Evidence map›Paper›PMID 41157374›Full record

ReviewSensors (Basel, Switzerland)2025

Intelligent Gas Sensors: From Mechanism to Applications.

Jianghong Wei, Qing Peng, Yuee Xie, Yuanping Chen

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. 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. Review
  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

4 authors.

Jianghong WeiSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang 212013, China.
Qing PengSchool of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China.ORCID 0000-0002-8281-8636
Yuee XieSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0009-0007-3729-6641
Yuanping ChenSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang 212013, China.

Funding

National Natural Science Foundation of China 12174157, 12074150, 12272378
6 · The paper itself

Abstract

Intelligent gas sensors are indispensable devices widely used in modern society for environmental monitoring, healthcare, the food industry, and public safety. Recent advancements in wireless communication, cloud storage, computing technologies, and artificial intelligence algorithms have significantly enhanced the intelligence level and performance requirements of these sensors. Particularly in the Internet of Things (IoT) environment, flexible and wearable gas sensors are playing an increasingly important role due to their convenience and real-time monitoring capabilities. This review systematically summarizes the latest progress in intelligent gas sensors, covering conceptual frameworks, working principles, and applications across various fields, as well as the construction of IoT networks using sensor arrays. It provides a comprehensive assessment of recent advancements in intelligent gas sensing technologies, highlighting innovations in device architecture, functional mechanisms, and performance in diverse application environments. Special emphasis is placed on transformative developments in flexible and wearable sensor platforms and the enhanced intelligence achieved through the integration of advanced computational algorithms and machine learning techniques. Finally, a summary and future prospects are presented. Despite significant progress, intelligent gas sensors still face challenges related to sensing accuracy, stability, and cost in future applications.

Indexed as

flexible sensorsgas sensing technologyintelligent gas sensorsIoT sensor networksmachine learning

Identifiers

PMID41157374
PMCPMC12567656

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.