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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Main Authors: | , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2014
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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 |
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. |
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