University of Bahrain
Scientific Journals

Air Quality Monitoring and Predicting System for Sustainable Health Management using Multi-Linear Regression in IoT

Show simple item record

dc.contributor.author Saritha
dc.contributor.author V, Sarasvathi
dc.contributor.author S, Smrithi
dc.date.accessioned 2020-04-29T22:50:13Z
dc.date.available 2020-04-29T22:50:13Z
dc.date.issued 2020-05-01
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/3823
dc.description.abstract Fresh Air is the preeminent requirement of each and every human being for a healthy living. With the increase in urbanization and the number of vehicles on road, large amount of various poisonous gases and Particulate Matter is released into the environment, causing global warming, rise in sea level, change in climatic condition, rainfall pattern, droughts and floods, etc. along with different types of endemic and epidemic diseases. Air pollution has become non-trivial phenomena in the world and has a diverse effect on every living being. In this paper, a model is built to provide a solution, to monitor the pollution level in air in any location and a warning message is sent against the exposure of living beings to hazardous gases. System is built using Machine Learning technique, the real time data collected from different locations is used as test data, and the model is trained with the current values to predict the future gaseous values. A graphical representation of the air quality is presented to the user to display the current and predicted values. If values exceed a certain predefined threshold, then possible symptoms are displayed to the user. en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Air Quality en_US
dc.subject Multi – Linear regression en_US
dc.subject Particulate Matter en_US
dc.title Air Quality Monitoring and Predicting System for Sustainable Health Management using Multi-Linear Regression in IoT en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/090307
dc.volume Volume 09 en_US
dc.issue Issue 03 en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Computer Science and Engineering, PESIT Bangalore South Campus, Bengaluru -560100 and affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India en_US
dc.source.title International Journal of Computing and Digital Systems en_US


Files in this item

The following license files are associated with this item:

This item appears in the following Issue(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 International Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International

All Journals


Advanced Search

Browse

Administrator Account