Evidence map›Paper›PMID 36032802›Full record

ArticleInternational journal of analytical chemistry2022

Residential Environment Pollution Monitoring System Based on Cloud Computing and Internet of Things.

Jing Mi, Xinghua Sun, Shihui Zhang, Naidi Liu

RetractedAbstract readRetracted Publication
In one paragraph

Article in International journal of analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jing MiCollege of Information Science and Engineering, HeBei North University, Zhangjiakou 075000, Hebei, China.ORCID https://orcid.org/0000-0002-0090-6959
Xinghua SunCollege of Information Science and Engineering, HeBei North University, Zhangjiakou 075000, Hebei, China.ORCID https://orcid.org/0000-0003-3141-7450
Shihui ZhangCollege of Information Science and Engineering, HeBei North University, Zhangjiakou 075000, Hebei, China.ORCID https://orcid.org/0000-0002-8086-8306
Naidi LiuCollege of Information Science and Engineering, HeBei North University, Zhangjiakou 075000, Hebei, China.ORCID https://orcid.org/0000-0002-3630-2567

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to solve the problems of single monitoring factor, weak comprehensive analysis ability, and poor real time performance in traditional environmental monitoring systems, a research method of residential environment pollution monitoring system based on cloud computing and Internet of Things is proposed. The method mainly includes two parts: an environmental monitoring terminal and an environmental pollution monitoring and management platform. Through the Wi-Fi module, the data is sent to the environmental pollution monitoring and management platform in real time. The environmental monitoring management platform is mainly composed of environmental pollution monitoring server, web server, and mobile terminal. The results are as follows. The data measured by the system is close to the data measured by the instrument, and the overall error is small. The measurement error of harmful gases is about 6%. PM 2.5 is about 6.5%. Noise is about 1%. The average time for sensor data update is 0.762 s. The average alarm response time is 2 s. The average data transfer time is 2 s. Practice has proved that the environmental pollution monitoring and alarm system operates stably and can realize real-time collection and transmission of data such as noise, PM 2.5, harmful gas concentration, illumination, GPS, and video images, providing a reliable guarantee for timely environmental pollution control.

Identifiers

PMID36032802
PMCPMC9402352

What OpenQuestion holds

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LicenceCC BY
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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.