03 about rtls
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About RTLS
2005.01.11
Kim, Chang Soon
Super Computing Laboratory
Dept . of Computer Science, Yonsei Univ .
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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
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Supercomputing Laboratory3
Types of RTLS
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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)
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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
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Supercomputing Laboratory6
INCITS T20 (cont¶)
Architecture
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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, «
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An Ubiquitous Framework and Protocolfor Object Tracking using RFID Tags
Pradip De, Kalyan Basuand and Sajal K. Das. University of Texas
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Contents
Introduction
Network Architecture
The Object Tracking Protocol
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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
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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
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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
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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
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LAND
MARC
:Indoor LocationSensing Using Active RFID
Lionel M. Ni, Yunhao Liu, YiuC
ho Lau, Michigan stateU
niversity
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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
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LANDMARC approach
RFID read ranges
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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
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Proposal
2005.01.11
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(domain).
± ,, DBq.
± ,q
.
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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>
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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
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2
Massive Data.
± Sol.) 2-Level Filtering(??)
� RFID Reader level
± reader cache
..
� RTLS Server level:
± Context Engine massive data.
± Context Engine RTLS Server (??).
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2-Level Filtering(??)
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± domain real-time object tracking
± Massive data scalability
� u
±
± «
± architecture
� Context Engine
±
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