Evidence map›Paper›PMID 42197824›Full record

ArticleSensors (Basel, Switzerland)2026

FRESH: An Autonomous IoT Platform for Multi-Parameter Environmental Sensing and Short-Term Forecasting.

Feiling Pan, James A Covington

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

2 authors.

Feiling PanBioSensors Laboratory, School of Engineering, University of Warwick, Library Road, Coventry CV4 7AL, UK.ORCID 0009-0000-4284-4904
James A CovingtonBioSensors Laboratory, School of Engineering, University of Warwick, Library Road, Coventry CV4 7AL, UK.ORCID 0000-0003-1307-6488

Funding

Warwick-Wellcome Translational Partnership Award [WT-219429/Z/19/Z]
6 · The paper itself

Abstract

Environmental monitoring systems are often constrained by high cost, limited portability, restricted pollutant coverage, and dependence on fixed infrastructure, which can limit their suitability for distributed real-time sensing. This study presents FRESH, an autonomous Internet of Things (IoT)-based platform for multi-parameter environmental monitoring and short-term forecasting. The system integrates sensors for air quality, thermal conditions, light, acoustics, and weather, together with GSM-based remote data transmission, onboard data logging, and hybrid battery-solar power management. FRESH was deployed across multiple indoor and outdoor locations in Coventry and at the University of Warwick, UK, and operated over a 10-month period to assess practical performance under varied environmental conditions. In addition to continuous environmental sensing, machine learning models were developed to predict short-term changes in selected environmental variables. Across the tested models, the best predictive performance was obtained for several key parameters, including particulate matter (R

Indexed as

air qualityenvironmental monitoringIoTmachine learningmulti-parameter sensingshort-term forecasting

Identifiers

PMID42197824
PMCPMC13210863

What Socratic 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 Socratic graph.