Affiliation:
1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150000, China
Abstract
Unlike outdoor trajectory prediction that has been studied many years, predicting the movement of a large number of users in indoor space like shopping mall has just been a hot and challenging issue due to the ubiquitous emerging of mobile devices and free Wi-Fi services in shopping centers in recent years. Aimed at solving the indoor trajectory prediction problem, in this paper, a hybrid method based on Hidden Markov approach is proposed. The proposed approach clusters Wi-Fi access points according to their similarities first; then, a frequent subtrajectory based HMM which captures the moving patterns of users has been investigated. In addition, we assume that a customer’s visiting history has certain patterns; thus, we integrate trajectory prediction with shop category prediction into a unified framework which further improves the predicting ability. Comprehensive performance evaluation using a large-scale real dataset collected between September 2012 and October 2013 from over 120,000 anonymized, opt-in consumers in a large shopping center in Sydney was conducted; the experimental results show that the proposed method outperforms the traditional HMM and perform well enough to be usable in practice.
Funder
Heilongjiang Postdoctoral Science Foundation
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Reference27 articles.
1. Indoor next location prediction with Wi-Fi;B.-K. Ang
2. Trajectory prediction in campus based on Markov chains;B. Wang,2016
3. Activity patterns of californians: use of and proximity to indoor pollutant sources;P. L. Jenkins,1992
4. The national human activity pattern survey (nhaps): a resource for assessing exposure to environmental pollutants;N. E. Klepeis;Journal of Exposure Science and Environmental Epidemiology,2001
5. Tesco provides free Wi-Fi in larger UK & Ireland stores;S. Shearman,2014
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献