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dc.contributor.advisorSabuj, Saifur Rahman
dc.contributor.authorAl-Farabi, Md.
dc.contributor.authorChowdhury, Muntasir
dc.contributor.authorHossain, Md. Rafat
dc.contributor.authorReaduzzaman, Md.
dc.date.accessioned2020-02-05T05:40:17Z
dc.date.available2020-02-05T05:40:17Z
dc.date.copyright2019
dc.date.issued2019-12
dc.identifier.otherID 16121104
dc.identifier.otherID 16121113
dc.identifier.otherID 16121053
dc.identifier.otherID 16121080
dc.identifier.urihttp://hdl.handle.net/10361/13735
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2019.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 51-53).
dc.description.abstractOver the last few decades, the main minacious and dodgy calamity that grab the world’s attention is “Greenhouse Effect”. It is evident that Carbon dioxide, methane, nitrous oxide, fluorinated gasses and water vapor are the common phenomenon causing this disaster. These gasses remain in the atmosphere causing the temperature to rise as the sunlight can pass through the ozone layer, but they can’t go back and trap inside the earth atmosphere. Being great concern to the future world, this proposal emphasizes on collecting data from the atmosphere and predicting future temperature and amount of gasses with the help of an Unmanned Aerial Vehicle (UAV) system. This system is designed as a comprised of sensors and database system. With the help of the drone which carries humidity sensor DHT11, gas sensors MQ2, MQ7, MQ135 along with temperature sensor TCH11, TCH22. The data that is needed for the further prediction will be collected by the help of these sensors. Node MCU will also be used. It will relate to Arduino Nano. With the help of Wi-Fi system all the data will be stored into a server. Based on the data, real-time graph for individual aspects will be plotted in an interface for better visualization, which will be helpful for monitoring and analysis. For the future prediction regression model is chosen and suggested values are compared. From the collecting values, if difference is much higher along with crossing the safe threshold limit. This proposal aims to identify the impact of “Green House” in a region and claims to raise awareness.en_US
dc.description.statementofresponsibilityMd. Al-Farabi
dc.description.statementofresponsibilityMuntasir Chowdhury
dc.description.statementofresponsibilityMd. Rafat Hossain
dc.description.statementofresponsibilityMd. Readuzzaman
dc.format.extent53 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.subjectGreen house effecten_US
dc.subjectLinear regression analysisen_US
dc.subjectUAVen_US
dc.subjectNodeMCUen_US
dc.subjectGas sensorsen_US
dc.subject.lcshAir--Pollution
dc.subject.lcshVehicles, Remotely piloted
dc.titleAir pollution monitoring system using unmanned aerial vehicle in Bangladeshen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, Brac University
dc.description.degreeB. Electrical and Electronic Engineering


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