A Data Warehouse Solution for Analyzing RFID-Based Baggage Tracking Data

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Abstract

Today, airport baggage handling is far from perfect. Baggage goes on the wrong flights, is left behind, or gets lost, which costs a lot of money for the airlines, as well as frustration for the passengers. To remedy the situation, we
present a data warehouse (DW) solution for storing and analyzing spatio-temporal Radio Frequency Identification (RFID) baggage tracking data. Analysis of this data can yield interesting results on baggage flow, the causes of baggage mishandling, and the parties responsible for the mishandling(airline, airport, handler,...), which can ultimately lead to improved baggage handling quality. The paper presents a carefully designed data warehouse (DW), with
a relational schema sitting underneath a multidimensional data cube, that can handle the many complexities in the data. The paper also discusses the Extract-Transform-Load (ETL) flow that loads the data warehouse with the appropriate tracking data from the data sources. The presented concepts are generalizable
to other types of multi-site indoor tracking systems based on Bluetooth and RFID. The system has been tested with large amount of real-world RFID-based baggage tracking data from a major industry initiative. The developed solution is shown to both reveal interesting insights as well as being several orders of
magnitude faster than computing the results directly on the data sources.
Original languageEnglish
Title of host publicationIEEE 14th International Conference on Mobile Data Management
Number of pages10
Volume1
PublisherIEEE Computer Society Press
Publication dateJun 2013
Pages283-292
ISBN (Print)978-1-4673-6068-5
ISBN (Electronic)978-0-7695-4973-6
DOIs
Publication statusPublished - Jun 2013
Eventthe 14th IEEE International Conference on Mobile Data Management - Milan, Italy
Duration: 3 Jun 20136 Jun 2013
Conference number: 14

Conference

Conferencethe 14th IEEE International Conference on Mobile Data Management
Number14
Country/TerritoryItaly
CityMilan
Period03/06/201306/06/2013

Keywords

  • RFID; data warehouse; data cube; data analysis; baggage tracking; moving objects; indoor tracking;

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