Evidence map›Paper›PMID 39628585›Full record

ReviewiScience2024

Sustainable and smart rail transit based on advanced self-powered sensing technology.

Hongjie Tang, Lingji Kong, Zheng Fang, Zutao Zhang, Jianhong Zhou, Hongyu Chen, Jiantong Sun, Xiaolong Zou

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

8 authors.

Hongjie TangSchool of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Lingji KongSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Zheng FangSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Zutao ZhangChengdu Technological University, Chengdu 611730, P.R. China.
Jianhong ZhouSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Hongyu ChenSchool of Design, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Jiantong SunSchool of Design, Southwest Jiaotong University, Chengdu 610031, P.R. China.
Xiaolong ZouSchool of Design, Southwest Jiaotong University, Chengdu 610031, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As rail transit continues to develop, expanding railway networks increase the demand for sustainable energy supply and intelligent infrastructure management. In recent years, advanced rail self-powered technology has rapidly progressed toward artificial intelligence and the internet of things (AIoT). This review primarily discusses the self-powered and self-sensing systems in rail transit, analyzing their current characteristics and innovative potentials in different scenarios. Based on this analysis, we further explore an IoT framework supported by sustainable self-powered sensing systems including device nodes, network communication, and platform deployment. Additionally, technologies about cloud computing and edge computing deployed in railway IoT enable more effective utilization. The deployed intelligent algorithms such as machine learning (ML) and deep learning (DL) can provide comprehensive monitoring, management, and maintenance in railway environments. Furthermore, this study explores research in other cross-disciplinary fields to investigate the potential of emerging technologies and analyze the trends for future development in rail transit.

Indexed as

Artificial intelligenceEnergy systemsEngineeringMechanical engineering

Identifiers

PMID39628585
PMCPMC11612783

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.