Evidence map›Paper›PMID 33920249›Full record

ArticleSensors (Basel, Switzerland)2021

Real-Time and Efficient Traffic Information Acquisition via Pavement Vibration IoT Monitoring System.

Zhoujing Ye, Guannan Yan, Ya Wei, Bin Zhou, Ning Li, Shihui Shen, Linbing Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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

7 authors.

Zhoujing YeNational Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China.ORCID 0000-0001-8115-1780
Guannan YanNational Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China.ORCID 0000-0002-8791-7393
Ya WeiDepartment of Civil Engineering, Tsinghua University, Haidian District, Beijing 100084, China.
Bin ZhouYunnan Research Institute of Highway Science and Technology, Panlong District, Kunming 650051, China.
Ning LiYunnan Research Institute of Highway Science and Technology, Panlong District, Kunming 650051, China.
Shihui ShenRail Transportation Engineering, Penn State University, Altoona, PA 16601, USA.ORCID 0000-0002-5718-722X
Linbing WangNational Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China.

Funding

Beijing major science and technology projects Z191100008019002
6 · The paper itself

Abstract

Traditional road-embedded monitoring systems for traffic monitoring have the disadvantages of a short life, high energy consumption and data redundancy, resulting in insufficient durability and high cost. In order to improve the durability and efficiency of the road-embedded monitoring system, a pavement vibration monitoring system is developed based on the Internet of things (IoT). The system includes multi-acceleration sensing nodes, a gateway, and a cloud platform. The key design principles and technologies of each part of the system are proposed, which provides valuable experience for the application of IoT monitoring technology in road infrastructures. Characterized by low power consumption, distributed computing, and high extensibility properties, the pavement vibration IoT monitoring system can realize the monitoring, transmission, and analysis of pavement vibration signal, and acquires the real-time traffic information. This road-embedded system improves the intellectual capacity of road infrastructure and is conducive to the construction of a new generation of smart roads.

Indexed as

internet of thingspavement vibrationreal-time monitoringroad-embedded systemtraffic information

Identifiers

PMID33920249
PMCPMC8069318

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.