dc.contributor.advisor | Islam, Md. Motaharul | |
dc.contributor.author | Alam, Md. Sakirul | |
dc.contributor.author | Ahsan, Farshid | |
dc.contributor.author | Sarker, Anik | |
dc.date.accessioned | 2021-06-22T07:16:40Z | |
dc.date.available | 2021-06-22T07:16:40Z | |
dc.date.copyright | 2020 | |
dc.date.issued | 2020-04 | |
dc.identifier.other | ID 16101233 | |
dc.identifier.other | ID 16301088 | |
dc.identifier.other | ID 16301007 | |
dc.identifier.uri | http://hdl.handle.net/10361/14636 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 35-37). | |
dc.description.abstract | In recent day situation, the non-stop increase in air and noise pollution can be an
enormous direful downside for our country. It has become an obligatory to manage
and ttingly monitor true so, the speci ed steps to manage true may be undertaken.
According to World Health Organization (WHO), 60dB is that the sound level hu-
man will tolerate while not gradual loss of hearing. Around 11.7% of the population
in Asian country have lost their hearing thanks to pollution says the Department of
Environment (DoE) study, that was conducted in 2017 and for pollution it a ects
the human body's metabolic process and cardiac systems, and additionally a ects
the eyes and di erent body organs.. Pollution additionally causes various diseases
like cancer that have an e ect on di erent body organs. Therefore, in our project,
an IoT primarily based technique exploitation Raspberry Pi is employed to observe
and check live the Air quality and also the noise pollution of a neighborhood, are
projected. System uses air sensors to sense presence of harmful gases/compounds
within the air and perpetually transmit this information to micro controller. Ad-
ditionally system keeps measuring excessive sound level and reports it to the web
server over IoT. We tend to additionally need to predict the pollution level of sound
and harmful gases so it may be prevented more.This permits authorities to observe
pollution in several areas and take action against it. For taking action, we've to
research it and that we can analyze it by Machine learning algorithms. | en_US |
dc.description.statementofresponsibility | Md. Sakirul Alam | |
dc.description.statementofresponsibility | Farshid Ahsan | |
dc.description.statementofresponsibility | Anik Sarker | |
dc.format.extent | 37 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | IoT | en_US |
dc.subject | Air monitoring | en_US |
dc.subject | Multi-Layer Perception | en_US |
dc.subject | Principal Com- ponent Analysis | en_US |
dc.subject | Long Short Term Memory | en_US |
dc.subject.lcsh | Machine Learning | |
dc.subject.lcsh | Internet of Things | |
dc.title | Environmental monitoring with the help of Internet of Things (loT) and machine learning | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B. Computer Science | |