IoT enabled Wi-Fi Indoor Positioning System using raster maps

被引：2

作者：

Ali, Muhammad Usman ^{[1
]}

Hur, Soojung ^{[1
]}

Park, Yongwan ^{[1
]}

机构：

[1] Yeungnam Univ, Gyongsan, Gyeongbuk, South Korea

来源：

IPSN '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS | 2019年

关键词：

Indoor localization; Internet of Things; Indoor Positioning System; IPS; Wi-Fi Fingerprinting; Particle Swarm Optimization; PSO;

D O I：

10.1145/3302506.3312612

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In the context of enabling location-based services in complex indoor environments using ubiquitous resources, this study presents a Wi-Fi-based Indoor Positioning System(IPS) which does not require any laborious and time-consuming effort in contrast to Wi-Fi fingerprinting which requires in its offline database calibration phase. The proposed system is an effortless approach in which radio maps are built automatically using online feedback of Wi-Fi enabled the Internet of Things(IoT) sensors. The results show that it is possible to achieve an accuracy of 2 meters by constructing radio maps of Wi-Fi environment using online feedback of IoT sensors in combination with the raster floor plan of the environment.

引用

页码：327 / 328

页数：2

共 6 条

[1] LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning [J].