Evidence map›Paper›PMID 40735132›Full record

ArticleDigital twins and applications

Indoor Localization Using Multi-Bluetooth Beacon Deployment in a Sparse Edge Computing Environment.

Soheil Saghafi, Yashar Kiarashi, Amy D Rodriguez, Allan I Levey, Hyeokhyen Kwon, Gari D Clifford

Abstract read
In one paragraph

Article in Digital twins and applications. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Soheil SaghafiDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, Georgia, USA.ORCID https://orcid.org/0000-0002-3676-5027
Yashar KiarashiDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, Georgia, USA.
Amy D RodriguezDepartment of Neurology, School of Medicine, Emory University, Atlanta, Georgia, USA.
Allan I LeveyDepartment of Neurology, School of Medicine, Emory University, Atlanta, Georgia, USA.
Hyeokhyen KwonDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, Georgia, USA.
Gari D CliffordDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, Georgia, USA.

Funding

Artificial Intelligence Applied to Video and Speech for Objectively Evaluating Social Interaction and Depression in Mild Cognitive ImpairmentR21DC021029 · NIDCD · EMORY UNIVERSITY · PI CLIFFORD, GARI DAVID, KWON, HYEOKHYEN · 2023 to 2023
$430k
NIDCD NIH HHS R21 DC021029
6 · The paper itself

Abstract

Bluetooth low energy (BLE)-based indoor localization has been extensively researched due to its cost-effectiveness, low power consumption, and ubiquity. Despite these advantages, the variability of received signal strength indicator (RSSI) measurements, influenced by physical obstacles, human presence, and electronic interference, poses a significant challenge to accurate localization. In this work, we present an optimised method to enhance indoor localization accuracy by utilising multiple BLE beacons in a radio frequency (RF)-dense modern building environment. Through a proof-of-concept study, we demonstrate that using three BLE beacons reduces localization error from a worst-case distance of 9.09-2.94 m, whereas additional beacons offer minimal incremental benefit in such settings. Furthermore, our framework for BLE-based localization, implemented on an edge network of Raspberry Pies, has been released under an open-source license, enabling broader application and further research.

Indexed as

ambient health monitoringbluetooth low energycloud computingedge computingindoor localization

Identifiers

PMID40735132
PMCPMC12305822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.