An Application of linear Regression on Air Pollution Detection Using Deep Learning

M. Mohammed Mustafa; S. Umamaheswari; Ahmed A. Khalifa; Bassem Mokhtar; Korhan Cengiz

doi:10.1109/HORA55278.2022.9800042

An Application of linear Regression on Air Pollution Detection Using Deep Learning

M. Mohammed Mustafa
, S. Umamaheswari
, Ahmed A. Khalifa
, Bassem Mokhtar
, Korhan Cengiz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

A regularly expanding number of urban occupants think about the criticalness of the air quality to their prosperity, especially who are living in the colossal urban territories are genuinely sabotaged through air pollution. Air quality observing assumes an undeniably significant job in giving exact air contamination information to evaluating the effects of air contamination on general wellbeing. Advancement of appropriate sensor systems, by sending the correct air contamination sensors at the ideal put in, so as to address the issues of various gatherings in the city and give the genuinely necessary open administrations, merits cautious consideration, particularly when savvy city improvement is to be measured. Notwithstanding, air quality observation is an exorbitant degree. To handle such a test, air contamination sensor position can be deliberately intended to accomplish definite ideal resident driven goals without field data, and application of the linear regression to it.

Original language	English
Title of host publication	HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665468350
DOIs	https://doi.org/10.1109/HORA55278.2022.9800042
Publication status	Published - 2022
Externally published	Yes
Event	4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022 - Ankara, Turkey Duration: Jun 9 2022 → Jun 11 2022

Publication series

Name	HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings

Conference

Conference	4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022
Country/Territory	Turkey
City	Ankara
Period	6/9/22 → 6/11/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Air Quality
Deep Learning
IOT
Python
Regression

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Signal Processing
Control and Optimization
Human-Computer Interaction

Access to Document

10.1109/HORA55278.2022.9800042

Cite this

Mustafa, M. M., Umamaheswari, S., Khalifa, A. A., Mokhtar, B., & Cengiz, K. (2022). An Application of linear Regression on Air Pollution Detection Using Deep Learning. In HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings (HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HORA55278.2022.9800042

An Application of linear Regression on Air Pollution Detection Using Deep Learning. / Mustafa, M. Mohammed; Umamaheswari, S.; Khalifa, Ahmed A. et al.
HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mustafa, MM, Umamaheswari, S, Khalifa, AA, Mokhtar, B & Cengiz, K 2022, An Application of linear Regression on Air Pollution Detection Using Deep Learning. in HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings. HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings, Institute of Electrical and Electronics Engineers Inc., 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022, Ankara, Turkey, 6/9/22. https://doi.org/10.1109/HORA55278.2022.9800042

Mustafa MM, Umamaheswari S, Khalifa AA, Mokhtar B, Cengiz K. An Application of linear Regression on Air Pollution Detection Using Deep Learning. In HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. (HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings). doi: 10.1109/HORA55278.2022.9800042

Mustafa, M. Mohammed ; Umamaheswari, S. ; Khalifa, Ahmed A. et al. / An Application of linear Regression on Air Pollution Detection Using Deep Learning. HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings).

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abstract = "A regularly expanding number of urban occupants think about the criticalness of the air quality to their prosperity, especially who are living in the colossal urban territories are genuinely sabotaged through air pollution. Air quality observing assumes an undeniably significant job in giving exact air contamination information to evaluating the effects of air contamination on general wellbeing. Advancement of appropriate sensor systems, by sending the correct air contamination sensors at the ideal put in, so as to address the issues of various gatherings in the city and give the genuinely necessary open administrations, merits cautious consideration, particularly when savvy city improvement is to be measured. Notwithstanding, air quality observation is an exorbitant degree. To handle such a test, air contamination sensor position can be deliberately intended to accomplish definite ideal resident driven goals without field data, and application of the linear regression to it.",

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AB - A regularly expanding number of urban occupants think about the criticalness of the air quality to their prosperity, especially who are living in the colossal urban territories are genuinely sabotaged through air pollution. Air quality observing assumes an undeniably significant job in giving exact air contamination information to evaluating the effects of air contamination on general wellbeing. Advancement of appropriate sensor systems, by sending the correct air contamination sensors at the ideal put in, so as to address the issues of various gatherings in the city and give the genuinely necessary open administrations, merits cautious consideration, particularly when savvy city improvement is to be measured. Notwithstanding, air quality observation is an exorbitant degree. To handle such a test, air contamination sensor position can be deliberately intended to accomplish definite ideal resident driven goals without field data, and application of the linear regression to it.

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An Application of linear Regression on Air Pollution Detection Using Deep Learning

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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