Evidence map›Paper›PMID 31979168›Full record

ArticleSensors (Basel, Switzerland)2020

Wavelet-Based Filtration Procedure for Denoising the Predicted CO

Jan Vanus, Klara Fiedorova, Jan Kubicek, Ojan Majidzadeh Gorjani, Martin Augustynek

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Sensor Technology for Smart Homes.Sensors (Basel, Switzerland) · 2020
    Article
  4. Article
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

5 authors.

Jan VanusDepartment of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic.
Klara FiedorovaDepartment of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic.
Jan KubicekDepartment of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic.
Ojan Majidzadeh GorjaniDepartment of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic.
Martin AugustynekDepartment of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic.

Funding

European Regional Development Fund CZ.02.1.01/0.0/0.0/16_019/0000867
6 · The paper itself

Abstract

The operating cost minimization of smart homes can be achieved with the optimization of the management of the building's technical functions by determination of the current occupancy status of the individual monitored spaces of a smart home. To respect the privacy of the smart home residents, indirect methods (without using cameras and microphones) are possible for occupancy recognition of space in smart homes. This article describes a newly proposed indirect method to increase the accuracy of the occupancy recognition of monitored spaces of smart homes. The proposed procedure uses the prediction of the course of CO

Indexed as

artificial neural networkcloud computingintelligent buildingsInternet of Thingsmultilayer perceptronpredictionsmart homewavelet transformation

Identifiers

PMID31979168
PMCPMC7038360

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.