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Changes in air pollution exposure after residential relocation and body mass index in children and adolescents: A natural experiment study

Abstract:
Air quality index measurements in Indonesia are carried out by ministry of environment and forestry (KLHK). The Ministry divides air quality levels into 5 categories, namely good, moderate, unhealthy, very unhealthy and dangerous. In this study, 3 air quality categories were used as primary research data, namely good, moderate and unhealthy because the others, never occurred in Indonesia from the time this research was conducted until its completion. This research develops the color histogram method in order to recognize the shape of an object in an image. First stage in this research is inputting the sky image into the system. Then carry out pre-processing in the form of cropping the image to obtained is only an image of sky. Next, convert the red, green and blue (RGB) colored sky image to Grayscale, then image enhancement, then noise reduction. After that is processed using development of the color histogram method. Refinement of color histogram method has yielded an impressive accuracy level of 90%, validated through the analysis of 30 sky images. The method successfully detected 27 images accurately, while three images posed detection challenges. The findings of this research is color histogram method can be used to identify objects especially air pollution from sky images
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.envpol.2023.122217

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Role:
Author
ORCID:
0000-0001-9924-5961
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Role:
Author
ORCID:
0000-0001-6552-6060
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Role:
Author
ORCID:
0000-0002-4467-0220
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Role:
Author
ORCID:
0000-0002-6432-2098


Publisher:
Elsevier
Journal:
Environmental Pollution More from this journal
Volume:
334
Pages:
122217-122217
Article number:
122217
Publication date:
2023-07-17
DOI:
EISSN:
1873-6424
ISSN:
0269-7491


Language:
English
Keywords:
Pubs id:
1493314
Local pid:
pubs:1493314
Source identifiers:
W4384500964
Deposit date:
2026-05-11
ARK identifier:
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