Evidence map›Paper›PMID 36711304›Full record

ArticleHeliyon2023

Iot application for energy poverty detection based on thermal comfort monitoring.

Ascensión López-Vargas, Agapito Ledezma-Espino

Erratum issuedAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Ascensión López-VargasControl Learning and Optimization Group, Computer Science and Engineering Department, University Carlos III of Madrid. Leganes, Madrid, Spain.
Agapito Ledezma-EspinoControl Learning and Optimization Group, Computer Science and Engineering Department, University Carlos III of Madrid. Leganes, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of a datalogger for identifying Energy Poverty (EP) using thermal comfort monitoring is described in this work. There is not a uniform definition of EP, and no global recommendations indicating the thermal comfort characteristics that should be utilized to identify EP. Most Internet of Things (IoT)-based systems designed for EP identification measure energy consumptions (electricity and gas). There is a lack of works that use IoT-based systems to identify EP through the monitoring of thermal comfort parameters. To address the deficiencies discovered in the identification of EP from the perspective of thermal efficiency, an IoT-based monitoring system was designed, developed, and tested. A first pilot was installed in a household in Getafe. A full month of temperature, relative humidity, and CO

Indexed as

Energy povertyFuel povertyInternet of thingsMonitoringSensorsThermal comfort

Identifiers

PMID36711304
PMCPMC9876999

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.