Evidence map›Paper›PMID 42515373›Full record

ArticleSensors (Basel, Switzerland)2026

A Vehicular IoT-Based Methane Sensing System for Large-Scale Urban Environmental Monitoring.

Nuncio Perrella, Fuad Kassab, Angelo Zanini

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Nuncio PerrellaPolytechnic School, University of Sao Paulo, Sao Paulo 05508-010, Brazil.ORCID 0009-0007-0747-1648
Fuad KassabPolytechnic School, University of Sao Paulo, Sao Paulo 05508-010, Brazil.ORCID 0000-0001-5142-9964
Angelo ZaniniMaua Institute of Technology, Sao Caetano do Sul 09580-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents the design, development, and large-scale deployment of a vehicular IoT-based methane sensing system for urban environmental monitoring. The proposed solution integrates a low-cost metal oxide semiconductor (MOS) methane sensor with a dual chamber gas sampling mechanism, embedded processing, and wireless communication via 4G/5G networks using a smartphone as a gateway. Methane concentration data are collected from sensors installed in moving vehicles, georeferenced in real time using GNSS, and transmitted to a cloud-based platform for storage and analysis. Field experiments were conducted in the metropolitan region of São Paulo, Brazil, using 16 instrumented vehicles over a 20-month period, covering approximately 192,274 km and generating more than 48 million measurements. The results reveal spatially consistent methane concentration patterns and identify urban areas with elevated levels exceeding global background concentrations. A comparative analysis with a commercial infrared-based mobile methane monitoring system showed consistent agreement in the identification of spatial methane concentration patterns and potential emission hotspots. These results demonstrate the effectiveness of the proposed system for scalable urban methane monitoring.

Indexed as

air pollutiongreenhouse gasesInternet of Things (IoT)methane sensormobile sensor networkssmart citiesurban environmental monitoringvehicular sensing

Identifiers

PMID42515373
PMCPMC13417624

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.