Spatiotemporal Data Cleansing for Indoor RFID Tracking Data

Asif Iqbal Baba, Hua Lu, Xike Xie, Torben Bach Pedersen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The Radio Frequency Identification (RFID) is increasingly being deployed in indoor tracking systems, e.g., airport baggage monitoring. However, the “dirtiness” in raw RFID readings hinder the progress of applying meaningful high level applications that range from monitoring to analysis. Hence, it is indispensable to cleansing RFID data in such systems. In this paper, we focus on two quality aspects in raw indoor RFID data: temporal redundancy and spatial ambiguity. The former refers to the large number of repeated readings for the same object and the same RFID reader during a period of time. The latter refers to the undetermined whereabouts of an object due to multiple readings by different readers simultaneously. We investigate the spatiotemporal characteristics of indoor spaces as well as RFID reader deployment, and exploit them in designing effective data cleansing techniques. Specifically, we aggregate raw RFID readings to reduce temporal redundancy; we design a distance-aware graph to resolve spatial ambiguity with respect to the indoor topology and the RFID reader deployment captured in the graph. We evaluate the spatiotemporal data cleansing techniques using both real and synthetic datasets. The experimental results demonstrate that the proposed techniques are effective and efficient in cleansing indoor RFID tracking data
Original languageEnglish
Title of host publicationIEEE 14th International Conference on Mobile Data Management : Milan, Italy, June 3-6, 2013
Number of pages10
Volume1
PublisherIEEE Computer Society Press
Publication date2013
Pages187-196
ISBN (Print)978-0-7685-4973-6
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event14th IEEE International Conference on Mobile Data Management - Milano, Italy
Duration: 3 Jun 20136 Jun 2013
Conference number: 14

Conference

Conference14th IEEE International Conference on Mobile Data Management
Number14
Country/TerritoryItaly
CityMilano
Period03/06/201306/06/2013

Cite this