Evidence map›Paper›PMID 37177383›Full record

ArticleSensors (Basel, Switzerland)2023

A Hybrid Indoor Altimetry Based on Barometer and UWB.

Minghao Si, Yunjia Wang, Ning Zhou, Cheekiat Seow, Harun Siljak

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Minghao SiKey Laboratory for Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China.ORCID 0000-0001-6581-4708
Yunjia WangKey Laboratory for Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China.ORCID 0000-0002-1903-242X
Ning ZhouChinese Academy of Surveying and Mapping, Beijing 100036, China.
Cheekiat SeowSchool of Computing Science, University of Glasgow, Glasgow G12 8RZ, UK.
Harun SiljakSchool of Engineering, Trinity College Dublin, The University of Dublin, D02 PN40 Dublin, Ireland.ORCID 0000-0003-1371-2683

Funding

China Scholarship Council 202106420051National Key Research and DevelopmentProgram of China 2016YFB0502102National Key Research and DevelopmentProgram of China 2022YFE0102600
6 · The paper itself

Abstract

Accurate altimetry is essential for location-based services in commercial and industrial applications. However, current altimetry methods only provide low-accuracy measurements, particularly in multistorey buildings with irregular structures, such as hollow areas found in various industrial and commercial sites. This paper innovatively proposes a tightly coupled indoor altimetry system that utilizes floor identification to improve height measurement accuracy. The system includes two optimized algorithms that improve floor identification accuracy through activity detection and address the problem of difficult convergence of

Indexed as

altimetrybarometerindoor positioningUWB

Identifiers

PMID37177383
PMCPMC10180845

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.