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

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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

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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.

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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.

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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

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• 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

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• 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

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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

System High Tag

Density

Reader & Antenna

Setup

Bubble

Wrap

EDS

Reader & Antenna

setup

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

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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.

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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

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Figure 2: Parameters Affecting Tag Selection

2.2.1.1 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]

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2.2.1.2 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

2.2.1.3 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]

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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

2.2.1.4 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

2.2.1.5 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

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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

2.2.1.6 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

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2.2.1.7 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

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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

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• 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

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

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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

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2.4.1.1 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.

2.4.1.2 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.

2.4.1.3 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.

2.4.1.4 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.

2.4.1.5 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.

2.4.1.6 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

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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

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

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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

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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.

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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

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.

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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

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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.

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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

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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.

3.3.2.1 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

3.3.2.2 Use Case analysis of Savant

We first start with the detection of actors, use cases and then the relationships

respectively.

3.3.2.2.1 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.

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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

1This 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 2Applications could be monitoring the reader information in real time. 3Applications sometimes prefer data to be in particular formats so that they could

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3.3.2.2.2 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

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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

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• 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

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

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• 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

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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

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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.

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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

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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

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.

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• 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:

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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.

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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

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

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

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

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 tags Effect 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

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

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

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

4.2 Experimental Investigation

4.2.1 Standard tests and test setups

4.2.1.1 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.

4.2.1.2 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.

4.2.1.3 Tags near water

Placing an aquarium near to the reader or in between the reader and the tag

4.2.1.4 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.

4.2.1.5 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

directions. The same can be repeated inside an anechoic chamber and a comparison can

be provided.

4.2.1.6 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

• 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

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

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

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].

4.2.4.1 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.

4.2.5.1 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.

4.2.5.2 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

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.

4.2.5.3 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.

4.2.5.4 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

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

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.

4.2.8.1 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

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

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 3 20

50 14 1

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/A 50

50 13 N/A

4.2.8.2 Tags in books:

4.2.8.2.1 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

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 17

38

73 8

• From the tabulation it can be seen that the readability decreases with increase in

the distance of separation

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

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 22

33

20 28-30

• As expected the readability has increased when the tags are in parallel in spite of

the metal present behind

4.2.8.2.2 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

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

4.2.8.2.3 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

• 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

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

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

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

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

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 1

Low

(Sparsely placed) No Water 5

Water 4

Partial 2

Medium

(Closely placed) No Water 5

Water 3

Partial 1

Small

(20 inch)

High

(Tightly placed) No Water 5

Water 0

Partial 0

Low

(Sparsely placed) No Water 5

Water 0

Partial 0

Medium

(Closely placed) No Water 5

Water 0

Partial 0

5

Large

(50 inch)

High

(Tightly placed) No Water 4

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 3

Low

(Sparsely placed) No Water 10

Water 6

Partial 2

Medium

(Closely placed) No Water 10

Water 2

Partial 2

Small

(20 inch)

High

(Tightly placed) No Water 10

Water 1

Partial 0

Low

(Sparsely placed)

No Water 6

Water 0

Partial 0

Medium

(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

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

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.

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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

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

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

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

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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

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

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 Z 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

• 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

• 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

87

A quality function deployment approach [34] was applied towards selecting the

appropriate KPIVs. The selection is done in two phases based on matrix based filtering

common to Quality Function Deployment (QFD).

In Phase 1 matrix, PIVs are listed on the top row of the matrix. KPOVs are listed

along the first column, and their relative importance (one for least important and four for

highly important) is listed in column 2. Among these, tag readability, is defined in terms

of the probability that a given tag is read in a specified environment, of particular interest.

Tag readability is determined by the fraction of the times a tag is read in a designed

experiment. The KPIVs are weighted according to their influence on each of the KPOVs

on a 9,3,1,0 scale (9 is the highest and 0 is the lowest influence) [34]. The absolute

technical importance is calculated by the following formula,

∑ = ×= ni 1 importance sKPOV' valueinfluence Importance Technical

Then the PIVs are ranked in ascending order w.r.t. their technical importance and

the PIVs with rank seven of less are chosen from the Phase 1 (see Table 20).

Also, the interrelationship matrix (as shown in Table 22), is built in the

following manner. If the relationship between two PIVs is very strong, we say it as a

highly positive relationship, which is denoted by the symbol “▲” in the interrelationship

chart. A loosely positive relationship is denoted by “+”. If the

relationship is weak, it is denoted by “�” the case of no relationship

is denoted by “▼”.

88

Table 20 : Selection of KPIVs- Phase 1

TAG READER ENVIRONMENT

KPOVs

Importance(Weight)

Form Factor

Tag Placement/Position

(θx)

Tag Orientation

(θy,(θz)

Tag Protocol

Reader frequency

Reader Make

Number of Antennae

Reader-Tag Distance

EMI

Tag Density

Weather

Vehicle type

Vehicle Speed

Readability

(READ) 4 3 9 9 9 9 9 9 9 9 9 3 3 9

Robust to Noise 2 0 3 3 3 9 3 9 9 9 9 9 9 3

Compatibility (with

most common RFID

standards and

systems)

3 3 0 0 9 9 9 0 1 1 1 1 1 1

Cost of study 1 3 1 1 1 3 1 1 1 9 1 9 3 1

Technical Importance 24 43 43 70 84 70 55 58 66 58 42 36 46

Rank

10 7 7 2 1 2 5 4 3 4 8 9 6

In Phase 2, we found that certain KPIVs are either fixed or noise, so these are

highlighted with “Grey” color and are depicted in Table 21. These KPIVs are eliminated

subsequently.

89

Table 21 : Selection of KPIVs - Phase 2

TAG READER ENVIRONMENT

KPOVs Importance(Weight)

Tag Placement/Position

(θx)

Tag Orientation

(θy,(θz)

Tag Protocol

Reader frequency

Reader Make

Number of Antennas

Reader-Tag Distance

EMI

Tag Density

Vehicle Speed

Readability (READ) 4 9 9 9 9 9 9 9 9 9 9

Robust to Noise 2 3 3 3 9 3 9 9 9 9 3

Compatibility (with most common

RFID standards and systems) 3 0 0 9 9 9 0 1 1 1 1

Cost of study 1 1 1 1 3 1 1 1 9 1 1

Technical Importance 43 43 70 84 70 55 58 66 58 46

Rank

7 7 2 1 2 5 4 3 4 6

Controllable [C] - Fixed [F] -Fixed

Maximum [M] - Noise [N] C C C F C M C N N C

90

Table 22 : Interrelationship Matrix of KPIVs

Highly Positive

(▲), Loosely

Positive (+), No

relationship (▼),

Weak

Relationship (P)

Form factor

Form factor

Tag

Placement/Position ▼[35]

Tag Placement/Position

(θx)

Tag Orientation +[36] ▼[36]

Tag Orientation

(θy, θz)

Tag Protocol

▼[37] ▼[35] +[38]

Tag Protocol

Reader frequency ▼[35] ▲[35] Z[38] ▼[37]

Reader frequency

Reader Make ▼[35] ▲[36] +[38] ▲[39] ▼[37]

Reader Make

Number of

Antennas +[35] +[38] Z[35] ▼[40] Z[35] ▲[37]

Number of Antennas

Reader-Tag

Distance ▲[35] +[36] +[36] +[35] ▲[4] ▲[37] ▲[37]

Reader-Tag Distance

EMI +[3] ▼[3] +[38] +[3] +[35] +[38] ▲[35] ▼[35]

EMI

Tag Density Z[38] +[36] ▲[37] +[41] Z[35] ▲[37] +[42] ▼[39] Z[3]

Tag Density

Weather Z[36] ▼[35] Z[38] ▼[35] +[35] Z[37] +[40] ▼[38] +[35] ▼[37] Weather

Vehicle type ▼[37] ▼[37] +[37] ▼[37] ▼[37] ▼[37] Z[37] Z[37] Z[37] Z[37] ▼[37] Vehicle type

Vehicle Speed Z[40] +[37] ▲[37] Z[3] +[35] +[37] ▲[37] ▲[37] Z[37] ▼[37] ▼[37] ▼[37] Vehicle Speed

91

Hence, we are left with the following variable and controllable factors for our

experimentation:

1. Reader make

2. Tag make

3. Distance between tag and reader

4. Tag Placement angle θx

5. Tag Orientation angle θy

6. Tag Orientation angle θz

7. Speed of the vehicle

92

5.3 Experimentation Details

Experiments were conducted on an open space at the entry of a parking lot at

Oklahoma State University. The objective of these experiments is the following:

a) statistically quantify the relative influence of various KPIVs on tag readability,

b) propose the optimal combination of KPIVs that will enhance readability, and

c) propose a mathematical relationship connecting tag readability to the various

combinations of the KPIVs

The experimentation setup is summarized in figures 5 and 6. Figure 31 shows an

Alien reader held tag a distance of 20 inch from the EPC Class 1 tag, mounted on the

vehicle’s windshield.

Figure 32 shows an AWID reader held at a distance of 20 inch from the ISO

18000-6 tag. This setup is one of the various combinations of levels of KPIVs, required

for the design of experiments. Figure 33 shows an Alien reader connected to a computer

system required to extract the tag information from the reader. The connection from the

reader to the backend computer is accomplished through an RS 232 or an Ethernet

Alien® Reader

EPC Class 1 Tag

Figure 31 : Antenna -tag Setup for experimentation

93

port.

Figure 33 : Reader to Computer System Connectivity

AWID® Reader ISO 18000-6 Tag

Figure 32: Antenna -tag Setup for experimentation

94

Some of the KPIVs were either insignificant or their interactions do not comply

with their hardware configurations. For example, effect of tag orientation (θx) on

readability is insignificant (hence, they were eliminated from the study). The Alien®

reader is incompatible with the ISO protocol, and the AWID reader works well, only with

the ISO protocol. Lab experiments revealed that, the tag flipping (i.e., changing in θz),

had little effect on readability.

A full factorial multi-level experiment was conducted with the following KPIVs:

1. Reader Make

2. Distance between tag and reader

3. Speed of the vehicle

4. Tag Orientation (θy)

With reference to the datasheets of individual readers and lab experiments

confirmed the read range distances for each reader. The levels of distance for each reader

determined based on prior lab experiments. The details of the various KPIVs and their

ranges are summarized in Table 23 and Table 24. It is noteworthy that the reader make

‘R’ is ordinal, in that it is coded as 1 and 2 depending on whether Alien or AWID reader

is used. The distance ‘D’ is coded between levels 1- 10, corresponding to the actual

distances ranging from 20 inch to 180 inch, as summarized in Table 24. The Speed ‘S’ is

coded at three levels for 0, 10 and 20 mph. θy is coded in two levels, for 0° and 90°. The

full factorial multi-level design and results with eight replicates for each run are shown in

Table in Appendix B.

95

Table 23 : Levels of Distances for each Reader

Alien AWID

Distance (inch)

50 20

85 45

115 72

145 100

180 125

Table 24 : Coding Scheme of KPIVs

KPIV Symbol Type Range of

Interest Level Coding

How

Measured

Alien® 1 Reader

Make R Ordinal

AWID® 2

2 Visual

20 1

45 2

50 3

72 4

85 5

100 6

115 7

125 8

145 9

Distance

(inch) D Continuous

180

10

10

Measuring

Tape

0 1

10 2 Speed

(mph) S Continuous

20

3

3

Vehicle

Speedometer

0 1 θy

(degrees) θy Continuous

90 2

2 Visual

96

5.4. Analysis of the experimental results

Analysis of the experimental results is done in two parts. Stepwise regression

analysis was performed to identify the main factors. Next, a response surface regression

analysis is done to facilitate detailed identification of significant main and interactions

effects, and determine optimal settings. The regression model is shown in the following

equation

.....1 14375.006869.045833.038125.016755.087778.004236.3 ySRDySDRREAD θθ ++−−−−=

The model captures 78% of variation in readability observed during our

experiments (See Table 25). Reader make (R) and the tag orientation (θy) seems to have a

strong influence on readability based on examining their relative magnitudes of all

KPIVs. Significantly, the joint effects of the reader make (R) and distance (D), as well as

that of speed (S) and tag orientation (θy) has a major effect on readability.

Table 25 : Response Surface Regression Analysis Results

Term Coefficient P

Constant 3.04236 0

R -0.87778 0

D -0.16755 0

S -0.38125 0

θy -0.45833 0

R*D 0.06869 0

S*θy 0.14375 0.001

S = 0.1934 R-Sq =79.4% R-Sq(adj) =78.3%

97

Figure 34 : Interaction Plot for Ybar (Tag Readability)

Figure 34 summarizes the joint effect of reader make R and the distance D on tag

readability. The readability of AWID reader to ISO complaint tags sharply drops after 45

inch (around 4 feet). Alien Reader is able to read EPC compliant tags beyond 100 inch.

This might be because of the power level of the system. Higher the power radiated, larger

will be its read range.

Figure 35 : Interaction Plot for Ybar (Tag Readability)

Figure 35 depicts the effect of reader make R and speed S of the vehicle on tag

readability. It can be inferred that the tag readability for Alien reader with EPC complaint

Alien

AWID

AWID

Alien

98

tags, drops consistently with the increase in speed from 0 mph to 20 mph whereas the tag

readability for AWID reader with ISO complaint tags, drops sharply after 0 mph. There is

a linear relationship between speed and readability for both the systems.

Figure 36 : Interaction Plot for Ybar (Tag Readability)

The effect of reader make R and yθ over tag readability is shown in Figure 36.

Here we see that the tag readability for Alien make reader with EPC complaint tags is

higher at °= 0yθ than at °= 90yθ . The AWID reader with ISO complaint tags has the

same effect as above when yθ changes from °° 90 to0 but in the latter case, the tag

readability is considerably lower than in the case of Alien reader. This is because

when °= 0yθ , the tag is oriented parallel to the reader antenna while at °= 90yθ , the tag

is oriented perpendicular to the reader antenna. There is a maximum coupling when the

tag is oriented in parallel than when it is oriented perpendicular with respect to the reader

antenna.

AWID

Alien

θy

99

Figure 37 : Interaction Plot for Ybar (Tag Readability)

Figure 37 shows the combined effect of distance D and yθ over tag readability.

The tag readability decreases consistently with the change in yθ from °° 90 to0 for each

distance level. The readability is inversely proportional to the distance and hence there is

a polynomial fall in readability with increase in distance.

Figure 38 : Interaction Plot for Ybar (Tag Readability)

Figure 38, shows the effect of Speed S and yθ over tag readability. It can be

inferred, that the tag readability is highest at 0 mph speed and is lowest at 20 mph speed.

θy = 0 °

θy = 90 °

θy

0 mph

10 mph

20 mph

100

It can be also concluded that the tag readability decreases when yθ changes

from °° 90 to0 . There is a relationship between the speed at which the vehicle is moving

and yθ . This is also reflected in the regression model (Interaction between speed S

and yθ ). This is because when the vehicle is moving, yθ changes i.e. at every position of

the vehicle, yθ is different.

Figure 39 : Surface Plot of Tag Readability vs. Distance and Speed

The surface plot of tag readability vs. distance D and speed S is depicted in Figure

39. The tag readability decreases consistently with increase in speed and distance. At a

speed of 10 mph when the tag is placed at a distance of 0 to 50 inch from the reader, the

readability does not vary much with respect to the distance. This region corresponds to a

plateau in the surface plot of Figure 39. The optimal value of tag readability can be

achieved when the speed is 10 mph and the distance is 100 inch.

101

Conclusions:

The study focuses on deriving statistical characterization and models that lead to

an optimal design of an RFID system for a specific application of vehicle ingress/egress

monitoring system in a warehouse environment. All the PIVs that are known to influence

the readability of an RFID system are considered and a method based on quality function

deployment (QFD) [34] is used to systematically determine a compact set of KPIVs.

From the study, the influence of distance, tag orientation, speed of the vehicle, and reader

make has been clearly delineated and rationalized based on electromagnetism. It has been

shown that the readability undergoes a polynomial decrement with increase in distance

(i.e. read range). In addition, the readability decreases linearly with increase in speed.

Maximum read rate is obtained when the tag is placed in parallel with respect to the

reader antenna i.e. when °= 0yθ . Thus, statistical analysis helps in determining an

optimal value of distance, speed, orientation, and other KPIVs for a particular

implementation of an RFID system for ingress/egress monitoring.

102

Appendix A

A.1 Reader Make

Readers used in any applications play an important role in how efficient the

system would be. Some of the features of the reader and the types of reader used in our

experiments are discussed below. Frequency of operation, ISO or EPC compliant, read

distance depending on the manufacturer, isolation of the reader from the influence of

other readers are some of the factors that depend on the reader make and that also

influence the efficiency of the RFID system. We have used two makes of readers,

namely, AWID (MPR 2010AN) and Alien (ALR 9774) reader for the experimentation.

• MPR-2010AN (see Figure 40) is a stationary reader that is able to decode EPC

C1, ISO-18000-6 Type B and EM Micro. It is designed to be upgradeable to EPC

C1G2 (Class 1 and Generation 2). This reader comes with a near ideal circular-

polarized antenna. (A circular polarized antenna radiates energy in both the

horizontal and vertical planes and all planes in between) so that tags in random

orientations can be captured. The reader is claimed to have a tag dependent range

of 12 to 18 feet (3.6 to 5.5 meters).

Figure 40 : Photograph of an AWID (MPR 2010AN) Reader[33]

103

• Alien readers support all EPC Gen1 protocols. They allow easy integration with

middleware and enterprise software. They are equipped with high capacity

memory to store tag history, have circularly polarized antennas and have a tag

dependent range of 8-12 feet [8] .

Figure 41 : Photograph of an Alien (ALR 9774) reader [8]

A.2 Communication frequency standards:

The selection of appropriate carrier frequency depends on various factors like, the

application requirement, environment in which the RFID system is used, desired read

range, and the air interface protocol used. The environment for vehicle ingress/egress

monitoring usually contain objects like the container, vehicle parts, etc., electronic parts

like the vehicle control systems, plastic parts of the vehicle and cardboards enclosing the

products transported by the vehicle. The EPC has specified standards for tag data storage

and management for frequencies suitable to HF and UHF frequencies. Furthermore, the

read range desired for this application is more than three feet. Lower frequency standards

such as 13.56 MHz or the HF thus becomes unsuitable for this application [41]. Also, the

size of tag and reader antennas are related to the size of the wave, and UHF being a short

wave as compared to HF, it requires small size antennas. In addition, UHF frequency is

widely used in civil communication like GMRS (General Mobile radio Service). Thus,

the most suitable frequency for the application in vehicle ingress/egress monitoring

system is 902-928 MHz or UHF.

104

A.3 Tag-make and form factors:

The tags used for this application must be durable as well as cheap. We

investigate the use of EPC Class 1 tags as well as ISO tags complaint with ISO 18000-6

standards [32]. EPC tags are cheaper and allow user defined conventions to write data

into the tag [9].

The tags that are used in the experiment are AWID models, Prox-Linc (MT APL

1216) and Prox-Linc (MT APT 1014) and Alien models 9354 and 9338 tags.

Figure 42 : AWID (MT APL 1216) tags for metallic surfaces

AWID Prox Linc MT APL 1216 tags are designed for mounting directly on metal

or other materials. They use a protective plastic to house the circuit and antenna. They

allow long read range and are compatible with MPR-2010 readers[33]. AWID Prox-Linc

(MT APT 1014) tag circuits are printed on a flexible, clear plastic. They allow a read

range of 9 to 11 feet when the tag is attached by self-adhesive to the inside of the

vehicle's windshield, as per installation instructions [7].

105

Figure 43 : AWID MT APT 1014 tags[33]

Alien 9354 (M tag) tag (see Figure 44) allow very high gain, and have low

environmental dependence.

Figure 44 : Aperture coupled patch antenna used for Alien 9354 tag[8]

The Alien 9338 ("Squiggle T" tag) tag have a small form factor and are very

inexpensive.

106

Figure 45 : Folded dipole antenna[8]

The tags used for this application must be durable as well as cheap. We propose to

use EPC Class 1 tags for the following reasons:

1. These tags are cheap [4]

2. User can use his conventions to write data on the tag

When using ISO based tags, we propose tags compliant to ISO 18000-6 standards

[32].

A.4 Tag Protocol and Standards

A protocol is the standard way or a language for communicating across a network.

The tags that follow the same class are developed in a way that they achieve

interpretability between different tags and readers. The two classes of protocols that are

used in the 900 MHz range are ISO- 18000 part 6 and EPC. These standards deal with

air-interface protocol, data content, conformance with regulatory requirements, and

application. A brief explanation of the two major standards is provided below.

EPC has specified standards for tag data content, communication between a tag

and a reader (air- interface protocols), reader protocols, Savant (Savant is a platform used

for reading data from different types of readers, data filtering and logging the data or

events into various devices) 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 (Generation 1) is already in use and

version 2 (Generation 2) is ratified and is being adopted. As per Generation 1 standard,

data is stored on the tag, in the format as shown in Figure 46. Companies like Texas

Instruments, Impinj, Philips Semiconductors, Alien Technology, Symbol Technologies

and Intermec Technologies have announced that they are at various stages in the

manufacturing of Generation 2 tags.

107

Figure 46 : Tag Data Partition[37]

ISO 18000-6 Part 6 standards set parameters for Air Interface Communications at

860 to 930 MHz frequency range. These standards also specify parameters like data

encoding rules, data transmission rates, types of signal modulations and anti-collision

protocols. Efforts are underway to form a unique standard that will avail a common

platform for widespread adoption of RFID technology all over the world.

A.5 Read range

The operating range is defined as a tag’s maximum distance from the interrogator

(reader) in order to satisfy the ASIC’s (Application Specific Integrated Circuit) power

consumption. For the tag to operate properly there has to be a minimum voltage induced

on the tag to turn on all the electronics in the tag, near the reader antenna. The power

received rP by a passive tag antenna is calculated given by

2

2

)4(

)(

R

GGPP rttr π

λ⋅⋅= (1)

Where, Pt is the power transmitted by the reader antenna (transmitter antenna), rG

is the gain of the tag antenna, tG is the gain of the reader antenna, R is the distance of

the tag from reader and λ is the wavelength of the EM RF waves, which for the

considered frequency range of 900 MHz is approximately 0.3m. Also )( tt GP ⋅ is called

the Effective Radiated Power (ERP).

As can be seen from the above formula, the power received by the tag is inversely

proportional to the square of the distance from the reader antenna. Hence, as the tag

moves away from the reader, the performance of the RFID system decreases.

108

A.6 Orientation of the tag

Orientation of a tag relative to a reader affects the polarization of the tag antenna

with respect to the reader antenna. Polarization is important in wireless communications

systems. Polarization, also called wave polarization, is an expression of the orientation of

the lines of electric flux in an EM field. Polarization can be constant i.e., remains in a

particular orientation at all times, or it can vary with each wave cycle. The physical

orientation of a wireless antenna corresponds to the polarization of the radio waves

received or transmitted by that antenna. Thus, a vertical antenna receives and emits

vertically polarized waves, and a horizontal antenna receives or emits horizontally

polarized waves. The best short-range communications is obtained when the transmitting

and receiving antennas have the same polarization.

The Friis transmission equation that was used in the analysis before can be

modified to include the influence of polarization of the antenna [43].

204 R

PeW tt π

=

Figure 47 : Geometrical orientation of transmitting and receiving antennas for Friis transmission

equation (1)

( ) ( ) ( )( )

222

2

, ,ˆ ˆ , (2)

4 4

t t t r r r t

r r r r r t t r t r

D D PP e D W e e

R

λ θ φ θ φλθ φ ρ ρ

π π

= =

�

Where,

109

te and re is the radiation efficiency of the transmitting antenna and receiving

antenna respectively

tP is the input power at the transmitter antenna

tW is the isotropic power density at the transmitter

( ),t tG θ φ is the gain in the direction ( ),t tθ φ

( ),t t tD θ φ is the directivity of the transmitting antenna in the direction ( ),t tθ φ

rA is the effective area of the receiving antenna

t t θ is tag orientation angle θy

t φ is the tag orientation angle θz

The power received assumes that the transmitting and receiving antennas are

matched to their respective lines or loads (reflection efficiencies are unity) and the

polarization of the receiving antenna is matched to the impinging wave (polarization

efficiency is unity). 2

ˆˆ rt ρρ ⋅ is called the polarization loss factor.

From the formula, it can be seen that the polarization loss factor is directly

proportional to the power received by the tag antenna. Hence, if there is a polarization

mismatch, the efficiency of the RFID system will be decreased. For reflection and

polarization matched antennas aligned for maximum directional radiation and reception,

the power received reduces to the form in Equation (1).

A.7 Speed

An antenna radiates a given amount of power into free space, and ideally, this

power propagates without loss in all directions. For the antenna that is used in the reader,

the gain is optimized in one direction so the power flow in that direction will be higher

than the power flow in any other direction. Considering the tag antenna to be in the

vicinity of the reader antenna and moving at a constant rate, if the speed of the tag

antenna is less than the propagation delay (it is the time lag between the departure of a

signal from the source and the arrival of the signal at the destination) at that particular

110

direction, then the tag will be recognized. The polarization loss factor and directivity of

the antenna in that particular direction must also be considered. The Doppler shift that

occurs due to the movement of the tag antenna near the reader and how well the receiver

clock recovers from that shift has to be explored. The shift in center frequency of the

receiver in the reader antenna must be studied also. Further investigation is needed here

to justify this fact. To study the propagation delay, some indoor propagation models must

be explored in detail.

111

Appendix B

Table B1: Full factorial multi-level design and results with eight replicates for each run

Run

Reader

Make

(R)

Distance

(D)

(inch)

Speed

(S)

(mph)

θy

(degrees) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Ybar

1 Alien 20 0 0 1 1 1 1 1 1 1 1 1

2 Alien 20 0 90 1 1 1 1 1 1 1 1 1

3 Alien 20 10 0 1 1 1 1 1 1 1 1 1

4 Alien 20 10 90 1 1 1 1 1 1 1 1 1

5 Alien 20 20 0 1 1 1 1 1 1 1 1 1

6 Alien 20 20 90 0 1 1 0 0 1 1 1 0.625

7 Alien 45 0 0 1 1 1 1 1 1 1 1 1

8 Alien 45 0 90 1 1 1 1 1 1 1 1 1

9 Alien 45 10 0 1 1 1 1 1 1 1 1 1

10 Alien 45 10 90 1 1 1 0 1 1 1 1 0.875

11 Alien 45 20 0 1 1 1 1 1 1 1 1 1

12 Alien 45 20 90 0 0 1 1 1 1 1 1 0.75

13 Alien 50 0 0 1 1 1 1 1 1 0 1 0.875

14 Alien 50 0 90 1 1 1 1 1 1 1 1 1

15 Alien 50 10 0 1 1 1 1 1 1 1 1 1

16 Alien 50 10 90 1 1 1 1 1 1 1 1 1

17 Alien 50 20 0 0 1 1 1 1 1 1 1 0.875

18 Alien 50 20 90 0 0 0 1 1 1 1 1 0.625

19 Alien 72 0 0 1 1 1 1 1 1 1 1 1

20 Alien 72 0 90 0 0 1 1 1 1 1 1 0.75

21 Alien 72 10 0 0 1 1 1 1 1 1 1 0.875

22 Alien 72 10 90 0 1 0 1 1 1 1 1 0.75

23 Alien 72 20 0 1 1 0 0 1 1 1 1 0.75

24 Alien 72 20 90 0 0 0 0 1 1 1 1 0.5

112

Run

Reader

Make

(R)

Distance

(D)

(inch)

Speed

(S)

(mph)

θy

(degrees) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Ybar

25 Alien 85 0 0 1 1 1 1 1 1 1 1 1

26 Alien 85 0 90 1 0 0 1 1 1 1 1 0.75

27 Alien 85 10 0 1 1 1 1 1 1 1 1 1

28 Alien 85 10 90 0 1 1 1 1 1 1 1 0.875

29 Alien 85 20 0 0 1 1 1 1 1 1 1 0.875

30 Alien 85 20 90 0 0 1 1 1 1 1 1 0.75

31 Alien 100 0 0 1 1 1 1 1 1 1 1 1

32 Alien 100 0 90 0 1 0 0 1 1 1 1 0.625

33 Alien 100 10 0 1 1 0 0 1 0 1 1 0.625

34 Alien 100 10 90 0 0 0 0 0 1 0 0 0.125

35 Alien 100 20 0 0 0 0 0 0 0 0 0 0

36 Alien 100 20 90 0 0 0 0 0 0 0 1 0.125

37 Alien 115 0 0 1 1 1 1 1 1 1 1 1

38 Alien 115 0 90 0 1 0 1 1 0 1 1 0.625

39 Alien 115 10 0 0 1 1 1 0 1 1 1 0.75

40 Alien 115 10 90 0 0 0 1 1 0 0 0 0.25

41 Alien 115 20 0 0 0 0 0 0 0 0 0 0

42 Alien 115 20 90 0 0 0 0 0 0 0 0 0

43 Alien 125 0 0 1 1 1 1 1 1 1 1 1

44 Alien 125 0 90 0 1 0 1 0 1 1 0 0.5

45 Alien 125 10 0 0 1 0 0 0 0 1 1 0.375

46 Alien 125 10 90 0 0 1 0 1 1 1 1 0.625

47 Alien 125 20 0 0 0 0 1 0 0 0 1 0.25

48 Alien 125 20 90 0 0 0 0 0 0 0 0 0

49 Alien 145 0 0 1 1 1 1 0 1 1 1 0.875

50 Alien 145 0 90 0 0 0 0 0 0 0 0 0

51 Alien 145 10 0 0 0 0 0 0 0 0 0 0

113

Run

Reader

Make

(R)

Distance

(D)

(inch)

Speed

(S)

(mph)

θy

(degrees) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Ybar

52 Alien 145 10 90 0 0 0 0 0 0 0 0 0

53 Alien 145 20 0 0 0 0 0 0 0 0 0 0

54 Alien 145 20 90 0 0 0 0 0 0 0 0 0

55 Alien 180 0 0 1 0 1 1 1 1 1 1 0.875

56 Alien 180 0 90 0 0 0 0 0 0 0 0 0

57 Alien 180 10 0 0 0 0 0 0 0 0 0 0

58 Alien 180 10 90 0 0 0 0 0 0 0 0 0

59 Alien 180 20 0 0 0 0 0 0 0 0 0 0

60 Alien 180 20 90 0 0 0 0 0 0 0 0 0

61 AWID 20 0 0 1 1 1 1 1 1 1 1 1

62 AWID 20 0 90 1 0 1 1 1 1 1 1 0.875

63 AWID 20 10 0 1 1 1 1 0 1 0 0 0.625

64 AWID 20 10 90 0 0 0 0 0 0 0 0 0

65 AWID 20 20 0 0 0 0 0 0 0 0 0 0

66 AWID 20 20 90 0 0 0 0 0 0 0 0 0

67 AWID 45 0 0 1 1 1 0 1 1 1 1 0.875

68 AWID 45 0 90 0 0 0 0 0 0 0 0 0

69 AWID 45 10 0 0 0 0 0 0 0 0 0 0

70 AWID 45 10 90 0 0 0 0 0 0 0 0 0

71 AWID 45 20 0 0 0 0 0 0 0 0 0 0

72 AWID 45 20 90 0 0 0 0 0 0 0 0 0

73 AWID 50 0 0 1 1 1 0 1 0 0 1 0.625

74 AWID 50 0 90 0 0 0 0 0 0 0 0 0

75 AWID 50 10 0 0 0 0 0 0 0 0 0 0

76 AWID 50 10 90 0 0 0 0 0 0 0 0 0

77 AWID 50 20 0 0 0 0 0 0 0 0 0 0

78 AWID 50 20 90 0 0 0 0 0 0 0 0 0

114

Run

Reader

Make

(R)

Distance

(D)

(inch)

Speed

(S)

(mph)

θy

(degrees) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Ybar

79 AWID 72 0 0 1 1 1 0 1 0 0 0 0.5

80 AWID 72 0 90 0 0 0 0 0 0 0 0 0

81 AWID 72 10 0 0 0 0 0 0 0 0 0 0

82 AWID 72 10 90 0 0 0 0 0 0 0 0 0

83 AWID 72 20 0 0 0 0 0 0 0 0 0 0

84 AWID 72 20 90 0 0 0 0 0 0 0 0 0

85 AWID 85 0 0 1 1 1 0 0 0 0 0 0.375

86 AWID 85 0 90 0 0 0 0 0 0 0 0 0

87 AWID 85 10 0 0 0 0 0 0 0 0 0 0

88 AWID 85 10 90 0 0 0 0 0 0 0 0 0

89 AWID 85 20 0 0 0 0 0 0 0 0 0 0

90 AWID 85 20 90 0 0 0 0 0 0 0 0 0

91 AWID 100 0 0 1 1 1 0 0 1 0 0 0.5

92 AWID 100 0 90 0 0 0 0 0 0 0 0 0

93 AWID 100 10 0 0 0 0 0 0 0 0 0 0

94 AWID 100 10 90 0 0 0 0 0 0 0 0 0

95 AWID 100 20 0 0 0 0 0 0 0 0 0 0

96 AWID 100 20 90 0 0 0 0 0 0 0 0 0

97 AWID 115 0 0 1 0 1 0 0 0 0 1 0.375

98 AWID 115 0 90 0 0 0 0 0 0 0 0 0

99 AWID 115 10 0 0 0 0 0 0 0 0 0 0

100 AWID 115 10 90 0 0 0 0 0 0 0 0 0

101 AWID 115 20 0 0 0 0 0 0 0 0 0 0

102 AWID 115 20 90 0 0 0 0 0 0 0 0 0

103 AWID 125 0 0 1 1 0 0 0 0 0 0 0.25

104 AWID 125 0 90 0 0 0 0 0 0 0 0 0

105 AWID 125 10 0 0 0 0 0 0 0 0 0 0

115

Run

Reader

Make

(R)

Distance

(D)

(inch)

Speed

(S)

(mph)

θy

(degrees) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Ybar

106 AWID 125 10 90 0 0 0 0 0 0 0 0 0

107 AWID 125 20 0 0 0 0 0 0 0 0 0 0

108 AWID 125 20 90 0 0 0 0 0 0 0 0 0

109 AWID 145 0 0 0 0 0 0 0 0 0 1 0.125

110 AWID 145 0 90 0 0 0 0 0 0 0 0 0

111 AWID 145 10 0 0 0 0 0 0 0 0 0 0

112 AWID 145 10 90 0 0 0 0 0 0 0 0 0

113 AWID 145 20 0 0 0 0 0 0 0 0 0 0

114 AWID 145 20 90 0 0 0 0 0 0 0 0 0

115 AWID 180 0 0 0 0 0 0 0 0 0 0 0

116 AWID 180 0 90 0 0 0 0 0 0 0 0 0

117 AWID 180 10 0 0 0 0 0 0 0 0 0 0

118 AWID 180 10 90 0 0 0 0 0 0 0 0 0

119 AWID 180 20 0 0 0 0 0 0 0 0 0 0

120 AWID 180 20 90 0 0 0 0 0 0 0 0 0

116

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117

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