Robot-assisted RSSI data collection for indoor fingerprint-based positioning

Houjin Lu; Seung Hoon Hwang

doi:10.1016/j.icte.2025.11.001

Robot-assisted RSSI data collection for indoor fingerprint-based positioning

Houjin Lu
, Seung Hoon Hwang

Department of Electronics & Electrical Engineering

Dongguk University

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Indoor positioning has diverse applications in public safety, industry, and healthcare [ 1 ]. This paper presents a robot-assisted data collection method to overcome the inefficiencies of conventional smartphone-based approaches in indoor positioning. By integrating advanced hardware and software optimizations, the robot achieves efficient and comprehensive Wi-Fi RSSI (Received Signal Strength Indicator) data acquisition at reference points (RPs). Experimental results demonstrate that the robot-assisted system achieves a positioning accuracy of 91.92 %, improving accuracy by 1.8 % compared to the smartphone-based method [ 2 ], while reducing data collection time by 59 %. The results validate the proposed method’s efficiency, systematization, and effectiveness in improving indoor positioning.

Original language	English
Pages (from-to)	249-254
Number of pages	6
Journal	ICT Express
Volume	12
Issue number	1
DOIs	https://doi.org/10.1016/j.icte.2025.11.001
State	Published - Feb 2026

Keywords

Data Collection
Indoor fingerprint positioning (IPS)
RSSI
Robot
Wi-Fi

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10.1016/j.icte.2025.11.001

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title = "Robot-assisted RSSI data collection for indoor fingerprint-based positioning",

abstract = "Indoor positioning has diverse applications in public safety, industry, and healthcare [ 1 ]. This paper presents a robot-assisted data collection method to overcome the inefficiencies of conventional smartphone-based approaches in indoor positioning. By integrating advanced hardware and software optimizations, the robot achieves efficient and comprehensive Wi-Fi RSSI (Received Signal Strength Indicator) data acquisition at reference points (RPs). Experimental results demonstrate that the robot-assisted system achieves a positioning accuracy of 91.92 \%, improving accuracy by 1.8 \% compared to the smartphone-based method [ 2 ], while reducing data collection time by 59 \%. The results validate the proposed method{\textquoteright}s efficiency, systematization, and effectiveness in improving indoor positioning.",

keywords = "Data Collection, Indoor fingerprint positioning (IPS), RSSI, Robot, Wi-Fi",

author = "Houjin Lu and Hwang, \{Seung Hoon\}",

note = "Publisher Copyright: {\textcopyright} 2025 The Authors.",

year = "2026",

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doi = "10.1016/j.icte.2025.11.001",

language = "English",

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T1 - Robot-assisted RSSI data collection for indoor fingerprint-based positioning

AU - Lu, Houjin

AU - Hwang, Seung Hoon

PY - 2026/2

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N2 - Indoor positioning has diverse applications in public safety, industry, and healthcare [ 1 ]. This paper presents a robot-assisted data collection method to overcome the inefficiencies of conventional smartphone-based approaches in indoor positioning. By integrating advanced hardware and software optimizations, the robot achieves efficient and comprehensive Wi-Fi RSSI (Received Signal Strength Indicator) data acquisition at reference points (RPs). Experimental results demonstrate that the robot-assisted system achieves a positioning accuracy of 91.92 %, improving accuracy by 1.8 % compared to the smartphone-based method [ 2 ], while reducing data collection time by 59 %. The results validate the proposed method’s efficiency, systematization, and effectiveness in improving indoor positioning.

AB - Indoor positioning has diverse applications in public safety, industry, and healthcare [ 1 ]. This paper presents a robot-assisted data collection method to overcome the inefficiencies of conventional smartphone-based approaches in indoor positioning. By integrating advanced hardware and software optimizations, the robot achieves efficient and comprehensive Wi-Fi RSSI (Received Signal Strength Indicator) data acquisition at reference points (RPs). Experimental results demonstrate that the robot-assisted system achieves a positioning accuracy of 91.92 %, improving accuracy by 1.8 % compared to the smartphone-based method [ 2 ], while reducing data collection time by 59 %. The results validate the proposed method’s efficiency, systematization, and effectiveness in improving indoor positioning.

KW - Data Collection

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KW - Robot

KW - Wi-Fi

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DO - 10.1016/j.icte.2025.11.001

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JO - ICT Express

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Robot-assisted RSSI data collection for indoor fingerprint-based positioning

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Keywords

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