Evidence map›Paper›PMID 39962119›Full record

ArticleScientific reports2025

Study of intelligent home environment system based on big data and improved k-means algorithm.

Shaopeng Yu, Chenyu Liu, Mingmei Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Shaopeng YuSchool of Information and Intelligent Engineering, Tianjin Renai College, Tianjin, China. globely@163.com.
Chenyu LiuSchool of Information and Intelligent Engineering, Tianjin Renai College, Tianjin, China.
Mingmei LiSchool of Information and Intelligent Engineering, Tianjin Renai College, Tianjin, China.

Funding

TianjiResearch Innovation Project for Postgraduate Students 2021KJ085
6 · The paper itself

Abstract

The Embedded operating system based on STC12C5A MCU is designed to facilitate real-time monitoring and control of the home environment, in order to solve some problems such as low acquisition frequency, poor real-time performance, lack of feedback and adaptation. The Kalman filter and improved k-means algorithm are used to analyze the big data which is processed by BP neural network, and then the most comfortable living environment parameters can be obtained. The independent monitoring mechanism and feedback adjustment are designed to achieve efficient collaboration and stable operation of system hardware and software. The test results show that the system has high acquisition accuracy, fast response speed, good reliability performance, as well as good real-time and adaptive capabilities.

Indexed as

Big dataBP neural networkEnvironmental monitoringImproved k-means algorithmKalman filter

Identifiers

PMID39962119
PMCPMC11832891

What OpenQuestion holds

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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.