Evidence map›Paper›PMID 38443474›Full record

ArticleScientific reports2024

Research on WSN reliable ranging and positioning algorithm for forest environment.

Peng Wu, Le Yu, Xiaomei Yi, Liang Xu, LiJuan Liu, YuTong Yi, Tengteng Jiang, Chunling Tao

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Peng Wu *College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.
Le Yu *College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.
Xiaomei YiCollege of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China. yxm@zafu.edu.cn.
Liang XuCollege of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.
LiJuan LiuCollege of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.
YuTong YiCollege of Humanities and Development Studies, China Agricultural University, Beijing, 100091, People's Republic of China.
Tengteng JiangCollege of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.
Chunling TaoCollege of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, 311300, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments.

Indexed as

Fitting methodHigh precisionRanging positioningRegional divisionWireless sensor network (WSN)

Identifiers

PMID38443474
PMCPMC10914735

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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.