RFID를 활용한 유비쿼터스 서비스
2005년 4월 15일
권오병
경희대학교 국제경영학부
obkwon@khu.ac.kr
Ubiquitous services & Biz model
Level of
services
Business
viability
Technical viability
Ubiquitous services & Biz model
H
Technical
Technical
Technical
Technical
Technical
Feasibility
Feasibility
Feasibility
Feasibility
Feasibility
Technical
Technical
Technical
Business
Business
Feasibility
Feasibility
Feasibility
Feasibility
Feasibility
L
L
Technical
Technical
Technical
Level
Levelof
of
Feasibility
Feasibility
Feasibility
Service
Service
H
Service Architecture
Context
inference
module
Context DB
Events
acquisition
module
Action
request module
Context subsystem
Application
system
Database
Management
Subsystem
Dialogue subsystem
Sensors
End users
Anytime anywhere
With any devices
Multimodal
Controller
Web
Augmented
Multimedia ……
Reality
……
RFID-Based Ubiquitous Services
 Some cases
 NAMA-RFID
 RFID-Based Reminder System
 NAMA-US
 RFID-Based Community Computing
Some cases
 CAM
 Security control
 Ads
 Home management
 Healthcare
 Convention
 Automobile maintenance
 Environment
 Smart elevator, etc.
(COEX, 2005)
CAM
CAM
CAM
Security control
NAMA-RFID
RFID-based reminder system
Reminder System
 Manual input of reminding
condition
 Personal resources are not
machine understandable
RFID-Based
Context Aware
Applications
Semantic web
Context-aware Reminder System
 Proactive reminder
 Automated need
identification
Need Identification
Any other
products?
Need
revelation
Intention to expire
the gap
Tension about
the gap
Identification of
current state
What to buy?
Product
brokering
Buyer
coalition
formation
Need
identification
Merchant
brokering
Identification of
goal state
Gap between the
current and goal
states
Whom to buy from?
Under what terms?
Product service
and evaluation
How is it going?
Negotiation
Purchase
and
delivery
Credit cards, By air, by ship?
Customer Buying Behavior Model
Associative Theory for
Need Identification Support
 Rescorla–Wagner’s model
V   (  VT )
 The change of the strength of association consists of the strength of
conditional stimulus , the strength of unconditional stimulus , and the
differences between the strength of association of unconditional
stimulus and the strength of overall association.
Contex
t
Stimulus
Contex
t
Stimulus
Buying
Need
Identification Intention
(problem)
Buying
Need
Identification Intention
(solution 1)
Contex
t
Reminder
Stimulus
Buying
Need
Identification Intention
(solution 2)
Gerlach and Kuo’s Model (1991)
Amended Model
Internal
Context (e.g. URL)
Personal
resources
e-Wallet
web service
Need Aware
Reminder
System
(NAMA)
External
context
(e.g. current
location)
Context
web service
Web service
matchmaker
Web
services
Ontology
E-Wallet ontology
- Personal Profile
- Personal Preference
- To Purchase List
NAMA – Need Aware Multi Agent
Serivce
InternetShop
User Information
User Preference
Food
kind
price
price
satisfaction
kind
satisfaction
Detail Setting
Hello, Joe!
This is NAMA Service.
Connecting to NAMA Agent
04.09.06 18:00
OpenHall
Context ontology
- Time
- Location
- User location
- Entity location
- URL
Service ontology
NAMA-RFID Architecture
Context in NAMA-RFID
 Time
 Current time
 Available service time
 Location
 RDIF-based
 Identity
 User ID
 Entity
 Currently available
services/shops
RFID recognition
Ci  Ti , I i , Li , Ei 
Cobkwon@ khu.ac.kr  2005  04  15  10 : 00am,
{andy @ khu.ac.kr, sjpark @ kgsm.ac.kr},
"WeanHall " ,163.180.99.54 
Context-ware Need
Identification
NAMA Agent
• Acquiring context data from RFID
- User ID
• Acquiring user profile/preference
from E-Wallet
• Context-aware need identification
- identify needs with
- user profile based reasoning
- to purchase lists in E-wallet
- using CBR
Context Information
Time
2004. 09. 06 12:30:00
Identity
Joe
Location
Dorm Hall
Entity
McDonald
Log Information
NAMA Agent
Joe is connecting to NAMA Agent
Receiving Joe’s Information…
Conneting to E-Wallet Web Service to get Joe’s Information.
Crawling Context Information.
Do Need Identification…… Wait…………
OK.
Joe’s Needs are below
Food, Book
Save Log File
Context Setting
Context-ware Need
Identification
Case base
Adding new case
Reasoning results
Service Match Making
•Constraint-based search & Case-based reasoning
•User preference estimation on a web service
w1 * Contextual _ Pref (c1 , c2 ,..., cm | s1 , s2 ,..., s n ) 
w2 *User _ Preference( p1 , p2 ,... pk )
where Ci is the ith contextual feature, Sj s the jth static feature, and Pk is the kth preference score
n / a, if the preference is not asserted by ontology
Static _ Pref ( s1 , s2 ,..., sn )  
k , otherwise

where k is an integer value range from (0,N), where N is the maximum score
e.g.: Static _ Pr ef (" FoodSpecial" , " School" )  5
Service Selection
NAMA
NAMA –– Need
Need Aware
Aware Multi
Multi Agent
Agent
Serivce
Serivce
NAMA
NAMA –– Need
Need Aware
Aware Multi
Multi Agent
Agent
InternetShop
Information
User InformationUserUser
Preference User Preference
Mc
KYMusic
KYLIB
KYFood
Serivce
Serivce
InternetShop
Information
User InformationUserUser
Preference User Preference
Mc
OpenLIB
Hello,
Hello, Joe!
Joe!
This
is
This is NAMA
NAMA Service.
Service.
Connecting
Connecting to
to NAMA
NAMA Agent
Agent
04.09.06
04.09.06 18:00
18:00
OpenHall
OpenHall
<typical reminder>
Wait…
Hello, Joe!
Receiving
McDonald
This is NAMA
Service.Web Service.
Choose
WebtoService.
Connecting
NAMA Agent
04.09.06
04.09.06 18:00
18:00
DormHall
OpenHall
<need-aware reminder>
Service Scenario
Actual Interface
User Test
Sample size = 209
7.15*
SelfEfficacy
-
Perceived
Ease-of-use
2.59*
5.44*
Behavior
Intention
4.61*
Preference
New-Tech.
-
Perceived
Usefulness
6.63*
Summary
 NAMA-RFID




Inviting Associative theory toward Automated Need Identification
Multi-agent based web services
Open personal resources (E-Wallet)
Could be a good application of context-aware mobile service
NAMA-US
 Applying community computing concepts
 Functions of community computing





1.
2.
3.
4.
5.
Knowing each other
Sharing preference and knowledge over the Internet
Generating consensus for heterogeneous communities
Supporting everyday life by multi-agent technologies
Assisting social events by personal digital assistants
Large
Size
of
Group
Small
Local area
decision
net
Computer
conference
Decision
room
Electronic
video
conferencing
Teleconferencing
Decision
conferencing / Broadcasting
well-known
anonymous
Multiple
Individuals
Single
group
Locus of participants
Multiple
groups
Virtual ad hoc conference
with RFID and Mobile devices
Based on community computing and
need identification technology
Service
brokering
Need
revelation
Identification of
current state
What to get
served?
Buyer
coalition
formation
Any other
services?
From whom to buy?
Need
identification
Intention to expire
the gap
Identification of
goal state
Merchant
brokering
Under what terms?
Service
evaluation
Tension about
the gap
Gap between the
current and goal
states
How is it going?
Negotiation
Purchase
and
delivery
Credit cards,
phone banking,
etc.?
Community member 1
Need
revelation
Identification of
current state
Intention to
expire the gap
Identification of
goal state
Tension about
the gap
Gap between the
current and goal
states
Agent Community
UUDI for Agent list
Service
brokering
What to get
served?
From whom
to get served?
Need
identification
Community member 2
Need
revelation
Any other
services?
Group
formation
Agent
brokering
Under
what terms?
Identification of
current state
Service
evaluation
Intention to
expire the gap
Identification of
goal state
Tension about
the gap
Gap between the
current and goal
states
How is it going?
Negotiation
Purchase
and
get served
Credit cards,
phone banking,
etc.?
Content for need Identification
Steps
Static content
(E-Wallet, manual)
Identification of current
state
User profile
Identification of goal
state
Wish list
To get served list
Contextual
content(RFID, E-Wallet)
Current location
Current time
Current activity
Gap between the current
and goal states
Tension about the gap
Perceived sensitivity of
contextual pressure
Contextual pressure
Due duration of get
served
Intention to expire the
gap
Eagerness to get served
Social context
Availability of services
Need revelation
Users’ commitment to
get served
Community
Contextually assigned group
B
A
a
b
c
d
D
E
c
f
g
h
f
h
k
t
u
v
RFID reader
RFID reader
RFID reader
b
c
e
RFID reader
RFID reader
RFID Tag
GDSS
Task agent
RFID Tag
c, k
RFID data
Context-aware
group formation
Dispatched to
GDSS
Task agent
c, k
RFID Tag
C
GDSS
Task agent
k, m
NAMA-US
GDSS
Task agent
f, g, h
 GDSS Task Agent






Negotiation
Voting
Knowledge share
Idea generation
Auction / Reverse auction
etc.
Summary
 RFID is nothing but a sensor. However,




Can be hidden (cf. OCR)
Attachable
In- and out-door (cf. GPS)
Cost effective ?
 RFID-based context aware computing
 Business model?
 Level of Service of RFID-based service
 Operational feasibility
− Who is willing to provide?
 Technical feasibility
− Privacy concern
 Economical feasibility
− Potential competitor