Exploring Fast Fingerprint Construction Algorithm for Unmodulated Visible Light Indoor Localization.

Chenqi Shi, Xinyv Niu, Tao Li, Sen Li, Chanjuan Huang, Qiang Niu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chenqi ShiSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.ORCID 0000-0001-5589-1582

Xinyv NiuSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Tao LiSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Sen LiSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Chanjuan HuangSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Qiang NiuSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Funding

National Natural Science Foundation of China 51674255

6 · The paper itself

Abstract

The study of visible light indoor position has received considerable attention. The visible light indoor position has problems such as deployment difficulty and high cost. In our system, we propose a new fingerprint construction algorithm to simplify visible light indoor position. This method can realize the rapid construction of a visible fingerprint database and prove that the fingerprint database can be used repeatedly in different environments. We proved the theoretical feasibility of this method through theoretical derivation. We carried out extensive experiments in two classic real indoor environments. Experimental results show that reverse fingerprinting can be achieved. In 95% of cases, the positioning accuracy can be guaranteed to be less than 10 cm.

Indexed as

fingerprint locationimage processvisible light indoor position

Identifiers

PMID33348777

DOI10.3390/s20247245

PMCPMC7766118

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.