Evidence map›Paper›PMID 37299794›Full record

ArticleSensors (Basel, Switzerland)2023

A Hybrid Scheme for Disaster-Monitoring Applications in Wireless Sensor Networks.

Danqi Chen, Yanxia Zhang, Guoli Pang, Fangping Gao, Li Duan

Open access · goldAbstract 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

1 citing paper in PubMed, 17 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Danqi ChenSchool of Information Engineering, Institute of Disaster Prevention, Sanhe 065201, China.ORCID 0000-0002-6226-6838
Yanxia ZhangSchool of Information Engineering, Institute of Disaster Prevention, Sanhe 065201, China.
Guoli PangSchool of Information Engineering, Institute of Disaster Prevention, Sanhe 065201, China.
Fangping GaoSchool of Information Engineering, Institute of Disaster Prevention, Sanhe 065201, China.
Li DuanCollege of Electronic Science and Control Engineering, Institute of Disaster Prevention, Sanhe 065201, China.
Institute of Disaster Prevention · CN

Funding

Langfang Science and Technology Research Self-Funded Project 2022011004Langfang Science and Technology Research Self-Funded Project 2022011033Special Fund of Fundamental Scientific Research Business Expense for Higher School of Central Government (Projects for creation teams) ZY20215106
6 · The paper itself

Abstract

Disaster monitoring is a primary task for wireless sensor networks. Systems for the rapid reporting of earthquake information are a crucial aspect of disaster monitoring. Furthermore, during emergency rescue after a large earthquake, wireless sensor networks can provide pictures and sound information to save lives. Therefore, when accompanied by multimedia data flow, the alert and seismic data sent by the seismic monitoring nodes must be sufficiently fast. We present herein the architecture of a collaborative disaster-monitoring system that can obtain seismic data in a highly energy-efficient manner. In this paper, a hybrid superior node token ring MAC scheme is proposed for disaster monitoring in wireless sensor networks. This scheme consists of set-up and steady-state stages. A clustering approach was proposed for heterogeneous networks during the set-up stage. The proposed MAC operates in the duty cycle mode at the steady-state stage and is based on the virtual token ring of ordinary nodes, the polling all the superior nodes in one period, and alert transmissions with a low-power listening and shortened preamble approach during the sleep state. The proposed scheme can simultaneously satisfy the requirements of three types of data in disaster-monitoring applications. Based on embedded Markov chains, a model of the proposed MAC was developed and the mean queue length, mean cycle time, and mean upper bound of the frame delay were obtained. Using simulations under various conditions, the clustering approach performed better than the pLEACH approach, and the theoretical results of the proposed MAC were verified. We found that alerts and superior data have outstanding delay and throughput performances even under heavy traffic intensity, and the proposed MAC can provide a data rate of several hundred kb/s for superior and ordinary data. Considering all three types of data, the frame delay performances of the proposed MAC are better than those of the WirelessHART and DRX schemes, and the alert data of the proposed MAC have a maximum frame delay of 15 ms. These satisfy the application requirements of disaster monitoring.

Indexed as

DisastersEarthquakesComputer Communication NetworksMonitoring, PhysiologicWireless Technologydisaster-monitoring applicationsframe delayhybrid schemelifetimethroughputwireless sensor networks

Identifiers

PMID37299794
PMCPMC10255642
OpenAlexW4378379471

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.