to participate in our research activities. Their qualification levels range from undergraduate to graduate standing (M.S. to Ph.D. level) with diverse backgrounds such as from mathematics, mechanical and aerospace engineering, industrial engineering, and electrical engineering. Their passion for advancing RFID systems and sensor technologies is a common thread that binds them all. COMMSENS lab research conducted under the aegis of CELDi, thus, has had a positive impact on the students involved as well as on our knowledge and understanding of RFID systems and sensor technologies.
  5. 5. 5 Section 1: Introduction 1.1 Background The Sensor Networks (RFID) and Complex Manufacturing Systems Monitoring Research (COMMSENS) lab was established in 2004 at the Advanced Research Center (ATRC) of Oklahoma State University in Stillwater, OK. The COMMSENS Lab facilities are spread over 1000 square feet at the ATRC for hosting test-beds for RFID and RF Sensing research. Lab facilities include antennae and readers from Alien and AWID, as well as 200 passive tags of various specifications. The lab also features RF sensing devices like motes from moteiv® (IEEE 802.15.4 compliant) for wireless mesh networking. All RFID information is processed in a Linux server that uses the SUN JAVA RFID software package with an Application Server and Enterprise Manager. Oracle 10i is used as the database to store information collected from our experiments. New experimental test bays with the latest Gen 2 specific hardware and software are being set up for the future applications. 1.2 Mission The mission of the lab is to study the principles of monitoring real world complex systems by harnessing information from a network of wired and wireless sensors. Such applications include various complex manufacturing machines, processes, enterprises, consumer products, and infrastructures like bridges, pipelines and railroads. Furthermore, we are attempting to harness large amounts of sensor data to bring substantial improvements to the design and operations, particular in quality and integrity assurance, of these engineering systems, which include many precision manufacturing machines and processes, the Internet, supply networks and infrastructure and lifelines systems. Overall, the objectives of our research are the following: • Study the origins of complicated patterns in sensor signals from manufacturing machines, processes, and specific infrastructure and lifeline systems
  6. 6. 6 • Derive theory and methods to capture the dynamics underlying these signals for quality and integrity monitoring 1.3 Accomplishments The following is a list of accomplishments and awards received as a result of COMMSENS research: • The lab efforts have received support from NSF, CELDi (the nation’s largest Industry-University consortium focused on logistics), General Motors, FAA, and the US Department of Transportation to the tune of $0.9M during 2004- 05 • A new course focusing on RFID system applications in manufacturing and engineering systems (one of the firsts of its kind in Industrial Engineering) offered in spring 2005 • A systematic statistical approach for experimental design of an RFID system developed. Also the research has yielded new principles for harnessing information on the complex (nonlinear and stochastic) nature of the process underlying signals from RFID and other sensor networks • The research has yielded 25+ journal papers and 20+ publications in refereed conference proceedings apart from being the basis for 3 PhD theses • Currently 16 students including 3 PhD, 5 MS thesis, 2 MS creative component, and 3 undergrad students take part in the lab activities (these include 3 members from underrepresented groups) 1.4 Education Accompanying the research at the COMMSENS lab are several educational components, which include: • A new course on RFID Applications in Manufacturing Systems offered in Spring 2005 • Guest lectures offered by several prominent industry speakers and implementers of RFID to share ideas and discuss technical issues surrounding RFID; thus supplementing course material with practical aspects • Field trip to SUN-RFID Testing Center in Texas was organized where pallet level and item level readability in conveyor environment was demonstrated
  7. 7. 7 • White papers that describe the quantitative and qualitative aspects of deploying RFID in a given environment have been published ─ papers detailing recent experiments are forthcoming • A 6 hour tutorial on RFID fundamentals and applications offered to industry participants as part of 2005 CELDi pre-conference event 1.5 Capabilities Capabilities and resources of the COMMSENS lab are the following: • Test bays and a statistical approach for RFID system design and deployment • New design method based on combining statistical and electromagnetism principles to screen parameters affecting an RFID system performance • Framework to undertake customized ROI studies • RFID /RF sensor deployment, instrumentation and integration studies for quality, integrity, performance monitoring and surveillance • Simulation based evaluation of decision enrichment using RFID/RF sensor information • A new simulation approach based on continuous flow dynamics for fast evaluation of system performance • Quality and integrity monitoring of complex machines and processes including precision machining and other manufacturing operations • Sensor-based health monitoring of complex structures for condition-based maintenance and Integrity assurance • Characterization of nonlinear stochastic dynamics underlying in large complex systems including various manufacturing machine operations, smart material and structural systems, large supply and transportation networks, and the Internet. See lab photographs below
  8. 8. 8 1.6 People The people involved in COMMSENS research come from a variety of backgrounds such as mathematics, industrial, mechanical, and electrical engineering. The following is a list of the people involved with COMMSENS research at OSU: • Satish T. S. Bukkapatnam, Ph.D., Associate Professor Topic: Overall Project Supervision • Brandon Gardner, Graduate Student, Dept. IEM Topic: Financial Model of RFID Systems • Sharethram Hariharan, Graduate Student, Dept. IEM Topic: Improved Decision Making in Business Process by the use of Markov Decision Process • Vignesh Rajamani, Graduate Student, Dept. EE Topic: EM Theory Applications in Antennae and RFID Systems Design Foam Metal Liquids Linux SystemHigh Tag Density Reader & Antenna Setup Bubble Wrap EDS Reader & Antenna setup
  9. 9. 9 • Jayjeet Govardhan, Graduate Student, Dept. IEM Topic: Technical Aspects of RFID System Design • Alicia Jones, Undergraduate Student, Dept. IEM Topic: RFID Sensor Documentation • Andrew Contreras, Undergraduate Student, Dept. MAE Topic: Gen 2 System Analysis • Amjad Awawdeh, Graduate Student, Graduate Student, Dept. EE Topic: RFID Sensor Applications • Tanay Bapat, Graduate Student, Dept. IEM Topic: Documentation of RFID Coursework • Randy Clark, Undergraduate Student, Dept. of IEM Topic: RFID front-end design • Gerardo Myrin, Undergraduate student, Dept. of IEM Topic: RFID front-end design • Vipul Navale, Graduate student, Dept. of IEM Topic: RFID front-end design • Chetan Yadati, Graduate Student, Dept. of IEM Topic: Implementation of Use Case Analysis in RFID middleware development 1.7 Organization of Report This report is divided in to four main components: I. Guidelines for RFID System Design and Deployment Part 1: Tag and Reader Design Guidelines II. Guidelines for RFID System Design and Deployment Part 2: Use Case Model and Architecture of Savant III. Summary of Best Industry Practices & Developments in RFID systems and their experimental investigation IV. Statistical Analysis and Design of RFID Systems for Monitoring Vehicle Ingress/Egress in Warehouse Environments
  10. 10. 10 Section 2: Guidelines for RFID System Design and Deployment Part 1: Tag and Reader Design Guidelines Summary The design and selection of appropriate RFID system components is usually among the first steps in the implementation of an RFID system. Over twenty parameters govern the performance of an RFID system in a given environment. This document is the first of a two part series that guidelines for developing a basic RFID system for a particular application and introduces the relevant RFID fundamentals concepts. 2.1 Introduction to RFID Radio frequency identification (RFID) is a generic term used to describe the technologies that harness radio-frequency waves to transfer data between a reader and a tag to identify, categorize and track objects. RFID is fast, reliable, and does not require physical sight or contact between reader and the tagged object. An RFID system consists of tags (also known as transponders), readers and a computing infrastructure for storing and analyzing the data received from the reader. A transponder is usually a memory device (e.g. Electrically Erasable Programmable Read-only Memory EEPROM) fitted on the object to be identified. It contains information to uniquely identify an object. The reader is capable of generating, receiving, demodulating and deciphering RF signals. As summarized in Figure 1, the reader sends RF signal into the environment. As soon as a tag comes into the reader’s RF electromagnetic field, the tag circuit sends signals back to the reader, thus identifying the object. This identification technology can be used for real time object tracking, goods and/or asset management, etc. The tags can be classified into various types depending on whether they are active or passive, read only and/or writable, etc. The readers too have different specifications like frequency, type of data transmission method, etc. The selection of the tag and reader attributes strongly impact the performance of the RFID system.
  11. 11. 11 Figure 1: Components of an RFID System [1] 2.2 RFID Tag Selection Guide The selection of RFID tag plays critical role in the successful deployment of an RFID system. The appropriate tag should conform to the required functionality expected in the given field, application, environmental conditions, and government’s regulations on the frequency use. 2.2.1 Parameters considered in Tag Selection: Following are the seven major parameters [2] considered in the process of tag selection (See Figure 2): 1. Application Requirements 2. Read Range 3. Frequency 4. Functionality 5. Environmental Conditions 6. Form Factor 7. Standard Compliance EPC/ISO
  12. 12. 12 Figure 2: Parameters Affecting Tag Selection Application Requirements RFID system applications include dock door reading, asset management, and transportation, inventory management in warehouses, conveyor reading, and point of sale reading, handheld mobile reading and smart identification card systems. These are the typical examples based on our observation. [The different applications and estimated growth of the global market for RFID systems can be seen in Figure 3].The application determines where and what objects are to be tracked. The application- imposed constraints, ultimately determine the choice of the read range. Figure 3: Estimated growth of global market for RFID systems[3]
  13. 13. 13 Read Range Read Range is the farthest distance between reader and tag at which reader can read the tag. Determinants of read range include frequency of operation, Electromagnetic Interference (EMI) levels, power of the reader (which is usually limited by Federal mandates), tag functionality, size of stored data, read time, relative velocity between the tagged object and the reader, and antenna design. The major factor among these is the frequency of operation based on the read range requirement Frequency Range The frequency ranges are categorized as Low (LF), High (HF), Ultra High (UHF) and Microwave frequency. The choice of frequency range depends upon the application / performance requirements and the regulatory requirements. The actual frequency values vary as per geographical regions. For US and Canada, 13.56 MHz is considered as HF and UHF ranges from 902 MHz-928MHz. This variation in actual frequency range values for geographical regions is a hindrance in developing a unique RFID system that can be deployed worldwide. Refer table for more details [4], [5]
  14. 14. 14 Table 1: Geographical Variation in Frequency Ranges Frequency Zones Low Frequency(LF) High Frequency(HF) Ultra High Frequency(UHF) Microwave US and Canada 125 - 134 KHz 13.56 MHz 902 - 928 MHz 2.4 - 2.48 GHz Europe 125 - 134 KHz 13.56 MHz 868 - 870 MHz 2.4 - 2.48 GHz Japan 125 - 134 KHz 13.56 MHz 950 - 956 MHz 2.4 - 2.48 GHz Functionality Based on functionalities, tags may be classified as passive, active and semi- passive. Passive tags are not supported with batteries, but they are powered by the energy supplied by reader field. Passive tags are cost effective and used in supply chain for identifying and tracking objects. Active tags are battery powered. See Figure 4. They can be used for long-range applications. Semi-passive tags are supported with batteries, but they are activated by the reader field. These tags are used for capturing additional details like temperature, humidity, etc. Figure 4: Tag Functionality Form Factor Form factor determines the size and shape of a tag. Generally, larger tags provide better range performance over tags with smaller form factors. The trade off analysis
  15. 15. 15 between the size of the tag and required range performance must be carried out while selecting tag for particular application. See Figure 5. Figure 5: RFID system classification based on tag functionality Environmental Conditions Environmental conditions and materials near RFID systems can affect RF field parameters like reflectivity/refractivity, absorptive and dielectric properties (detuning). Hence, tag performance is dependant upon materials near the tag and environmental conditions like temperature, humidity, etc. Different frequency ranges experience different degree of effects due to above materials. For example, the attenuation of reflectivity increases with the frequency. The suitable frequency range and tags should be chosen in order to minimize these effects. Table 2: Effect of Materials on RF field Material Effect on RF field Cardboard Absorption (moisture), Detuning (dielectric) Conductive liquids Absorption Plastics Detuning (dielectric) Metals Reflection Groups of cans Complex effects (lenses, filters), Reflection Human body / animals Absorption, Detuning (dielectric), Reflection
  16. 16. 16 RFID Standard Compliance In order to avoid interferences from other RF applications like electric and radio equipments and to achieve interpretability between different tags and readers, RFID system standards are being developed. These standards deal with air-interface protocol, data content, conformance with regulatory requirements, and application. Two major standards available today are Electronic Product Code (EPC) Global and ISO/IEC standards. • EPC Standards EPC has specified standards for tag data content, communication between tag & reader (air-interface protocols), reader protocols, Savant specifications, Physical Mark-up language (PML) specifications, and Object Naming Service (ONS) specifications for HF and UHF ranges. There are two versions of these standards. Version 1 is already in use and version 2(Generation 2) is ratified and going to be adopted in near future. As per this standard, data is stored on the tag, in the format as shown in Figure 6. Version 1 is already in use and version 2(Generation 2) is ratified and going to be adopted in near future. Companies like Texas Instruments, Impinj, Philips Semiconductors, Alien Technology, Symbol Technologies and Intermec Technologies have announced their plans to manufacture Gen 2 tags. Figure 6:Tag Data Partition
  17. 17. 17 Table 3: Tag Classification based on EPC Global Protocol [4] EPC Class Description Functionality Remarks 0 Read Only Passive tags Data can be written only once during tag manufacturing and read many times 1 Write Once and Read only Passive tags Data can be written only once by tag manufacturer or user and read many times 2 Read/Write Passive tags User can read/write data many times 3 Read/Write Semi-passive tags Can be coupled with on board sensors for capturing parameters like temperatures, pressure, etc. 4 Read/Write Active tags Can be coupled with on board sensors and act as radio wave transmitter to communicate with reader • ISO/IEC 18000 Series ISO & IEC have established Joint Technical Committee to address technology standards. Within JTC -1, Subcommittee 31, Work Group 4 deals with RFID. ISO 15693 and ISO 18000 series provide air interface standards for communication between tag-reader and reader-tag at LF, HF, UHF and microwave frequencies. These standards also specify parameters like data encoding rules, data transmission rates, types of signal modulations and anti-collision protocols [6], [7]. • 18000-1 Part 1 - Generic Parameters for the Air Interface for Globally Accepted Frequencies • 18000-2 Part 2 - Parameters for Air Interface Communications below 135 KHz 18000-3 Part 3 - Parameters for Air Interface Communications at 13.56 MHz
  18. 18. 18 • 18000-4 Part 4 - Parameters for Air Interface Communications at 2.45 GHz • 18000-5 Part 5 - Parameters for Air Interface Communications at 5.8 GHz (Withdrawn) • 18000-6 Part 6 - Parameters for Air Interface Communications at 860 to 930 MHz • 18000-7 Part 7 - Parameters for Air Interface Communications at 433 MHz Efforts are initiated to form a unique standard that will avail a common platform for widespread adoption of RFID technology all over the world. 2.3 Market Survey Below is the summary of available tags and tag manufacturers in today’s market. This summary of various tag manufacturers, tag functionalities and their features will help user to select appropriate tag for his application. Table 4: RFID Tag Market Survey Manufacturer Model Frequency Functionality Standard Remark ALL-9238, ALL-9250, ALL-9254 UHF (902-928 MHz) Passive and 64 bit EPC Global Class 1 General purpose item tracking, suitable in metallic environment Alien Technology [8] ALL-9338, ALL-9354, ALL-9334 UHF (902-928 MHz) Passive and 96 bit EPC Global Class1 General purpose item tracking Dual Dipole UHF (902-928 MHz) Passive 112,128 bits EPC Global Class 0 Matrics /Symbol Technologies [9] Single Dipole UHF (902-928 MHz) Passive 112,128 bits EPC Global Class 0 General labeling, carton & pallet labeling, and pharmaceutical labeling
  19. 19. 19 Manufacturer Model Frequency Functionality Standard Remark Hitachi [10] Mu-chip 13.56 MHz Passive and 128 bit EPC Global Class 1 0.4mm x 0.4mm x 0.060 mm size. Can be used in currency notes for authentication Tire Tag Insert UHF 869 /915 MHz Passive Class 1 Used in tire tagging. Typical Applications include work in process (WIP), quality control Container Tag UHF 915 MHz Passive Class 1 Pallet, carton and container tracking Intermec Technologies [11] CIB Meander Free Space Insert 2.45 GHz Passive Class1 Electronic Article Surveillance tags, and inventory management
  20. 20. 20 2.4 RFID Reader Selection Guide A reader is critical to a successful deployment of a RFID system. The appropriate reader should fit with required functionality based on the application, environment conditions and country’s frequency norms. This section presents the criteria for reader selection. 2.4.1 RFID Reader Selection Guide Following are major parameters considered in the process of reader selection: 1. Application Requirement 2. Frequency Range 3. Read/Write Range 4. Functionality of Tag 5. Standard EPC/ISO Air Interface Figure 7: Parameters Affecting Reader Selection
  21. 21. 21 Application Requirement The shape, size and functionality of a reader change according to the application of the RFID system. Some of the common RFID systems are conveyor reading, dock door reading, forklift reading, mobile reading etc. Frequency Range A suitable reader, for a given application, can be selected to match the frequency range chosen (LF, HF, UHF or Microwave). Multi-frequency readers can be chosen if the application requires using both short as well as long read/write ranges. Read/Write Range Read range is based on the frequency chosen, functionality of the tag and power of the reader. Write range is the distance from which a reader can write tags. This range is usually 70% of read range. Functionality of Tag Active and passive tags talk to reader using different air-interface protocols. Hence, reader should support the functionality of tag. A multi-protocol reader which supports different protocols is seen as the best solution and is quiet popular in today’s market. Air Interface Protocol Reader should support the air-interface specifications provided by either EPC or ISO standards. The reader and tag should comply with these standards. Some readers can support EPC as well as ISO standard protocols and these are the most popular ones in the market. Other Factors Other factors like the number of tags read per second, interface to the host and anti-collision (Tag collision and Reader collision) are also important. Based on need of application, suitable parameters can be chosen for the selection of the reader. Anti- collision requirement can be the most demanding feature. Reader should recognize
  22. 22. 22 uniquely the identity of tags lying in the range of the reader. ISO and EPC protocols define anti-collision implementations. 2.5 Market Survey Below is the summary of readers and their manufacturers in today’s market. Table 5: RFID Reader Market Survey Manufacturer Model Frequency Type Standard Remark ALR- 9780 UHF 902-928 MHz Fixed EPC Global Class1 Compatible with any LAN network, perfect match for applications where high- speed, highly reliable reads are required. Alien Technology [8] ALR- 9640 UHF 902-928 MHz Fixed EPC Global Class1 Low-cost, flexible industrial reader, The reader electronics and antenna reside in a single package, eliminating external antenna cables, resulting in a simple and inexpensive installation. Matrics/Symbol Tech [9] AR-400 UHF 902-928 MHz Fixed EPC Class 0 and Class 1 Multiprotocol reader- Supports all EPC- compliant passive RFID tags, Allows dynamic data updates for broader application support and provides flexibility in tag usage, EPC Generation 2 Upgradeable
  23. 23. 23 Manufacturer Model Frequency Type Standard Remark Samsys Technologies [12] MP9320 MP9310 UHF 902-928 MHz Fixed EPC Class 0, 0+, Class 1, ISO18000- 6A, 6B, 6B "fast", Philips U- code 1.19, 1.19 "fast", Intermec Intellitag, EM Marin 4022, 4222, 4223 Flexibility in supporting multiple tag protocols, multi-regional regulatory compliance, and programmability for a multitude of EPC applications environments Configurable for North America FCC (902-928 MHz) and European ETSI (865-869 MHz) regulatory environments
  24. 24. 24 2.6 Boilerplate for RFID Component Selection of a Typical Warehouse 2.6.1 Warehouse Operations RFID technology has great potential in streamlining warehouse operations to meet the dynamic market demand. We have developed RFID tag and reader selection guide which can be used to configure the RFID system for particular applications. This section contains a brief discussion of the various warehouse operations and how the RFID tag- reader selection guide can be used to configure RFID system for these operations. 2.6.2 Assumptions In preparing the above boilerplate, the following assumptions are made: 1. The warehouse under consideration is used only for consumer goods. 2. Case and pallet level tagging are the only ways to deploy RFID tags on the products. (Item level tagging is not considered). The key operations in warehouse are: 1. Receiving 2. Inspection 3. Bulk Storage / Cross Docking 4. Order Picking and Sorting 5. Shipping Figure 8: Material Flows in a Warehouse
  25. 25. 25 The above operations can be defined briefly, as follows and depicted in Figure 8 and explained below: 1. Receiving Incoming truck is identified and routed to appropriate receiving dock. At receiving dock, products (raw material, semi-finished, or finished) are unloaded. 2. Inspection The quality (mostly visual inspection for damage detection of cartons) and quantity of received products is assured as per requirement. The faulty products are separated. 3. Cross Docking Cross docking is the process of unloading material from one truck or trailer and loading it to outbound truck or trailer without storing it in warehouse. 4. Bulk Storage Received products are identified and routed to appropriate storage location in warehouse. Generally, the products are stored in carousals, racks or on pallets. 5. Order Picking and Sorting Once the order is received, the products are picked in correct quantity. Once order is filled, the products are routed to correct shipping dock. 6. Shipping The shipment of right products to the right customer is ensured.
  26. 26. 26 Figure 9: Operations in Warehouse: Receiving, Inspection, Bulk Storage/Cross Docking, Order Picking/Sorting, Shipping 2.6.3 RFID tag and reader selection The various parameters that should be considered for tag and reader selection are application requirement, frequency, read range, functionality of tags, environmental conditions, form factor and standard/compliance. The RFID applications in warehouse include, dock door or portal reading, forklift reading, conveyor reading, stretch wrap reading and overhead reading. Based on these applications, there is a need of RFID system that can track tags placed on individual pallets and cases, at long distances and in large quantities. Low frequency RFID system has read range of few centimeters. For High Frequency systems, range is up to 1m. For Ultra High Frequency (UHF) systems range can be obtained more than 1 m and up to 15m or even more. For above mentioned warehouse applications, UHF is the best suitable frequency due to longer read range and fast and large amount of data transfer. The environmental conditions and the nature of the product also play an important role in selecting RFID frequency range. The presence of metals and liquids near RFID systems can have deleterious effects on RF field like reflection/refraction and absorption. In the
  27. 27. 27 case of a consumer goods warehouse, UHF range can yield better results by proper shielding system environment. Passive tags are the best suitable for warehouse operations. The supplier can fix a tag with a unique ID on the cases and pallets. This unique ID can be linked to specific information about individual product ID, product type, product name, date of manufacturing and batch number, etc. Form factor plays an important role the range of any RFID system. In the case leveling tracking, usually a "slap and ship" kind of tag is deployed. In case of pallet level tagging various forms of tags such as plastic coated tags, label tags etc. can be used. These kinds of tags are cost effective for warehouse applications. EPC Global Class 0 tags can be used where the structure of tag information like the number of object classes is fixed and the tag user does not require programming of the tag at it site. When the product range changes are very frequent EPC Global Class 1 tags can be deployed. In this case the tag user has the freedom to program the tag according to its specifications where except the Header partition, all other partitions are programmable. The user can use its own programming techniques for better security.
  28. 28. 28 Section 3: Guidelines for RFID System Design and Deployment Part 2: Use Case Model and Architecture of Savant Summary Software products like any other engineered product should be based on solid analysis and realistic modeling. A brilliant solution applied to a wrong problem causes as much, if not more, damage as a bad solution to the problem. Software systems unlike other engineered products are not physically measurable and hence the relevance of analysis and modeling becomes more critical in their development. We attempt to define and describe the middleware of a typical RFID system, called Savants through the use of IBM Rational Unified Process(RUP)® [13]. 3.1 Introduction 3.1.1 RFID technology Radio Frequency Identification has recently gained much attention owing to the various mandates by commercial and federal organizations [14], [15]. The concept of using Radio frequencies to store and retrieve information from products has suddenly made many hitherto fantasies very practical. Enterprises are keenly interested in the economics of such a solution. The possibility of tracking every product and being able to store considerable data into each of them has opened up possibilities of unique identification and total automation. As can be expected, however, the technology is still not completely mature in its implementation. There exists a definite lack of benchmarking the performance of various RFID tags has been seen as a major hurdle to be crossed before large-scale adoption can be carried out. RFID solutions typically contain four main components: Tag readers, the Middleware, the Applications that use the RFID data and the tags themselves. From a systems engineering perspective, the performance of components on deployment makes a very interesting study. Clear guidelines, however, on the specifications of each of these
  29. 29. 29 components will go a long way in properly understanding the benefits of an RFID solution. 3.1.2 Savants The middleware components of an RFID solution are collectively called the Savant. They are the most important links that collect raw data and convert it into information that can be understood. Savants are primarily intended to collect, filter and aggregate data that are derived from the readers. Their primary functionalities also include interfacing with other enterprise applications that wish to make use of the information they have collected. The tags read by the tag readers have a unique identification code associated with each of them. Currently there are two standards associated with naming the products - the ISO code[16] and the EPC code [4]. These codes contain information regarding the manufacturer, the current owner, the product type and much more. The savants are expected to collect the tag data and filter out the replications and smoothen out the data set and persists the so collected information. We will examine the functionalities of the savants in more detail in section2. 3.1.3IBM® Rational Unified Process® IBM Rational Unified Process (formerly known as Rational IBM Rational Unified Process) is a software engineering paradigm that specifies a UML [17] based methodology for developing systems. Although the UML is generic and can be applied to the design and development of any system we primarily apply it to the software engineering process in this paper. RUP is IBM Rational Unified Process, or RUP®, is a configurable software development process platform that delivers proven best practices and a configurable architecture [13].Our primary focus in this paper is to apply RUP in an effort to understand the functionalities of a Savant in clear detail and come up with a generic architecture for the system.
  30. 30. 30 3.2 Software Requirements Definition 3.2.1 Goal To develop and deploy a middleware system that enables effective communication between the tag-readers and various other external software applications. 3.2.2 Top level requirements definition 1. The system should be able to recognize each reader and gather required data from it and be able to handle exceptional situations like reader breakdown. 2. The system should be able to perform aggregation activities like counting the number of items, rate of filling and emptying of aisles/locations of item storage, Positional counts etc. 3. The System should be able to filter the gathered data so as to help derive useful information from them. 4. The system should be able to convert gathered data into proper data formats (PML). 5. The system should be able to persist the data gathered into a predefined repository. The system should also be able to communicate with the repository and perform query response activities. 6. The system should be able to communicate with other external applications like ERP systems (may be other savants themselves) to enable decision making activities. 7. The system should be able to allow a web user to logon and view various statistics related to the current status of the data gathered. That is, there should be a web interface for viewing the information generated by the savant using the data gathered from the tag reader. 8. The system should be configurable, i.e. it should be able to recognize and understand various product code specifications
  31. 31. 31 3.3.2 Requirements analysis RUP® suggests that the requirements analysis should be carried out using Use case diagrams. Use case Diagrams are one of the five Diagrams in Unified Modeling Language which forms the basis for the Rational Unified Process. They are central to the modeling of the behavior of the intended system. They aid us in visualizing, specifying and documenting the intended behavior of the system. They adopt a black-box view of the system allowing users to specify just the intended use of the system. This paradigm allows developers to separate the implementation of the system from its interface. Components of a Use case diagram • Use cases: A use case is a description of a set of sequences of actions, including variants, that a system performs to yield an observable result of value to an actor [17]. It is graphically represented as an ellipse. Typically use cases are represented as verbs. • Actors: An Actor represents a coherent set of roles that users play when interacting with these use cases [1]. They typically represent a human, a hardware device (like tag readers) or even other systems (like other systems). In modeling terms they represent entity being serviced by the use cases. • Relationships: Use cases can exhibit aggregation, generalization or just association relationships. Several stereotypes are used to qualify the relationships between use cases and actors. Relationships between use cases are also allowed. • Notes and Constraints: Notes and any specific constraints can also be stated in an use case diagram Use Case analysis of Savant We first start with the detection of actors, use cases and then the relationships respectively. Actors Actors in practical terms are the stakeholders of the system under consideration. Any change in the system affects the actors alone directly. We expect the following actors for the savant.
  32. 32. 32 1. Web User: Although this actor could be modeled as a part of the Applications, we choose to model him separately since, the roles and requirements of this actor are very specific and to an extent different from that of the Applications. This actor is intended to use the savants directly to gather product information. He is expected to view the current status of the product inventory. His set of requirements are as follows: (a) Login (b) Logout (c) View the current status of the RFID installation 2. Tag Readers: The relation between the tag holders and the savant is an inverse relation in the sense that the services are expected by the savant than by the tag reader itself. However since the model is for the savant, we try to capture the requirements as if the tag reader requests for it. The following are the requirements of the tag reader: (a) Identify Tag reader (b) Process Tag reader data (c) Process Control 3. Applications: These are other software systems which use the data gathered by the savant to perform other activities. Although, the requirements for the Applications are custom defined for each deployment, we assume a least common set of requirements for the current effort. Other requirements could be modeled as extensions of the existing set of requirements and can easily be accommodated. The following are identified as the requirements for the Applications (a) Identify and recognize applications1 (b) Process Application queries 2 (c) Cache queries (d) Get PML3 1 This could become a critical requirement when the savant information is transacted between different enterprises automatically, since in such a situation, the savants would have to recognize the message headers from the enterprise applications 2 Applications could be monitoring the reader information in real time. 3 Applications sometimes prefer data to be in particular formats so that they could
  33. 33. 33 Use Cases Use cases capture the behavioral description of the system. They formalize graphically the functional requirements of the system. Although there are no formal set of rules in detecting the use cases, we try to detect the use cases by as king the following questions 1. What functions does each actor require from the system? 2. What inputs does the system need? 3. What outputs does the system provide for each role? 4. Does the actor need to create, destroy modify or store some kind of information? 5. Does the actor require the system to identify/validate access? Basing on the above questions the following use cases were detected. 1. login Assumptions: • The user is registered Main flow: • The user presents his username and password • The System recognizes the user and authenticates him 2. logout Main flow: • The user logs out • The system records the changes if any and stops all transactions initiated by the user 3. view Main flow: • The user requests the system to show him specific details. • The system creates a view with the requested details and presents it to him Alternate Flow: • The user is unauthorized to view the requested details • The systems informs the user about his restrictions and asks him to understand them. An ideal example would be an XSLT engine which could translate the PML to any other ML
  34. 34. 34 reformulate his request 4. process data Assumptions: • The interface of the tag reader is known to the savant Main flow: • The savant strips out the headers and converts the data into more a compact form 5. process control Assumptions: • The interface of the tag reader is known to the savant Main flow: • The savant instructs the tag reader to perform specific activities Alternate Flow: • The savant is not able to communicate with the savant • The savant generates an alert displaying the status 6. identify reader Main flow: • The system recognizes the location indicators in the message headers • The system recognizes the reader id Alternate Flow: • The message headers carry an unregistered savant id or location id • The system generates an alert displaying the misbehaving reader particulars 7. process EPC data Main flow: • The system recognizes EPC headers • It extracts the EPC codes from the tag reader data • It runs preliminary consistency checks to determine if the data obtained is good Alternate Flow: • Corrupt data is obtained
  35. 35. 35 • The savant initiates a re-read 8. process ISO data Main flow: • The system recognizes ISO headers • It extracts the ISO codes from the tag reader data • It runs preliminary consistency checks to determine if the data obtained is good Alternate Flow: • Corrupt data is obtained • The savant initiates a re-read 9. perform maintenance Main flow: • The system performs maintenance activities of the readers. This includes, checking the communication link between the reader and the savant and similar activities 10. handle interrupts Assumptions: • The interrupt handling procedures are well defined Main flow: • The savant recognizes the interrupt • It initiates the interrupt handling procedure 11. initiate reads Assumptions: • Either there has been a ’bad read’ or there is a specific instruction by an authorized application to initiate the reread process Main flow: • The system identifies the reader to be instructed • It initiates the reread procedure 12. recognize reader id Assumptions: • The reader id is registered
  36. 36. 36 Main flow: • looks up the reader id and checks if it matches any existing entry 13. recognize reader location Assumptions: • Reader id has been recognized Main flow: • Obtains the reader location using the reader id 14. identify application Assumptions: • Application interface is known Main flow: • Savant associates the application with permissions and restrictions • Savant associates the application with data formats 15. cache queries Assumptions: • Valid queries have been made Main flow: • Stores both the query and the result in a local cache for further usage Alternate Flow: • The result of a cached query has components which have changed since last query • The savant discards the cached information 16. get PML Assumptions • The XSD for the PML is known Main flow: • The system creates a view specific to the PML document • It Converts the view into PML 17. process queries Main flow: • Checks if there is any cached result
  37. 37. 37 • If there is one then the system displays it • Otherwise, the system initiates a fresh query to the local persistence. Alternate Flow: • There is an invalid query • The system informs the application 18. filter data Main flow: • The system checks the data obtained • It filters out the redundant information from the data and smoothens it out 19. aggregate/create view Main flow: • Creates a view from existing data 20. persist Main flow: • Stores the filtered data into predefined data structures Table 6 : Use Case Nomenclature Number Use Case Questions motivating the discovery of Use case Software Requirements traced to Use case U1 login Q5 SR7 U2 logout Q5,Q4 SR7 U3 view Q1,Q3 SR7 U4 process data Q1,Q2,Q3 SR1,SR8 U5 process control Q1 SR1 U6 identify reader Q2,Q4,Q5 SR1 U7 process EPC data Q1,Q2,Q3 SR1,SR8 U8 process ISO data Q1,Q2,Q3 SR1,SR8
  38. 38. 38 Number Use Case Questions motivating the discovery of Use case Software Requirements traced to Use case U9 perform maintenance Q1 SR1 U10 handle interrupts Q1 SR1 U11 initiate reads Q1 SR1 U12 recognize reader id Q2,Q4,Q5 SR1 U13 recognize reader location Q2,Q4,Q5 SR1 U14 identify application Q2,Q5,Q4 SR6 U15 cache queries Q1,Q2,Q3 SR5 U16 get PML Q1,Q3 SR4 U17 process queries Q1,Q2,Q3 SR5,SR6 U18 filter data Q1,Q2,Q4 SR3 U19 aggregate/create view Q1,Q3 SR2,SR5,SR6 U20 persist Q4 SR5
  39. 39. 39 Figure 10: Use case diagram 3.4 Architecture Architecture of a system depicts the bridge between the actual design and the requirements model. It tells us meta-relationships between functionalities and structural components of the requirements model. We depict a generic architecture for the design of savants which can be implemented through the use of any set of coherent technologies. In the later section we also present a case study of the Sun Java RFID solution’s savant architecture.
  40. 40. 40 Architectural components are hard to find. Some of them naturally classify into many architectural modules. Hitting the right granularity of modules becomes a critical decision during the architecture phase. We as earlier use a question based approach to find architectural components. Our belief is that with this approach the right granularity is easier to attain. Some of typical questions we ask ourselves to detect architectural components are: 1. Are there functional requirements, which operate with the same interfaces? 2. Are there use cases, which have generalization, aggregation relationships? 3. Are there use cases, which have tightly coupled functionalities? 4. Are there possibilities that use case implementations could be varied over time? 5. Are there use cases related to specific functionalities like security etc? In answer to these questions and a few more, we detected that there were the following architectural components: 1. Reader Interface module: This component handles all the reader specific activities like reader types, physical reader interfaces etc 2. Event Management module: This component handles all event triggered activities like parsing the data received, filtering the received data, initiating rereads in case of bad data and such 3. Information processing module: This module handles the semantics of the gathered data. It performs aggregation and persistence related activities 4. Application Interface Module: This component allows for application level customization where the system is configured to interact with particular application types 5. Messaging layer: This layer forms the bus for message transactions between different modules 6. Data Access and Filtering: This module handles the different code formats of the data and filtering of received data 7. Control module: This module handles all physical control activities to be
  41. 41. 41 performed by the savant with respect to the tag reader 8. Persistence manager module: this module handles the local and real time persistence Figure 11: General Architecture of a Savant 3.5 Case Study: Sun JAVA ™System RFID Software [18] Sun Microsystems middleware or Savant are geographically distributed servers which are connected to RFID readers at various locations, collect data from them, and also pass on the control signals from the ERP systems. Savants in this system: • Gathers, stores, and processes EPC data from one or more readers • Smoothes data i.e. filters redundant read values • Corrects duplicate reader or tag entries • Stores and also forwards data up or down the architecture • Monitors for events like low-stock level • Passes up the data to the ERP systems used by the company either continuously or on a periodic basis Information that is typically collected by a Savant includes: • EPC of the tag read • EPC of the reader that scanned the tag • Time stamp of the reading i.e. at what instant of time the tag was read by
  42. 42. 42 the reader • Other information such as temperature or geographical position that the reader is programmed to collect along with the EPC of the tag There are three software modules in the Sun’s version of the auto-id architecture: 1. Event Management System (EMS) 2. Real-time in-memory data structure (RIED) 3. Task Management System (TMS) 3.5.1. Event Management System (EMS) The Event Management system provides event triggered functionality. Its functionalities include: • A Java TM technology based system • Provide a common interface for various types of readers • Collect data in a standard format • Allow customized filters to smooth and clean data • Provide various mechanisms to log data into a database or remote servers using standard protocols (HTTP, SOAP, Java Message Service and Java Message Queue) 3.5.2. Real-time in-memory data structure (RIED) The features of the RIED include: • Stores event information by Edge Savants • Provides the same interface as a database, but offers much better performance • Applications can access RIED using JDBCTM technology or a native Java technology interface • Also supports SQL operations and can maintain snapshots of the database at different time stamps 3.5.3. Task Management System (TMS) Task Management system provides an interface to perform administration and maintenance activities.
  43. 43. 43 • It provides an external interface to schedule tasks • It simplifies the maintenance of distributed Savants because the enterprise can maintain Savants by merely keeping the tasks on a set of class servers up to date, and appropriately scheduling tasks on the Savants • In addition to data gathering and transmission the TMS can be used to request PML and ONS activity and schedule and administer tasks on other Savants Figure 12: Sun Java System RFID architecture for Savant The below table captures a trace of the Sun java architecture from our Software requirements:
  44. 44. 44 Table 7: Sun Java Architecture Sun Java System RFID solution component General Architecture component Use Case Software Requirements Event Management Module U4,U7,U8,U13, SR Event Management System Data filtering Module, Reader Interface Module U12,U18,U11 Real-Time In- memory Information processing module, U14,U15,U16,U17, SR Data Structure Persistence manager U19,U20 Task Management System Control Module U5,U9,U10,U11 SR 3.6 Conclusion Use case analysis and Architectural modeling of Savants enables better understanding of the system. It provides a basis for further improvements in the design of future versions of the savant. In addition, it provides us with a basis to perform further refinements into the savant specifications.
  45. 45. 45 Section 4: Summary of Best Industry Practices & Developments in RFID Systems and their Experimental Investigation 4.1 Best Industry Practices & Developments in RFID Systems: Application / Area of Interest Variables Affecting Tag Readability Description Suggested By The wear of interconnections between antenna and chip of a tag affects the reliability and read distance of the tag. Effect of tag wear Contacts made by silver epoxy or compression contacts on copper or aluminum degrade over time and are affected by high temperatures Effect of form factor There is an almost linear relationship between the size of tag and its readability AVANTE Labs Effect of variations in tags Effect of tag orientation The read range of a dipole tag increases when the tag becomes parallel to the field and is least when it is perpendicular to the field. Tag flipping reduces the tag readability. Same is the case with the write range though it is less in all events as compared to the read range. K.V.S. Rao (Intermec)
  46. 46. 46 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By Effect of large number of tags scanned by a single reader The average tag readability in large scale events is 96.8% Yusuke Kawakita, and et al ( Keio University Tokyo, Japan) Usually tags require 7-8db in power for reading at a fixed distance of 1m. The "bad" or weak tags require 25-26 db of power to get activated. Sorting of such "bad" tags from a pool of can increase the tag readability to more than 98% Effect of "weak" tags Sorting of tags on the basis of energy required to respond is a very time consuming process and if done in the RFID printer itself, requires high degree of calibration when each tag is tested at variable levels of power. If done on a post-application level, it increases the rework by 3-5%. Dan Dobkin (Enigmatics) Effect of tag velocity on number of reads The number of reads decrease exponentially with the increase in the tag's velocity Effect of tag velocity on average reading time The average reading time decrease exponentially with the increase in the tag's velocity Katariina Penttila, and et al ( Tampere University of Technology, Finland)
  47. 47. 47 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By Effect of number of tags on identification time Tag identification time increases linearly with the increase in number of tags in close proximity. Multiple tag identification is successful only up to 4m/s of tag velocity Katariina Penttila, and et al ( Tampere University of Technology, Finland) Effect of high tag density Effect of number of tags on response time The running time in tag response for a set of 60 tags close to each other but well inside the optimized field coverage of the antenna, is more than 6000 milliseconds Vogt. H. Antenna size Increase in antenna size of both the tag and the reader can increase the read distance by 25-50% AVANTE Labs Effect of antenna Relationship between antenna diameter and read range 100% tag readability of UHF tags is obtained by properly identifying the form factor suitable for a specific read range required for the application. A tag antenna with diameter of 18 mm can result in 100% readability only within 500 mm distance from the reader Hosaka, R. Effect of reader Power of reader Low powered handheld readers can achieve a reader distance of 1/3rd of the fixed antenna reader i.e. up to 2-3 feet distance AVANTE Labs
  48. 48. 48 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By Forklift mounted RFID readers are the best in warehouse environments. They provide the flexibility in inventory counting procedures.Type of reader The tags should be placed facing out, towards the aisle on every asset for this solution to work properly John McGinnis (AVID Wireless) Effect of Liquids Effect of proximity to liquids Attenuation of signals may reduce the read distance by few hundred percents AVANTE Labs Effect of Metallic environments Proximity to metals Metals reduce the read as well as write range of tag in their vicinity. For a tag placed on a metal sheet and at a distance of 1 m from the reader has a 4/5th reduction in read range as that of a tag not in the proximity of metals AVANTE Labs Effect of Rain Read distance can fall even by 100% in rainy or high humidity environments Effect of climate Effect of snow Snow has the same effect as that of rain, but here the reduction in read range can be as low as zero AVANTE Labs
  49. 49. 49 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By Hardened plastic, foam and plastic wrap have little effect on tag readability Effect of plastics To increase the accuracy and precision of tag readability, use of additional tags per component, use of higher frequency ranges, use of additional receivers, increase in antenna power, and/or improvement in post processing data must be practiced Effect of wooden enclosures Tags covered with wooden blocks from all sides, have zero readability Proximity of metals reduce the tag readability by more than 50% as compared with non-occluded tagsEffect of metallic enclosures Any line of sight occlusions (involving metal) between a tag and any of the receivers results in the occluded receiver not even detecting the tag Effect of packaging material Effect of Ceramics Tags placed under ceramic moldings have reduced accuracy and less readability in tag localization as compared to non-occluded tags Tucker Balch, Adam Feldman and Wesley Wilson Effect of occlusions Effect of PVC pipelines RFID tags enclosed in a PVC container have less read range though this Hussein Al- Mousawi
  50. 50. 50 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By decrease in read range is very less. Effect of Concrete Tags up to a distance of 200mm behind a concrete bar are detectable but writing range of such tags is just 100mm (though the tag readability also depends on the water and steel content of the concrete block) Effect of air gap When tags are enclosed in a plastic container, a small air gap between the tag and the container walls increases the readability Effect of water content in concrete Water content in concrete blocks, decreases the tag readability by up to 20% (Adger University College, Norway) Use of WiFi With a WiFi enabled reader, the last location of the forklift movement with the identifiable RFID tag can be found out which can help in relating the tag movement and its location the warehouse Michael Oh (TCM RFID Pte Ltd) Use of performance enhancing technologies and tools Use of "SAW- RFID Technology" Surface Acoustic Waves (SAW) work better and has a read range of around 300 feet. It works better through metals and tags in the vicinity of metals John McGinnis (AVID Wireless)
  51. 51. 51 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By The tags have very small data storage capacity and work only if we do not need to write anything on the tag and cost a few dollars. Able to scan through all shelves to have an update of stock level with high tag readability. High cost of implementation Michael Oh (TCM RFID Pte Ltd) 100% tag readability is possible Will not achieve 100% performance above 3 inches off the surface Use of "Smart Shelf" Close proximity of tags may reduce the tag readability Ron Marino (RAM Engineering & Consulting, Inc.) Use of non- metallic slider bed conveyor Non-metallic conveyor eliminates electro-magnetic interferences by using composite polymers that can work at temperatures ranging from -40°F to 165°F and the conveyor is virtually transparent to all frequency ranges (HF, UHF and Microwave). Multiple readers can be mounted on the within close proximities. This type of conveyor helps in reducing scattering of RF signals due to metals. Upstream reading and downstream writing or Carl Forsythe (Globe Composite Solutions, Ltd.)
  52. 52. 52 Application / Area of Interest Variables Affecting Tag Readability Description Suggested By verification of tags is possible. FID readers can be mounted, above, below or on either sides of the conveyor thus making it possible to achieve any read angle adjustments Read range as high as 300mm can be obtained while using Mu-chip. The tag is 0.3mm x 0.3mm x 0.06 mm in dimensions and can be fitted easily on electronic circuit boards, miniature electronic parts, etc. Use of "Mu- chip" Very complicated design with high cost of production Mitsuo Usami (Hitachi Ltd.) Active tags work best in metallic environments and have high read range The maximum possible read range achieved by an active tag is not more than 9 meters for tags enclosed in machine tools. Use of active tags The reliable read range is limited to just above 1.5 meters when used in chilling stations Paul Goodrum and et al (University of Kentucky, Lexington)
  53. 53. 53 4.2 Experimental Investigation 4.2.1 Standard tests and test setups Options for varying distance: Switched attenuator, fully tested and calibrated, to simulate changes in read distance. An attenuator is a device that attaches to a transmission line (a coaxial cable) and reduces the power of a signal as it travels from the reader to the reader antenna through the cable. Attenuators are usually rated in terms of decibels (dB), a logarithmic measurement of the intensity of emitted energy, and the frequency spectrum they are designed for. They work by dissipating the RF energy into heat. Tags near metal To assess the performance of tags near metal, each tag can be placed at varying distances from a large, flat piece of steel. The tags and metal plate are separated by air. Then use an attenuator to determine the dB attenuation level at which the tag could no longer read. A higher attenuation level, expressed in dB, corresponds to a longer reading distance. At each distance, increase the reader's dB attenuation level until no reads were observed. This will provide an approximate maximum read distance for each tag. Tags near water Placing an aquarium near to the reader or in between the reader and the tag Using a spectrum analyzer A spectrum analyzer can be used to measure ambient RF energy in the room to ensure that there was no electromagnetic interference that would affect the test results. Antenna pattern Separating the reader and the tag by a constant distance and rotating one of them 360º with respect to the other - a 3D plot that shows how much RF is radiated in all
  54. 54. 54 directions. The same can be repeated inside an anechoic chamber and a comparison can be provided. Reader placement Increasing the accuracy of read without placing more readers is of great importance when considering minimizing the cost of deployment of RFID systems. This is essentially finding the optimal place for the readers to detect maximum number of tags Varying the reader antenna placement is usually the easiest thing to try first, but is one of the trickiest things to do well. The reader antenna must be placed in a position where powering the tag and receiving data can be optimized for the particular application. In a multiple antenna system, the radiation pattern of all the antennas must be known as well as the location of other nearby readers. It is important to keep in mind that the read range of an RFID system is generally limited by the amount of power that can be captured by the tag. This requirement serves as a simple guide for determining initial antenna placement. Both OATS (Open Air Tests / Free space) measurement and measurements inside the anechoic chamber can be done to determine the antenna pattern of all the antennas that we use in the reader and tags. Once the 3D plot of the antenna pattern is plotted, it will help us largely in the placement of readers [19]. 4.2.2 Equipments available for testing • An anechoic chamber with RF field measurement and analysis instrumentation • Simulation software’s to simulate the cases • Spectrum analyzer to measure EM power levels and the frequency domain measurements of the response of the tags and readers • Oscilloscope to capture the signal response of the tag and the reader • Vector Network Analyzer to measure the antenna parameters of the tag and the readers • Attenuator – to be purchased
  55. 55. 55 • Antenna tuner for better tuning of the tag and the reader antenna • Signal generator to output certain signals at the desired frequency and power levels • Logistics software’s • Alien and AWID readers/tags • Computers and software’s for specific readers 4.2.3Proposed test beds: Some of the proposed test beds are suggested in Figure 13. The idea was imported from the existing test facility show in Figure 14. For a conveyor belt application, another test bed is proposed as in Figure 15. Figure 13: Test setup 1: For pallet testing and moving a loaded cart Antenna
  56. 56. 56 Figure 14 : Test setup[20] Figure 15: Test setup 2: For conveyor belt applications 4.2.4 Challenges It is a challenge because the radio waves that underlie RFID technology can go haywire when placed close to certain items containing liquid or metal. For example, liquids, like soda in a can, tend to absorb the electromagnetic energy needed to power the RFID chip. Meanwhile, the metal of the soda can tends to reflect this energy, bouncing it
  57. 57. 57 around in unpredictable ways. In either case, the RFID signal sent by a chip to the reader faces interference, thus dramatically reducing read rates for RFID tags [21]. Could RFID technology be deployed successfully on a factory floor? There are many issues to address: • Metal: Both the products and the carts used to transport them around the factory floor were made primarily of metal, which blocks radio waves. In addition, directly attaching a tag to metal could create difficulties in reading it. Tags were placed on system components located on an interior surface of the metal chassis, providing further reading difficulties. • Orientation and placement: Tag orientation (with respect to the reader antenna) and placement on the product had an affect on tag-reading ability. • Interference: A factory floor is generally filled with radio waves from other sources, including cellular phones and 802.11 wireless devices. Will these interfere with EPC network tags? • Stray or missed reads: The intend is to prove that the readers could sense all tags that were intended to be read, would not miss any reads, and would not unintentionally pick up stray reads from units that were passing by. There are some additional goals, such as determining read accuracy and throughput in a production environment; enterprise information systems (EIS) integration capabilities; and gaining hands-on experience. This will be a step toward a larger goal of determining if an EPC network could be implemented throughout a factory, which is expected to eliminate manual key entry and inventory counts while providing item-level tracking and history [22]. The key challenges to using RFID tags are read range and interference from metal objects. The power and size of the reader antenna, the system frequency, and the size of the tag will affect the range. Preliminary research has shown that both inductive and capacitive tags can operate on some products containing metal, such as batteries, but
  58. 58. 58 inductive tags need to be specially tuned if they are to be installed on a battery or other metal-containing object in order to maximize the read range. Capacitive tags have been shown to work well on metal products such as steel or aluminum cans, though inductive tags do not. Capacitive tags can also be read through small metal objects, as long as the metal object is not grounded. Both inductive and capacitive tags work well on fluorescent light bulbs, even when placed on a part of the bulb containing metal [23]. Questions related to readability and usage of RFID with respect to change in temperature • How does the tag operate when tags are placed are on the products present inside a cooler? • When the tags are stored at high temperature (Higher than the room temperature) how is the readability affected? 4.2.5 Electromagnetic Issues that the lab can address There are many physical interactions taking place in an RFID system. The most important factors are listed below. Absorption and Attenuation As the electromagnetic field propagates through various materials, the dielectric loss and conductive losses in the material attenuate the field of the reader as well as the response signal of the tag. This effect is of particular concern in pallet-level interrogation, where users desire to read multiple tags embedded inside large heterogeneous pallet containers. This can be addressed by simulating multiple tags embedded inside a large pallet using FEMLAB. This will help in better placement of the tags on pallets in a way that the interference between the tags is minimized. Shielding Electromagnetic shielding occurs in materials having high electrical conductivity. In particular, the shielding effect is the result of induced currents by the applied
  59. 59. 59 electromagnetic field, which act to cancel the applied field. Understanding this phenomenon is particularly relevant to situations such as reading multiple items inside a pallet containing metal cans or liquids, as well as reading items on a shelf through different shelf materials. Antenna Detuning The conductive and dielectric environment surrounding an RFID label can result in a detuning of the label. This reduces the amount of energy being captured by the tag and also reduces the modulation signal detected by the reader. Although this problem is most well-known for RFID tags operating at 13.56MHz that have a high Q-factor, this is also relevant to some degree for 868-930MHz (ultra-high frequency/UHF) RFID labels as well. In the case of a UHF or microwave backscatter tag, the antenna tuning is primarily a function of the tag geometries and material properties, but it is also susceptible to detuning effects if the tag antenna is made highly resonant. Reflections and Interference The reflected waves from one or more metal surfaces in the environment combine to produce a non-uniform and non-monotonic variation in the field produced by the reader due to the phase differences between the multiple paths. This is the same effect that we experience walking around with a mobile phone inside a building. Depending on the position of the tag, this interference can either enhance read range or it can destroy it, leading to "null spots." For a given RFID frequency, if the geometry of the environment is known, this field variation can be calculated and mapped. Multiple propagation paths can also be created in situations where the reader field is partially blocked or absorbed. Examples of this situation might be a loading dock or warehouse environment where the reader field can be partially blocked by several large objects or perhaps blocked by containers in the pallets themselves. Once again, in this case, if the geometry of the environment is known, the interference effects can be predicted and hopefully avoided.
  60. 60. 60 It should also be noted that interference effects (diffraction) can also result from a single aperture alone. This situation may occur if trying to read distant tags from a high- frequency reader through a narrow space, such as layers in a pallet or items stacked on a shelf [24]. 4.2.6 RFID security and privacy – can our lab address any of the privacy issues by doing some preliminary tests • Cover RFID tags with protective mesh or foil • How to kill RFID tags? • Some method of having a encryption thus making the tags not readable with non legitimate readers • Using a blocker tag that can shield the other tags being read from non legitimate readers [25], [26] 4.2.7 Test articles Test articles are used to evaluate the performance of the tags. Here tests are done with products that come in plastic containers and metal containers which have the same shape. The test results will help us in evaluating which tags will be performing better on plastic containers and what will be the effect of bringing a metal into the same tests. The test articles are also chosen in various sizes so that the effect of placing the tags at the right places for large containers can also be determined for increasing the readability. Cylindrical: Large – Folgers coffee cans – Plastic/Metal Medium – Coke cans (Metal) and same size juice bottles (Plastic) Small - Salt shaker (Plastic)
  61. 61. 61 4.2.8 Experiments and Results This is a list of all the experiments that have been conducted in the lab in marching towards our goals in the research front. In addition to this a novel method for reading the tags in high metal environment is also under development. No. of tags vs. readability: Using 20 tags: Free space • 20 tags were stuck to a piece of cardboard sheet at random orientations. The tags are separated from each other i.e., they don’t over lap as shown in Figure 16 • The sheet with the tags is held against the reader at distances 20 inches and 50 inches as shown in Figure 17. The plane of testing is parallel plane and as the reader antenna is circularly polarized, the orientation of the tags does not matter • For 20 inches, 18 tags were read successfully and for 50 inches of separation, 14 tags were read successfully Presence of Metal • A big sheet of metal was placed right behind the cardboard sheets (Ref: Figure 18) and the same experiment was repeated for a distance of 20 and 50 inches • With the metal present at the back, for a separation of 20 inches 3 tags were read successfully and for 50 inches of separation, only 1 tag was read Note: In this experiment, the tags and the reader antenna are always in the line of sight.
  62. 62. 62 Figure 16: 20 tags placed on a cardboard sheet in random orientations Figure 17: Reader antenna and tag sheet separated by a distance of 20 inches in free space
  63. 63. 63 Figure 18: Tag sheet placed on a big sheet of metal Using 50 tags stacked: • 50 tags are bunched up together randomly and the reader antenna was held at a distance of 20 inches • 20 tags were read successfully. The low read is because of the influence of the tags that are placed one over the other. • When the separation distance was increased from 20 inches to 50 inches, the readability reduced further. This is expected. As the read distance increases, the readability decreases because the power decreases exponentially. • The results for different tests are tabulated in Table 8 Table 8: Experimental results using 20 and 50 tags Number of Tags Distance between reader and tag (inch) No. of hits No. of hits when a sheet of metal is placed at the back 20 18 320 50 14 1
  64. 64. 64 Number of Tags Distance between reader and tag (inch) No. of hits No. of hits when a sheet of metal is placed at the back 20 20 N/A50 50 13 N/A Tags in books: in a book shelf: Using RFID for maintaining a library and getting quick information on the books and their availability is also of interest in the RFID field. So some experiments that will support this theory were done. This experiment is done to get a good idea about tag placement. • Alien tags are placed inside the books in a book shelf. Ref: Figure 19 • The tags are placed in a similar fashion that they are located right below the main cover of the book • There were in total 38 books present and hence 38 tags • The reader antenna is placed perpendicular to the books in the shelf
  65. 65. 65 Figure 19: Tags placed inside the books in a book shelf • Number of reads was recorded for varying distance of separation between the tags and the reader • The results are tabulated in Table 9 Table 9: Experimental results using tags on books (Tag orientation - perpendicular) Number of Tags Distance between reader and tag (inch) No. of hits 20 22 35 1738 73 8 • From the tabulation it can be seen that the readability decreases with increase in the distance of separation
  66. 66. 66 • Even for small distance of separation, the efficiency of read is low because the tags are in the presence of metal and as seen from the previous experiments, the presence of metal at the back of the tags decreases the read rate • Also the tags are placed in the perpendicular plane with respect to the reader antenna and as known, the read rate in the perpendicular plane is not high • Hence the experiment was repeated by putting the tags in the parallel plane with respect to the reader antenna • The placement of the tags in a parallel plane and on the books can be seen in Figure 20 Figure 20: Tags placed on the sides of the books in a book shelf • When the tags are placed on the sides, they are parallel to the reader so a enhancement in the readability is anticipated • The reader is placed at varying distance from the shelf and the number of hits is determined • The results are tabulated in Table 10
  67. 67. 67 Table 10: Experimental results using tags on books (Tag orientation - parallel) Number of Tags Distance between reader and tag (inch) No. of hits 70 11 40 2233 20 28-30 • As expected the readability has increased when the tags are in parallel in spite of the metal present behind Half filled book shelf: This experiment was done to look at the change in readability with the change in tag density. Hence for the same settings the experiment is repeated when the rack in the book shelf is half empty. • Number of tags is 18. The tags are placed at the same spot as before • The reduced number of tags in books placed in the book shelf can be seen in Figure 21 • The reader antenna is held at a distance of 35 inches from the rack and the number of hits is determined and the results are tabulated in Table 11
  68. 68. 68 Figure 21: Tags placed inside the books in a half filled book shelf Table 11: Experimental results using tags on books (Tag density – Half as in the precious stage) Number of Tags Distance between reader and tag (inch) No. of hits 18 35 16 Pile of books: • The tags are placed inside the front cover of the books and the books are piled up on the floor as shown in Figure 22 • The reader antenna was placed at a distance of 36 inch from the pile and the number of hits is determined • Note: Now the tags are in a parallel plane with respect to the reader antenna and there is no metal behind the books (While the books were placed in shelves, there was metal present at the back of the books)
  69. 69. 69 • Also as the books are piled in random orientation, the tags are also in random places Figure 22: Tags placed inside the books when the books are not in the influence of metal • The number of hits table is given below in Table 12 Table 12 : Experimental results using tags on books (Books are stacked on floor. No influence of metal) Number of Tags Distance between reader and tag (inch) No. of hits 10 36 10 14 36 14 18 36 16
  70. 70. 70 4.2.9 Readability with books considering tag density along with presence of metal After the preliminary set of experiments that was used to determine the readability of tags when present inside books, a more practical and more procedural experiment was carried out to determine how the tag density plays a role in the presence of metal when we are trying to read the tags present in the books. Note: From the results of previous experiments it was noted that the parallel orientation of the tag with respect to the reader is giving maximum readability hence, the same is followed in this set of experiments also. The tag is placed in the side. • The tags are placed in a similar fashion that they are located parallel to the reader. Ref : Figure 23 and Figure 24 • The experiment was carried on for two sets of tags Number of tags = 20 Number of tags = 48 • Three tag densities are used for the experimentation Low – Sparsely placed Medium – Closely placed High – Very tightly placed • The experiments were carried on for two varying distances (Distance refers to the distance between the reader and the tag) Small – 20 inches Large – 50 inches • The reader is placed opposite to the tags at the line of sight • The results are tabulated in Table 13 and Table 14 Table 13: Experimental results using tags on books (Influence of metal) No. of Tags Distance (inch) Tag density Presence of metal No. of Hits Metal 18 Low No Metal 20 Metal 17 20 Small Medium No Metal 20
  71. 71. 71 No. of Tags Distance (inch) Tag density Presence of metal No. of Hits Metal 18 High No Metal 20 Metal 15 Low No Metal 17 Metal 14 Medium No Metal 11 Metal 15 Large High No Metal 17 Table 14: Experimental results using tags on books (Influence of metal) No. of Tags Distance (inch) Tag density Presence of metal No. of Hits Metal 35 Low No Metal 38 Metal 31 Medium No Metal 38 Metal 30 Small High No Metal 38 Metal 29 Low No Metal 32 Metal 21 Medium No Metal 32 Metal 25 48 Large High No Metal 35 • From the table it can be seen that the presence of metal reduces the readability and it gets worse with the increase in distance and tag density
  72. 72. 72 Figure 23: Tags placed on the sides of the books in free space Figure 24: Tags placed on the sides of the books in a book shelf
  73. 73. 73 4.2.10 Readability in the presence of water • Plastic bottles are tagged using the Alien 9354 tag. As the reader antenna is circularly polarized, the orientation of the tag on the plastic bottle is not significant This would be significant in using RFID in medicinal applications like in a drug store where it would be easier to find the stock of drugs available • Bottles with the tags placed on them will be placed opposite to the reader as shown in Figure 25 and Figure 26 and the number of successful reads are determined for three varying tag densities • When the tags are placed against water in the bottle, the water will influence the readability of the RFID system so positioning the tag at the right place on the bottle is very important • The effect of having the bottles full of water and half empty with the tags placed near the brim was determined • The experiment was carried on for two sets of bottles Number of bottles = 5 Number of bottles = 10 • Three tag densities are used for the experimentation Low – Sparsely placed Medium – Closely placed High – Very tightly placed • The experiments were carried on for two varying distances (Distance refers to the distance between the reader and the tag) Small – 20 inches Large – 50 inches • The results are tabulated in Table 15 and Table 16
  74. 74. 74 Table 15: Experimental results using 5 tags on bottles No. of Tags Distance (inch) Tag density Presence of Water No. of Hits Water 1 Partial 1Low (Sparsely placed) No Water 5 Water 4 Partial 2Medium (Closely placed) No Water 5 Water 3 Partial 1 Small (20 inch) High (Tightly placed) No Water 5 Water 0 Partial 0Low (Sparsely placed) No Water 5 Water 0 Partial 0Medium (Closely placed) No Water 5 Water 0 Partial 0 5 Large (50 inch) High (Tightly placed) No Water 4
  75. 75. 75 Table 16: Experimental results using 10 tags on bottles No. of Tags Distance (inch) Tag density Presence of Water No. of Hits Water 4 Partial 3Low (Sparsely placed) No Water 10 Water 6 Partial 2Medium (Closely placed) No Water 10 Water 2 Partial 2 Small (20 inch) High (Tightly placed) No Water 10 Water 1 Partial 0Low (Sparsely placed) No Water 6 Water 0 Partial 0Medium (Closely placed) No Water 6 Water 0 Partial 0 10 Large (50 inch) High (Tightly placed) No Water 7 • From the table it can be seen that the presence of water affects the readability of the RFID system and the variation with respect to distance is also obvious
  76. 76. 76 Figure 25: Tags placed on the sides of the bottles with high tag density Figure 26: Tags placed on the sides of the bottles with low tag density
  77. 77. 77 Section 5: Statistical Analysis and Design of RFID Systems for Monitoring Vehicle Ingress/Egress in Warehouse Environments Summary Many academic and industry research efforts are currently focused on evaluating the potentials of RFID technology for industrial applications. Major applications of RFID technologies are anticipated in warehouse and depot environments. One needs systematic methodologies for effective design and deployment of RFID systems in these environments. The authors present a statistically designed experimentation approach determining the most desirable settings of an RFID system, deployable at vehicle ingress/egress points of a typical warehouse, depot, or a manufacturing plant. The approach yields phenomenological insights into the joint effects of multiple RFID system parameters on the performance of the ingress/egress monitoring system.
  78. 78. 78 5.1. Introduction After September 11, the US government as well as the major industries have started placing increasing attention on tracking and monitoring of cargo and vehicles movement [27]. It is becoming imperative for every warehouse, depot, and a manufacturing plant to monitor vehicle ingress and egress through their premises. As a result, many commercial warehouse or storage management systems have begun to include components for vehicle transit monitoring. They are primarily aimed in achieving the following three basic functions: (1) Inventory management, (2) safety of the goods, and (3) security of the warehouse, depot or any manufacturing plant A typical vehicle transit monitoring system uses checkpoints placed at various locations within a warehouse. The security personnel need to physically examine and identify each container or item, most likely by reading the barcode information. This information is then, transferred to an ERP system to cross-verify the goods being shipped from or arriving into the warehouse. This procedure has some inherent lacunas. For example, the system requires at least one dedicated person to carry out the vehicle ingress/egress monitoring process at each checkpoint, and the system cannot keep a check on the movement of every vehicle the enters or leaves the premises of a warehouse. RFID and other such automatic identification technologies offer potential for surmounting these shortcomings. A typical RFID system consists of tags (also known as transponders), readers (sometimes known as transreceivers) and a computer system for storing and managing the data received from the reader and analyzing it according to the type of software application that uses it. A transponder is usually a memory device (e.g. EEPROM), fitted on the object to be identified [3]. It contains information that uniquely identifies an object. A reader is capable of generating, receiving, demodulating and deciphering RF signals.
  79. 79. 79 Tags are classified, into various types depending on whether they are active or passive, readable and/or writable, etc., [2]. Based on the protocol of the tags, they can be differentiated into two main types as EPC and ISO tags. Table 17 represents the classification of EPC based tags. Among these, Class 0 and Class 1 tags are widely accepted by the industry due to their cost effectiveness and easy availability. Tags classified according to the frequency standards in ISO 18000 series [28] are summarized in Table 2 [5]. Whenever a tag comes into a reader’s RF electromagnetic field, it gets powered due to the incident electromagnetic field, and sends signals back to the reader that identifies the tagged object. This identification technology can be used for real time job tracking, goods and/or asset management, etc., [3]. Table 17: Tag Classification of EPC tags EPC Class Description Functionality Remarks 0 Read Only Passive tags Data can be written only once during tag manufacturing and read many times 1 Write Once and Read only Passive tags Data can be written only once by tag manufacturer or user and read many times 2 Read/Write Passive tags User can read/write data many times 3 Read/Write Semi-passive tags Can be coupled with on board sensors for capturing parameters like temperatures, pressure, etc. 4 Read/Write Active tags Can be coupled with on board sensors and act as radio wave transmitter to communicate with reader
  80. 80. 80 The data carrier frequencies recommended by the Federal laws is as shown in Table 18 Table 18: Classification of Frequencies Low Frequency(LF) High Frequency(HF) Ultra High Frequency(UHF) Microwave 125 - 134 KHz 13.56 MHz 902 - 928 MHz 2.4 - 2.48 GHz As shown in Figure 27, the information stored in a tag is transmitted to a reader at a carrier frequency. The reader de-modulates the signal and sends the tag information to the RFID middleware. The middleware consists of an event processor and a link to the central database. The event processor uses the central database to retrieve tag-specific data. It then compares the data with that read from the tag. This processed-information is sent to an enterprise application (EA) such as an ERP system [3]. An EA links the database and the user so that a user can extract higher-level information with regard to, vehicle arrival patterns, classification of the vehicle, vehicle authorization, etc. Figure 27 : RFID Data Flow Diagram[29] During the last two years, the industry has initiated a few planning studies and pilot deployments of RFID systems. The industry has envisaged potential of RFID systems in improving the practices of supply chain management, logistics, machine health monitoring, warehouse management and customer support. RFID systems are considered in quite a few scenarios to be a better substitute to bar codes due to their ability to identify any part, product or vehicle on item level, and they are considered to be
  81. 81. 81 more cost effective compared to many global positioning systems. Many companies are patenting new RFID solutions to an extent that some have started to believe that the bar codes, which are prevalent in many industrial identification applications, will become obsolete in a few years. However, RFID systems, at present have some inherent shortcomings. They include: 1. loss of readability in the presence of metals due to signal scattering, 2. a quadratic reduction in readability of tags with an increase in the distance between the tag and the reader, and 3. large dependence of readability on the form factor (i.e. shape, size and orientation), make, standard compliance and reader antennas. Implementation of RFID system in real world environments therefore requires careful design and selection of key system parameters such as the tag orientation, reader make, vehicle speed, etc., in order to optimize pertinent performance variables including the read rate, robustness to noise, etc. These parameters will henceforth be referred as Key Process Input Variables (KPIVs), and the key output variables will be referred to as Key Process Output Variables (KPOVs). The objective of the work presented in this paper is to derive a statistical approach towards systematically designing an effective RFID enabled vehicle ingress/egress monitoring system. The following benefits are achieved using such an RFID based monitoring: 1. A current system with barcodes requires a person to manually inspect a vehicle and have the barcode identified by using the barcode reader. An RFID enabled system, obviates the need for such highly repetitive human activity, and thus allows fast and easy information gathering. It will eliminate several non-value added activities and can systematically reduce the paper work and documentation, and excessive reliance on routine manual labor. 2. RFID enables easy bulk identification and verification of vehicles and its contents entering or leaving a warehouse or a manufacturing plant. A
  82. 82. 82 RFID system can be coupled with picture identification, thus allowing faster and robust identification of a vehicle from a remote location [30]. 3. The system can be used for monitoring and identification of patterns in vehicle motion states over time. This information can then be used to upgrade the current plant and enterprise practices towards improving overall system performance. Figure 28 : Schematic of an RFID based vehicle ingress/egress monitoring system As shown in Figure 28, an RFID based vehicle ingress/egress monitoring system would require modifications to the existing setup/infrastructure in the form of reader antennae placed at the entry and exit checkpoints. One may use multiple (at least two) antennae positioned in tandem to differentiate between ingressing and the egressing vehicles. These modifications will help in tracking the flow of vehicles in the warehouse or plant premises. Each vehicle will be equipped with an RFID tag at an appropriate location (e.g. near the center of windshield). This tag will store information that uniquely identifies the vehicle. Apart from this, all items/containers may be RFID tagged to allow identification of the contents of the vehicle. We note that this paper focuses on determining RFID system elements for vehicle monitoring only. Determination of the
  83. 83. 83 locations and other KPIVs of RFID tags on the containers requires a separate statistical and electromagnetic (EM) field analysis, which is beyond the scope of this paper. The presented approach can be applied to design a layer vehicle monitoring system whereby the position of vehicles can be tracked by synchronizing antenna signals at various locations in a warehouse and unauthorized vehicles can be easily tracked and identified. The remainder part of this paper is organized as follows: A description of our approach to select the KPIVs from among a large number of system parameters is presented in Section 2, our experimentation setup and procedures are described in Section 3, and the results are presented in Section 4.
  84. 84. 84 5.2. Determination of KPIVs As summarized in Figure 29 and Table 19, an RFID system is influenced by many factors or Process Input Variables (PIVs). It is important that correct factors be chosen to yield designs for successful implementation of the vehicle monitoring systems. The current EM theoretical models are not tractable for capturing the effects of these factors on the readability in real world environments. Statistical approaches are therefore imperative for effective design of the RFID systems [31]. Further, different factors will have significantly diverse influence on readability only a select set of factors have major influence. Therefore, for facilitating tractable statistical analysis, these PIVs need to be filtered to extract a more compact set of KPIVs. Some of them are explained below and detailed further in Appendix A. Figure 29 : Cause and Effect Diagram
  85. 85. 85 • The tags used for this application must be durable, cheap and the user must be able to use its conventions to write relevant data on the tag. So, we propose to use two types of tags EPC Class 1 [4] and ISO 18000-6 complaint tags [32] • Orientation of tag is the relative placement of the tag w.r.t. the field of polarization of the reader’s antenna. This may be parallel and perpendicular or oblique to the EM field along various planes of references as shown in Figure 30. The orientation is specified in terms of angles )180(0,and)90(0,),90,0( °∈°∈°∈ zyx θθθ . Z X Y Reader Tag Figure 30 : Tag Orientation (All angles at zero degrees) • Form Factor refers to the size and shape the tag antenna. It wields a significant influence on the EM field envelope generated in presence of a reader and the tags, which in turn is the main determinant of readability. • Tag Collision is the effect of one or more tags responding to the reader signal at the same time. This confuses the reader and requires complex algorithms such as binary tree method, etc., to distinguish between individual tags θy θx θz Y X Z
  86. 86. 86 • Operating environment holds significant influence on readability. For example, metal parts of a vehicle can hinder the free flow of information from the tag to the reader and vice versa, by reflecting the waves in all directions. There are different tags for different purposes. A tag created exclusively for metallic environments such as AWID’s ISO 18000-6 tag [33], works well in such environments than a general-purpose tag. In addition, the presence of other tags and reader antennas may cause an adverse effect on the EM field. Thus, the presence of more than one reader antenna may become a PIV in the experimentation. Table 19: List of PIVs Sr. No. PIVs Controllable(C) / Noise(N) / Fixed(F) 1 Orientation of tag (θy,(θz) C 2 Placement of tag (θx) C 3 Weather N 4 Vehicle type N 5 Frequency range F 6 Speed of vehicle C 7 Reader placement C 8 Reader make C 9 Tag make C 10 Form factor F 11 Electronics installed in the vehicle N 12 Tag collision N 13 Metallic environment N 14 Number of reader antennas C 15 Frequency used F 16 Standard compliance C 17 Tag functionality C