Evidence map›Paper›PMID 40977770›Full record

ArticleFrontiers in public health2025

Research on intelligent design and environmental adaptability of public art installations in the context of low-carbon cities.

Wei Wu, He Ren

Abstract read
In one paragraph

Article in Frontiers in public health, 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

2 authors.

Wei WuSchool of Art and Design, Beijing Forestry University, Beijing, China.
He RenSchool of Art and Design, Beijing Forestry University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The idea of a low-carbon city is to achieve sustainable development by reducing greenhouse gas emissions. This study explores how intelligent design can enhance the environmental adaptability of public art installations and contribute to urban low-carbon goals. In the study, five representative public art installations were investigated by means of literature review, case analysis and empirical research. The results show that intelligent design functions (such as sensor response time ≤ 0.5 s and AI algorithm accuracy rate of 95%) significantly improve the environmental performance. The unit energy consumption is reduced to 0.35 kWh/h, renewable energy accounts for 85% of the total consumption, and the comprehensive carbon emission intensity is reduced to 0.24 kg CO

Indexed as

ArtArtificial IntelligenceCarbonCitiesHumansSustainable DevelopmentCarbonenvironmental adaptabilityintelligent designlow-carbon citiesmultidimensional assessmentpublic art installations

Identifiers

PMID40977770
PMCPMC12443717

What OpenQuestion 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 OpenQuestion graph.