Sensor-free corner shape detection by wireless networks

Due to the rapid growth of the smartphone applications and the fast development of the Wireless Local Area Networks (WLANs), numerous indoor location-based techniques have been proposed during the past several decades. Floorplan, which defines the structure and functionality of a specific indoor env...

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Bibliographic Details
Main Authors: WANG, Yuxi, ZHOU, Zimu, WU, Kaishun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/4754
https://ink.library.smu.edu.sg/context/sis_research/article/5757/viewcontent/icpads14_wang.pdf
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Institution: Singapore Management University
Language: English
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Summary:Due to the rapid growth of the smartphone applications and the fast development of the Wireless Local Area Networks (WLANs), numerous indoor location-based techniques have been proposed during the past several decades. Floorplan, which defines the structure and functionality of a specific indoor environment, becomes a hot topic nowadays. Conventional floorplan techniques leverage smartphone sensors combined with WiFi signals to construct the floorplan of a building. However, existing approaches with sensors cannot detect the shape of a corner, and the sensors cost huge amount of energy during the whole floorplan constructing process. In this paper, we propose a sensor-free approach to detect the shape of a certain corner leveraging WiFi signals without using sensors on smartphones. Instead of utilizing traditional wireless communication indicator Received Signal Strength (RSS), we leverage a finer-grained indicator Channel State Information (CSI) to detect the shape of a certain corner. The evaluation of our approach shows that CSI is more robust in sensor-free corner shape detection, and we have achieved over 85% detection accuracy in simulation and over 70% detection accuracy in real indoor experiments.