Evidence map›Paper›PMID 35009652›Full record

ReviewSensors (Basel, Switzerland)2021

Cloud Platforms for Context-Adaptive Positioning and Localisation in GNSS-Denied Scenarios-A Systematic Review.

Darwin Quezada-Gaibor, Joaquín Torres-Sospedra, Jari Nurmi, Yevgeni Koucheryavy, Joaquín Huerta

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Darwin Quezada-GaiborInstitute of New Imaging Technologies, Universitat Jaume I, 12071 Castellon, Spain.ORCID 0000-0002-8064-9955
Joaquín Torres-SospedraALGORITMI Research Center, Universidade do Minho, 4800-058 Guimaraes, Portugal.ORCID 0000-0003-4338-4334
Jari NurmiElectrical Engineering Unit, Tampere University, 33720 Tampere, Finland.ORCID 0000-0003-2169-4606
Yevgeni KoucheryavyElectrical Engineering Unit, Tampere University, 33720 Tampere, Finland.
Joaquín HuertaInstitute of New Imaging Technologies, Universitat Jaume I, 12071 Castellon, Spain.

Funding

H2020 Marie Skłodowska-Curie Actions 101023072H2020 Marie Skłodowska-Curie Actions 813278Ministerio de Ciencia, Innovación y Universidades PTQ2018-009981
6 · The paper itself

Abstract

Cloud Computing and Cloud Platforms have become an essential resource for businesses, due to their advanced capabilities, performance, and functionalities. Data redundancy, scalability, and security, are among the key features offered by cloud platforms. Location-Based Services (LBS) often exploit cloud platforms to host positioning and localisation systems. This paper introduces a systematic review of current positioning platforms for GNSS-denied scenarios. We have undertaken a comprehensive analysis of each component of the positioning and localisation systems, including techniques, protocols, standards, and cloud services used in the state-of-the-art deployments. Furthermore, this paper identifies the limitations of existing solutions, outlining shortcomings in areas that are rarely subjected to scrutiny in existing reviews of indoor positioning, such as computing paradigms, privacy, and fault tolerance. We then examine contributions in the areas of efficient computation, interoperability, positioning, and localisation. Finally, we provide a brief discussion concerning the challenges for cloud platforms based on GNSS-denied scenarios.

Indexed as

cloud platformGNSS-denied scenarioslocalisationpositioningsystematic review

Identifiers

PMID35009652
PMCPMC8747096

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.