An automated indoor localization system for online Bluetooth signal strength modeling using visual-inertial SLAM

Tomažič, Simon (author), Škrjanc, Igor (author)

Indoor localization is becoming increasingly important but is not yet widespread because installing the necessary infrastructure is often time-consuming and labor-intensive, which drives up the price. This paper presents an automated indoor localization system that combines all the necessary components to realize low-cost Bluetooth localization with the least data acquisition and network configuration overhead. The proposed system incorporates a sophisticated visual-inertial localization algorithm for a fully automated collection of Bluetooth signal strength data. A suitable collection of measurements can be quickly and easily performed, clearly defining which part of the space is not yet well covered by measurements. The obtained measurements, which can also be collected via the crowdsourcing approach, are used within a constrained nonlinear optimization algorithm. The latter is implemented on a smartphone and allows the online determination of the beacons’ locations and the construction of path loss models, which are validated in real-time using the particle swarm localization algorithm. The proposed system represents an advanced innovation as the application user can quickly find out when there are enough data collected for the expected radiolocation accuracy. In this way, radiolocation becomes much less time-consuming and labor-intensive as the configuration time is reduced by more than half. The experiment results show that the proposed system achieves a good trade-off in terms of network setup complexity and localization accuracy. The developed system for automated data acquisition and online modeling on a smartphone has proved to be very useful, as it can significantly simplify and speed up the installation of the Bluetooth network, especially in wide-area facilities.

• Language: English
• Keywords: indoor localization, visual-inertial SLAM, constrained optimization, path loss model, particle swarm optimization, Bluetooth low energy, beacon
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2021
• Number of pages: 21 str.
• Numbering: Vol. 21, iss. 8, art. 2857
• PID: 20.500.12556/RUL-135337
• UDC: 681.5:004
• ISSN on article: 1424-8220
• DOI: 10.3390/s21082857
• COBISS.SI-ID: 60483331
• Publication date in RUL: 08.03.2022

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

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: 19.04.2021

Secondary language

• Language: Slovenian
• Keywords: lokalizacija v notranjem okolju, vizualnoinercialni SLAM, optimizacija z omejitvami, model izgub na prenosni poti, optimizacija z rojem delcev, Bluetooth z nizko porabo energije, svetilnik