WIP: Daily Life Oriented Indoor Localization by Fusion of Smartphone Sensors and Wi-Fi

被引:0
作者
Nurdag, Ayse Vildan [1 ]
Arnrich, Bert [1 ]
Yurdakul, Arda [1 ]
机构
[1] Bogazici Univ, Comp Engn Dept, TR-34342 Istanbul, Turkey
来源
2018 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP 2018) | 2018年
关键词
indoor localization; smartphone sensors; magnetic field; Wi-Fi; ID3; decision tree; classification;
D O I
10.1109/SMARTCOMP.2018.00050
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Smartphones are the best personal assistants in our lives on several counts. However, their services can still be improved for a better quality of life. In this paper, we aim to determine the exact location of a smartphone in a room, i.e, on a study desk, a television table, etc. By this way, our daily settings may be automatically activated from the smartphone itself. For example, if a user puts his/her phone on the bed commode, then the phone would be able to switch itself to the night mode on its own. A successful localization in a room should be able to distinguish different corners from each other so that it can be used in various applications as a supported technology. Hence, in this work, we are proposing an indoor localization system that can distinguish different indoor places by using the smartphones' sensors and Wi-Fi services. Unlike the common location-based services, our solution is not a server-client based system. In order to enhance feasibility and availability, we only use the mobile device but no additional infrastructure. We developed two applications on Android platform. The first one allows the user to easily collect sensor data from his/her living places, such as home and office settings. The second one is a data mining application sourced by Weka. The tests were performed in different rooms of a house and office environment. We achieved 86% accuracy for room level localization.
引用
收藏
页码:258 / 260
页数:3
相关论文
共 2 条
[1]  
Basri C, 2016, INT CONF MULTIMED, P253, DOI 10.1109/ICMCS.2016.7905633
[2]  
Hu ZZ, 2017, IEEE IMAGE PROC, P4402, DOI 10.1109/ICIP.2017.8297114