Evidence map›Paper›PMID 30744141›Full record

ArticleSensors (Basel, Switzerland)2019

Fast Radio Map Construction by using Adaptive Path Loss Model Interpolation in Large-Scale Building.

Jingxue Bi, Yunjia Wang, Zengke Li, Shenglei Xu, Jiapeng Zhou, Meng Sun, Minghao Si

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
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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

7 authors.

Jingxue BiNASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China. bjx1050@163.com.ORCID 0000-0002-2964-7698
Yunjia WangNASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China. wyjc411@163.com.ORCID 0000-0002-1903-242X
Zengke LiSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China. zengkeli@yeah.net.
Shenglei XuSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China. tb17160013b2@cumt.edu.cn.
Jiapeng ZhouSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China. ts16160038a3@cumt.edu.cn.
Meng SunSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China. tb18160007b1@cumt.edu.cn.
Minghao SiSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China. 13218021689@163.com.

Funding

Outstanding Innovation Scholarship for Doctoral Candidate of "Double First Rate" Construction Disciplines of CUMT 0
6 · The paper itself

Abstract

The radio map construction is usually time-consuming and labor-sensitive in indoor fingerprinting localization. We propose a fast construction method by using an adaptive path loss model interpolation. Received signal strength (RSS) fingerprints are collected at sparse reference points by using multiple smartphones based on crowdsourcing. Then, the path loss model of an access point (AP) can be built with several reference points by the least squares method in a small area. Afterwards, the RSS value can be calculated based on the constructed model and corresponding AP's location. In the small area, all models of detectable APs can be built. The corresponding RSS values can be estimated at each interpolated point for forming the interpolated fingerprints considering RSS loss, RSS noise and RSS threshold. Through combining all interpolated and sparse reference fingerprints, the radio map of the whole area can be obtained. Experiments are conducted in corridors with a length of 211 m. To evaluate the performance of RSS estimation and positioning accuracy, inverse distance weighted and Kriging interpolation methods are introduced for comparing with the proposed method. Experimental results show that our proposed method can achieve the same positioning accuracy as complete manual radio map even with the interval of 9.6 m, reducing 85% efforts and time of construction.

Indexed as

fingerprintingindoor positioningleast squarespath loss modelradio map

Identifiers

PMID30744141
PMCPMC6387199

What OpenQuestion holds

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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.