Paper Info
Title
A New Approach for Wi-Fi-Based People Localization in a Long Narrow Space
Abstract
Wi-Fi-based positioning technology has been recognized as an effective technology for indoor positioning along with the rapid development and application of smartphones. One of its typical applications is localizing people in large public areas such as shopping malls, schools, and airports. A common and critical task from such applications is localizing people in long narrow spaces such as a long corridor which is considered as the most frequent place where people activities take place. Generally, the geographical distribution of Wi-Fi access points (APs) in long spaces is poor for localizing people since normally less than 3 APs are connected to a smartphone. In addition, all these APs are normally mounted along a straight line; hence, it is difficult to track people using traditional positioning algorithms such as trilateration and fingerprinting. To address this issue, a new approach called same-line-dual-connection (SLDC) was developed to estimate user locations with a good positioning accuracy, particularly for long narrow spaces where only limited Wi-Fi connections are available. The SLDC approach integrates geometry principle with positioning theories and machine learning ideas. The test outcome has shown that the SLDC approach produced a promising result, and a mean positioning accuracy of 1.60 m was achieved.
Year
DOI
Venue
2019
10.1155/2019/9581401
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Field
DocType
Volume
Line (geometry),Computer science,Real-time computing,Positioning technology,Distributed computing,Trilateration
Journal
2019
ISSN
Citations 
PageRank 
1530-8669
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Longshi Gao100.34
Shuangxia Tang200.34
Yuntian Brian Bai3142.96