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RFID 를 활용한 유비쿼터스 서비스

RFID 를 활용한 유비쿼터스 서비스. 2005 년 4 월 15 일 권오병 경희대학교 국제경영학부 obkwon@khu.ac.kr. Level of services. Business viability. Technical viability. Ubiquitous services & Biz model. Ubiquitous services & Biz model. Service Architecture. RFID-Based Ubiquitous Services. Some cases NAMA-RFID

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RFID 를 활용한 유비쿼터스 서비스

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  1. RFID를 활용한 유비쿼터스 서비스 2005년 4월 15일 권오병 경희대학교 국제경영학부 obkwon@khu.ac.kr

  2. Level of services Business viability Technical viability Ubiquitous services & Biz model

  3. Ubiquitous services & Biz model

  4. Service Architecture

  5. RFID-Based Ubiquitous Services • Some cases • NAMA-RFID • RFID-Based Reminder System • NAMA-US • RFID-Based Community Computing

  6. Some cases (COEX, 2005) • CAM • Security control • Ads • Home management • Healthcare • Convention • Automobile maintenance • Environment • Smart elevator, etc.

  7. CAM

  8. CAM

  9. CAM

  10. Security control

  11. NAMA-RFIDRFID-based reminder system Reminder System Semantic web • Manual input of reminding condition • Personal resources are not machine understandable Context-aware Reminder System RFID-Based Context Aware Applications • Proactive reminder • Automated need identification

  12. Need revelation Identification of current state Intention to expire the gap Identification of goal state Gap between the current and goal states Tension about the gap Need Identification Any other products? Buyer coalition formation Product brokering What to buy? Whom to buy from? Need identification Merchant brokering Under what terms? Product service and evaluation Negotiation Purchase and delivery Credit cards, By air, by ship? How is it going? Customer Buying Behavior Model

  13. Context Buying Intention Need Identification Stimulus (problem) Associative Theory forNeed Identification Support • Rescorla–Wagner’s model • 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. Context Context Buying Intention Buying Intention Need Identification Need Identification Reminder Stimulus (solution 1) (solution 2) Stimulus

  14. Gerlach and Kuo’s Model (1991)

  15. Amended Model Personal resources Internal Context (e.g. URL) e-Wallet web service Need Aware Reminder System (NAMA) Web service matchmaker External context (e.g. current location) Web services Context web service

  16. Ontology E-Wallet ontology - Personal Profile - Personal Preference - To Purchase List Context ontology - Time - Location - User location - Entity location - URL Service ontology

  17. NAMA-RFID Architecture

  18. Context in NAMA-RFID • Time • Current time • Available service time • Location • RDIF-based • Identity • User ID • Entity • Currently available services/shops

  19. RFID recognition

  20. Context-ware Need Identification • 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

  21. Context-ware Need Identification Case base Adding new case Reasoning results

  22. Service Match Making • Constraint-based search & Case-based reasoning • User preference estimation on a web service where Ci is the ith contextual feature, Sj s the jth static feature, and Pk is the kth preference score where k is an integer value range from (0,N), where N is the maximum score e.g.:

  23. Service Selection <need-aware reminder> <typical reminder>

  24. Service Scenario

  25. Actual Interface

  26. User Test Sample size = 209 Self- Efficacy Perceived Ease-of-use 7.15* 2.59* - Behavior Intention 5.44* 4.61* 6.63* Preference New-Tech. Perceived Usefulness -

  27. 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

  28. NAMA-US • Applying community computing concepts

  29. Functions of community computing • 1. Knowing each other • 2. Sharing preference and knowledge over the Internet • 3. Generating consensus for heterogeneous communities • 4. Supporting everyday life by multi-agent technologies • 5. Assisting social events by personal digital assistants

  30. Electronic video conferencing Local area decision net Large Decision room Size of Group Computer conference Decision conferencing Teleconferencing / Broadcasting Small well-known anonymous Multiple Individuals Single group Multiple groups Locus of participants Virtual ad hoc conference with RFID and Mobile devices Based on community computing and need identification technology

  31. Need revelation Identification of current state Intention to expire the gap Identification of goal state Gap between the current and goal states Tension about the gap Buyer coalition formation Service brokering What to get served? Any other services? From whom to buy? Need identification Merchant brokering Under what terms? Service evaluation Negotiation Purchase and delivery How is it going? Credit cards, phone banking, etc.?

  32. Community member 1 Agent Community UUDI for Agent list Need revelation Identification of current state Group formation Intention to expire the gap Service brokering Identification of goal state Any other services? What to get served? From whom to get served? Gap between the current and goal states Tension about the gap Need identification Agent brokering Community member 2 Under what terms? Need revelation Identification of current state Service evaluation Negotiation Intention to expire the gap Identification of goal state Credit cards, phone banking, etc.? Purchase and get served How is it going? Gap between the current and goal states Tension about the gap

  33. Steps Static content (E-Wallet, manual) Contextual content(RFID, E-Wallet) Identification of current state User profile Current location Current time Current activity Identification of goal state Wish list To get served list 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 Content for need Identification

  34. Community Contextually assigned group RFID Tag B C A a b c d D E b c e c f g h f h k t u v RFID reader RFID reader RFID Tag RFID reader RFID reader RFID reader RFID Tag GDSS Task agent RFID data c, k Context-aware group formation Dispatched to GDSS Task agent GDSS Task agent GDSS Task agent NAMA-US c, k k, m f, g, h

  35. GDSS Task Agent • Negotiation • Voting • Knowledge share • Idea generation • Auction / Reverse auction • etc.

  36. 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

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