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dc.contributor.advisorIslam, Md. Motaharul
dc.contributor.authorAlam, Md. Sakirul
dc.contributor.authorAhsan, Farshid
dc.contributor.authorSarker, Anik
dc.date.accessioned2021-06-22T07:16:40Z
dc.date.available2021-06-22T07:16:40Z
dc.date.copyright2020
dc.date.issued2020-04
dc.identifier.otherID 16101233
dc.identifier.otherID 16301088
dc.identifier.otherID 16301007
dc.identifier.urihttp://hdl.handle.net/10361/14636
dc.descriptionThis 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.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 35-37).
dc.description.abstractIn 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.statementofresponsibilityMd. Sakirul Alam
dc.description.statementofresponsibilityFarshid Ahsan
dc.description.statementofresponsibilityAnik Sarker
dc.format.extent37 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac 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.subjectIoTen_US
dc.subjectAir monitoringen_US
dc.subjectMulti-Layer Perceptionen_US
dc.subjectPrincipal Com- ponent Analysisen_US
dc.subjectLong Short Term Memoryen_US
dc.subject.lcshMachine Learning
dc.subject.lcshInternet of Things
dc.titleEnvironmental monitoring with the help of Internet of Things (loT) and machine learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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