03 about rtls

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 1/25

 About RTLS

2005.01.11

Kim, Chang Soon

Super Computing Laboratory 

Dept . of Computer Science, Yonsei Univ .

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 2/25

 Supercomputing Laboratory2

RTLS

Real Time Location/Locating System

 ± Fully automated systems that continually monitor the

locations of assets

 ± Usually utilizes active RFID tags Why RFID?

 ± Other technologies

� WLAN

 ± High cost, power consumption

� GPS

 ± High cost, not applicable to the indoor building

 ± RFID

� Low cost, low power consumption

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 3/25

 Supercomputing Laboratory3

Types of RTLS

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 4/25

 Supercomputing Laboratory4

Research Issues

Location Decision

 ± TDO A / SRO A / Based on signal strength

Management of the location information inreal-time

Mechanism to provide the location

information to the client (user)

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 5/25

 Supercomputing Laboratory5

INCITS T20

ANSI Standard, 2003

Consist of 

 ± Two Air Interface (2.4GHz / 433MHz)

 ± One API (Web Service)

Terminologies

 ± RTLS transmitter: active radio transmitters(tags)

� Use DSSS (direct sequence spread spectrum)

anti-collision protocols are not required

 ±RTLS Reader 

 ± RTLS server: aggregates from the RTLS readers.

 ± Signpost/exciter: alter the rate of transmission of an RTLS

transmitter 

 ± Blink: spread spectrum radio frequency transmission

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 6/25

 Supercomputing Laboratory6

INCITS T20 (cont¶)

Architecture

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 7/25

 Supercomputing Laboratory7

INCITS T20 (cont¶)

Lack of T20

 ± It is fit well for F acility RTLS ,

but not for Enterprise/Private RTLS 

 ± It is not consider the mechanism about processing of massive data

� e.g) filtering, «

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 8/25

 An Ubiquitous Framework and Protocolfor Object Tracking using RFID Tags

Pradip De, Kalyan Basuand and Sajal K. Das. University of Texas

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 9/25

 Supercomputing Laboratory9

Contents

Introduction

Network Architecture

The Object Tracking Protocol

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 10/25

 Supercomputing Laboratory10

Introduction

Higher risky transaction process ± Multitude of products

 ± Complexity in the international supply demand

Major issues in t

he ch

ain(SCM

) ± Visibility

� Detailed knowledge of what is going on in other parts of thechain

 ± Control

 ± Good visibility + lack of control = required changescannot be effected within a short time

Solution ± Real time tracking of transacted objects

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 11/25

 Supercomputing Laboratory11

Network Architecture

RFID Readers

 ± RMM(Reader Management Module)

� Captures the EPC of the tag

� Captures the EPC or ID of the reader 

� Captures the reading timestamp

Savants

 ± Smoothen and aggregate the data

coming from the readers

 ± Correct errors

 ± Operations

� Data capturing / monitoring / transmission

PML Servers

 ± Store PML files

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 12/25

 Supercomputing Laboratory12

PML Servers

H-PML (Home PML)

 ± Contains information about an object owned by organization

 ±  Adopts the concept of Cellular system

� HLR / VLR

GW-PML (Gateway PML)

 ± To handles queries and

transaction with other 

organizations

 ±  Act as a protocol converter 

N etwork Architecture

Intra Organization Netowrk

Inter Organization Netowrk

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 13/25

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 14/25

 Supercomputing Laboratory14

HLR/VLR HLR/VLR

The Object Tracking Protocol

T riplet 

 ± <EPC_Id, Timestamp, Reader_Id>

HLR

 ± Updates the current location

 ± Keeps a history of locations

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 15/25

LAND

MARC

:Indoor LocationSensing Using Active RFID

Lionel M. Ni, Yunhao Liu, YiuC

ho Lau, Michigan stateU

niversity

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 16/25

 Supercomputing Laboratory16

Features

Algorithm for indoor location sensing

Uses reference tags

 ± Serve as reference points

Advantages ± No need for a large number of RFID readers

 ± Environmental dynamics can easily be accommodated

 ± Location information is accurate

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 17/25

 Supercomputing Laboratory17

LANDMARC approach

RFID read ranges

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 18/25

 Supercomputing Laboratory18

LANDMARC approach (cont¶)

Reader 

 ± Will scan from range 1 to 8 and keep repeating the cycle

 ± Calculates the Signal Strength Vector 

� Of Tracking tag: S = (S1, S2, «, Sn)

� Of Reference tag: = (1, 2, «, n) ± Obtain the coordinate (x,y) of tracking tag

� using k-nearest neighbor algorithm (by Euclidian distance)

 ± Example

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 19/25

Proposal

2005.01.11

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 20/25

 Supercomputing Laboratory20

(domain).

 ± ,, DBq.

 ± ,q

.

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 21/25

 Supercomputing Laboratory21

³T 1 ´ previous location?

 ± Sol.) RFID Reader Writer 

� Reader  ID announcement.

� c.f) Mobile IP, Cellular system

receive new

reader ID?REPORT

REPORTwrite new

reader ID

yes

no | timeout

<Fl ow Chart of a Tag>

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 22/25

 Supercomputing Laboratory22

Example

Q. Reader  ID RTLS

Server ?

 ± e.g) 03  A

 ± Sol.)

� ID EPC .

� ONS resolution.

annooun.<11>

report<id, 03> & store <11>

T1 11

notify <T 1, B>

B

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 23/25

 Supercomputing Laboratory23

2

Massive Data.

 ± Sol.) 2-Level Filtering(??)

� RFID Reader level

 ± reader  cache

..

� RTLS Server level:

 ± Context Engine massive data.

 ± Context Engine RTLS Server (??).

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 24/25

 Supercomputing Laboratory24

2-Level Filtering(??)

8/6/2019 03 About Rtls

http://slidepdf.com/reader/full/03-about-rtls 25/25

 Supercomputing Laboratory25

 ± domain real-time object tracking

 ± Massive data scalability

� u

 ±

 ± «

 ± architecture

� Context Engine

 ±