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A new model of air quality prediction using lightweight machine learning

Air pollution has become one of the environmental concerns in recent years due to its harmful threats to human health. To inform people about the air quality in their living areas, it is essential to measure the extent of pollution in the atmosphere. Air pollution sensors are assembled at static, fi...

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Bibliographic Details
Main Authors: N. H. Van, P. Van Thanh, D. N. Tran, D. T. Tran
Format: Bài trích
Language:English
Published: Springer 2022
Subjects:
Air Quality Index
Lightweight machine learning
Online Access:https://link.springer.com/article/10.1007/s13762-022-04185-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/5966
https://doi.org/10.1007/s13762-022-04185-w
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spelling oai:localhost:PNK-59662022-08-17T05:54:51Z A new model of air quality prediction using lightweight machine learning N. H. Van P. Van Thanh D. N. Tran D. T. Tran Air Quality Index Lightweight machine learning Air pollution has become one of the environmental concerns in recent years due to its harmful threats to human health. To inform people about the air quality in their living areas, it is essential to measure the extent of pollution in the atmosphere. Air pollution sensors are assembled at static, fixed-site measurement monitoring stations to acquire data. The data can be processed at the fixed stations or transmitted to the server to predict the Air Quality Index (AQI). Some previous studies applied machine learning algorithms to predict the AQI. Even though those works showed good performance on specific data, the results are not consistent on different datasets 2022-07-13T02:00:08Z 2022-07-13T02:00:08Z 2022 Bài trích https://link.springer.com/article/10.1007/s13762-022-04185-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/5966 https://doi.org/10.1007/s13762-022-04185-w en Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Air Quality Index
Lightweight machine learning
spellingShingle Air Quality Index
Lightweight machine learning
N. H. Van
P. Van Thanh
D. N. Tran
D. T. Tran
A new model of air quality prediction using lightweight machine learning
description Air pollution has become one of the environmental concerns in recent years due to its harmful threats to human health. To inform people about the air quality in their living areas, it is essential to measure the extent of pollution in the atmosphere. Air pollution sensors are assembled at static, fixed-site measurement monitoring stations to acquire data. The data can be processed at the fixed stations or transmitted to the server to predict the Air Quality Index (AQI). Some previous studies applied machine learning algorithms to predict the AQI. Even though those works showed good performance on specific data, the results are not consistent on different datasets
format Bài trích
author N. H. Van
P. Van Thanh
D. N. Tran
D. T. Tran
author_facet N. H. Van
P. Van Thanh
D. N. Tran
D. T. Tran
author_sort N. H. Van
title A new model of air quality prediction using lightweight machine learning
title_short A new model of air quality prediction using lightweight machine learning
title_full A new model of air quality prediction using lightweight machine learning
title_fullStr A new model of air quality prediction using lightweight machine learning
title_full_unstemmed A new model of air quality prediction using lightweight machine learning
title_sort new model of air quality prediction using lightweight machine learning
publisher Springer
publishDate 2022
url https://link.springer.com/article/10.1007/s13762-022-04185-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/5966
https://doi.org/10.1007/s13762-022-04185-w
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score 8.881002

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