JUCS - Journal of Universal Computer Science 29(6): 627-646, doi: 10.3897/jucs.96878
OBLEA: A New Methodology to Optimise Bluetooth Low Energy Anchors in Multi-occupancy Location Systems
expand article infoJosé L. López Ruiz‡, Ángeles Verdejo Espinosa‡, Alicia Montoro Lendínez‡, Macarena Espinilla Estévez‡
‡ University of Jaén, Jaén, Spain

Corresponding author: José L. López Ruiz ( llopez@ujaen.es )

© José L. López Ruiz, Ángeles Verdejo Espinosa, Alicia Montoro Lendínez, Macarena Espinilla Estévez.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
Citation: López Ruiz JL, Verdejo Espinosa Á, Montoro Lendínez A, Espinilla Estévez M (2023) OBLEA: A New Methodology to Optimise Bluetooth Low Energy Anchors in Multi-occupancy Location Systems. JUCS - Journal of Universal Computer Science 29(6): 627-646. https://doi.org/10.3897/jucs.96878
Open Access
Abstract
Nowadays, it is becoming increasingly important to understand the multiple configuration factors of BLE anchors in indoor location systems. This task becomes particularly crucial in the context of activity recognition in multi-occupancy smart environments. Knowing the impact of the configuration of BLE anchors in an indoor location system allows us to distinguish the interactions performed by each inhabitant in a smart environment according to their proximity to each sensor. This paper proposes a new methodology, OBLEA, that determines the optimisation of Bluetooth Low Energy (BLE) anchors in indoor location systems, considering multiple BLE variables to increase flexibility and facilitate transferability to other environments. Concretely, we present a model based on a data-driven approach that considers configurations to obtain the best performing configuration with a minimum number of anchors. This methodology includes a flexible framework for the indoor space, the architecture to be deployed, which considers the RSSI value of the BLE anchors, and finally, optimisation and inference for indoor location. As a case study, OBLEA is applied to determine the location of ageing inhabitants in a nursing home in Alcaudete, Jaén (Spain). Results show the extracted knowledge related to the optimisation of BLE anchors involved in the case study.
Keywords
Indoor location system, Bluetooth Low Energy, Fog-Cloud computing, Sustainable development goals