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RFID-Enhanced Boarding Pass System (REBP) An Initial Design By Jason Anderson, Brett Bojduj, Michael Huffman, Arlo White.

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Presentation on theme: "RFID-Enhanced Boarding Pass System (REBP) An Initial Design By Jason Anderson, Brett Bojduj, Michael Huffman, Arlo White."— Presentation transcript:

1 RFID-Enhanced Boarding Pass System (REBP) An Initial Design By Jason Anderson, Brett Bojduj, Michael Huffman, Arlo White

2 Considered Stakeholders 1. Airlines 2. Vendors 3. Security 4. Passengers

3 Technological Assumptions Active RFIDActive RFID Locates boarding pass every 1 secondLocates boarding pass every 1 second –4D coordinates: x, y, z, and timex, y, z, and time –Accuracy within 10 feet Airport security camera coverageAirport security camera coverage Access to passenger manifestingAccess to passenger manifesting

4 4 Airlines Boarding attendantsBoarding attendants –Responsibilities Flight check-inFlight check-in Boarding pass issuanceBoarding pass issuance Flight schedule alterationsFlight schedule alterations Boarding processBoarding process 4

5 5 Airlines InterestsInterests –Maximize efficiency of boarding process Missed/delayed connectionsMissed/delayed connections Customer dissatisfactionCustomer dissatisfaction Operating costsOperating costs System desiresSystem desires –Real-time location of passengers OutcomeOutcome –Assist passengers find gate in timely manner –Delay flights only when passenger in terminal 5

6 6 Vendors InterestsInterests –Finding optimal locations to sell products –Targeted marketing and advertisements 6

7 Vendors To find good locationsTo find good locations 1.Get location data for people as they move through the airport 2.Areas where people stay for a long amount of time can be good places to have a store 3.Use data about different types of areas, e.g., bathrooms, security area, etc., to make a good decision E.g., if people spend lots of time in bathrooms, install vending machines!E.g., if people spend lots of time in bathrooms, install vending machines!

8 Vendors: Targeted Ads LCD screens in key locationsLCD screens in key locations –Targeted ads based on past buying habits –Useful information such as where you are and where your gate is, on a map 7

9 Security TSA and airport security personnelTSA and airport security personnel Responsible for detecting threats and effectively handling themResponsible for detecting threats and effectively handling them

10 Security Interests –Quickly respond to situations –Allow passenger information to be used for suspicious passenger detection

11 Passenger Security Profile

12 Passenger Inconvenience Minimize False Pos without having False Neg Two step investigation process to limit inconvenience System must flag a passenger as suspicious Security Personnel monitors passenger via automated video tracking

13 12 Passengers InterestsInterests – Finding directions within the airport – Knowing the travel issues ahead – Locating lost party members DesiresDesires – Privacy – Security – Comfort & Convenience 12

14 13 Services Demography associationDemography association Location trackingLocation tracking –Real-time –Historical Suspicious passenger detectionSuspicious passenger detection Social networkingSocial networking Purchase recommenderPurchase recommender 13

15 14 Data RFID TagRFID Tag –Unique identifier per tag –Correlated to ticket purchase REBPREBP –Demographic data (name, gender, dob) –Flight history –Airport purchase information –Security data (X-rays, security recordings) 14

16 15 Data Required data interfacesRequired data interfaces –RFID tags and antenna –Passenger manifesting systems –Airport security cameras 15

17 Ethical Concerns PrivacyPrivacy –Stakeholders agreed that no privacy is lost Already have people going through luggageAlready have people going through luggage Already have to go through metal detectorAlready have to go through metal detector

18 17 Analytical Tasks Suspicious passenger detectionSuspicious passenger detection –Association rules and classification Online Analytical ProcessingOnline Analytical Processing –Locations –Demographic data –Purchases Spatio-temporal clusteringSpatio-temporal clustering 17

19 18 Q & A Questions?Questions? 18


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