Abstract

Indoor localization technologies based on Radio Signal Strength (RSS) attract many researchers’ attentions, since RSS can be easily obtained by wireless devices without additional hardware. However, such technologies are apt to be affected by indoor environments and multipath phenomenon. Thus, the accuracy is very difficult to improve. In this paper, we put forward a method, which is able to leverage various other resources in localization. Besides the traditional RSS information, the environmental physical features, e.g., the light, temperature, and humidity information, are all utilized for localization. After building a comprehensive fingerprint map for the above information, we propose an algorithm to localize the target based on Naïve Bayesian. Experimental results show that the successful positioning accuracy can dramatically outperform traditional pure RSS‐based indoor localization method by about 39%. Our method has the potential to improve all the radio frequency (RF) based localization approaches.

Highlights

  • It is widely accepted that indoor localization is essential to many service applications and attracts many researchers’ attentions [1,2,3,4,5,6]

  • Among various indoor localization technologies [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22], the technologies based on the Radio Signal Strength (RSS) are popular, since RSS can be obtained by common wireless devices without additional hardware

  • With the help of temperature information, the localization accuracy can be improved by about 10% for both day and night environments

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Summary

Introduction

It is widely accepted that indoor localization is essential to many service applications and attracts many researchers’ attentions [1,2,3,4,5,6]. The patients can be found and taken care if indoor localization technologies are applied. Among various indoor localization technologies [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22], the technologies based on the Radio Signal Strength (RSS) are popular, since RSS can be obtained by common wireless devices (e.g., wireless sensors, mobile phone) without additional hardware. Signal emitted from one transmitter will arrive at the receiver from many different propagation paths. Many improvement works have been proposed, the localization accuracy based on such technologies is very difficult to improve

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