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Sensors 2015, 15(7), 17274-17299; doi:10.3390/s150717274

VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls

1
School of Computing, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong, Daejeon 305-338, Korea
2
School of Computer Science and Engineering, Korea University of Technology and Education (KOREATECH), 1600 Chungjeol-ro, Cheonan, Chungcheong 330-708, Korea
3
Department of Computer and Communications Engineering, Kangwon National University (KNU), 1 Kangwondaehak-gil, Chuncheon, Gangwon 200-701, Korea
Dr. Byoungjip Kim is now with Samsung Electronics.
*
Author to whom correspondence should be addressed.
Academic Editors: Kourosh Khoshelham and Sisi Zlatanova
Received: 6 May 2015 / Revised: 20 June 2015 / Accepted: 9 July 2015 / Published: 16 July 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
View Full-Text   |   Download PDF [2026 KB, uploaded 16 July 2015]   |  

Abstract

In this paper, we introduce a novel smartphone framework called VisitSense that automatically detects and predicts a smartphone user’s place visits from ambient radio to enable behavioral targeting for mobile ads in large shopping malls. VisitSense enables mobile app developers to adopt visit-pattern-aware mobile advertising for shopping mall visitors in their apps. It also benefits mobile users by allowing them to receive highly relevant mobile ads that are aware of their place visit patterns in shopping malls. To achieve the goal, VisitSense employs accurate visit detection and prediction methods. For accurate visit detection, we develop a change-based detection method to take into consideration the stability change of ambient radio and the mobility change of users. It performs well in large shopping malls where ambient radio is quite noisy and causes existing algorithms to easily fail. In addition, we proposed a causality-based visit prediction model to capture the causality in the sequential visit patterns for effective prediction. We have developed a VisitSense prototype system, and a visit-pattern-aware mobile advertising application that is based on it. Furthermore, we deploy the system in the COEX Mall, one of the largest shopping malls in Korea, and conduct diverse experiments to show the effectiveness of VisitSense. View Full-Text
Keywords: smartphone sensing; visit detection; place recognition; visit prediction; mobile advertising smartphone sensing; visit detection; place recognition; visit prediction; mobile advertising
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kim, B.; Kang, S.; Ha, J.-Y.; Song, J. VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls. Sensors 2015, 15, 17274-17299.

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