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Title:An indoor radio mapping dataset combining 3D point clouds and RSSI
Authors:ID Milosheski, Ljupcho, Institut "Jožef Stefan" (Author)
ID Akiyama, Kuon (Author)
ID Bertalanič, Blaž, Institut "Jožef Stefan" (Author)
ID Hribar, Jernej, Institut "Jožef Stefan" (Author)
ID Shinkuma, Ryoichi (Author)
Files:URL URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S2352340926005093
 
.pdf PDF - Presentation file, download (2,10 MB)
MD5: 1A8F90A4DABEA1DC24E0E60CC6442A1B
 
Language:English
Typology:1.03 - Other scientific articles
Organization:Logo IJS - Jožef Stefan Institute
Abstract:The growing number of smart devices supporting bandwidth-intensive and latency-sensitive applications, such as real-time video analytics, smart sensing, Extended Reality (XR), etc., necessitates reliable indoor wireless connectivity. In such environments, accurate Radio Environment Maps (REMs) enable adaptive wireless network planning and optimization of Access Point (AP) placement. However, generating realistic REMs remains difficult due to the variability of indoor environments and the limitations of existing modelling approaches, which often rely on simplified layouts or synthetic data. These challenges are further amplified by the adoption of next-generation Wi-Fi standards, operating at higher frequencies with limited range and wall penetration. To support progress in this area, we collected a dataset that combines high-resolution 3D LiDAR scans with Wi-Fi RSSI measurements across 20 setups in a multi-room indoor environment. It includes two measurement scenarios, one with and one without human presence, enabling development and validation of REM estimation models that incorporate physical geometry and environmental dynamics. The described dataset supports research in data-driven wireless modelling and the development of high-capacity indoor communication networks.
Keywords:indoor radio mapping, LIDAR, RSSI, wireless dataset
Publication status:Published
Publication version:Version of Record
Submitted for review:23.03.2026
Article acceptance date:09.06.2026
Publication date:13.06.2026
Publisher:Elsevier
Year of publishing:2025
Number of pages:str. 1-19
Numbering:Vol. 67, [article no.] 112959
Source:Nizozemska
PID:20.500.12556/DiRROS-30547 New window
UDC:004.7
ISSN on article:2352-3409
DOI:10.1016/j.dib.2026.112959 New window
COBISS.SI-ID:282631171 New window
Copyright:© 2026 The Author(s).
Note:Nasl. z nasl. zaslona; Soavtorji: Kuon Akiyama, Blaž Bertalanič, Jernej Hribar, Ryoichi Shinkuma; Opis vira z dne 23. 6. 2026;
Publication date in DiRROS:29.06.2026
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Record is a part of a journal

Title:Data in brief
Publisher:Elsevier
ISSN:2352-3409
COBISS.SI-ID:32117977 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0016-2019
Name:Komunikacijska omrežja in storitve

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:MN-0009-2025
Name:Timeliness of Information in Smart Grids Networks

Funder:Japan Society for the Promotion of Science
Project number:23H00464

Funder:Japan Society for the Promotion of Science
Project number:25H01124

Funder:Japan Society for the Promotion of Science
Project number:120245002

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:BI-JP/24-26-001-2024
Name:MISA: Inteligentna uporaba LiDAR senzorjev v pametnih mestih

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:11.06.2026
Applies to:VoR

Secondary language

Language:Slovenian
Keywords:notranje radijsko kartiranje, LIDAR, indikator jakosti sprejetega signala, brezžični podatkovni nabor


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