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dc.contributor.advisorChakrabarty, Amitabha
dc.contributor.authorSohan, Asif Ahmed
dc.contributor.authorFairooz, Fabiha
dc.contributor.authorRahman, Adham Ibrahim
dc.contributor.authorAli, Mohammad
dc.date.accessioned2021-11-21T04:51:31Z
dc.date.available2021-11-21T04:51:31Z
dc.date.copyright2019
dc.date.issued2019-08
dc.identifier.otherID 15301072
dc.identifier.otherID 15301061
dc.identifier.otherID 15301091
dc.identifier.otherID 15301054
dc.identifier.urihttp://hdl.handle.net/10361/15628
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 25-26).
dc.description.abstractThe whole world is familiar with the Global Positioning System or GPS which can identify the exact position of any object with the help of satellites. Yet GPS signals are not available indoors. To overcome this, Indoor Positioning System(IPS) is used which enables us to locate objects inside an indoor environment. Our goal is to build an Indoor Positioning System by estimating the location using Received Signal Strength Indication (RSSI) through wireless networks. The proposed model will determine the position of wireless devices in a room. We took the RSSI values as coordinates and speci c reference points at every two meters making the room into a grid. The RSSI values on the reference point are measured. The position of the wireless devices will be estimated from the reference points using the trilateration method and the ITU indoor path loss model. With the aforementioned process, we calculated the position using the ITU indoor path loss model and trilateration. Using the ITU indoor path loss model our mean error was 1.01166m and while using trilateration it was 1.22m.en_US
dc.description.statementofresponsibilityAsif Ahmed Sohan
dc.description.statementofresponsibilityFabiha Fairooz
dc.description.statementofresponsibilityAdham Ibrahim Rahman
dc.description.statementofresponsibilityMohammad Ali
dc.format.extent26 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.subjectIndoor positioningen_US
dc.subjectWiFien_US
dc.subjectRSSIen_US
dc.subjectTrilaterationen_US
dc.subjectITUen_US
dc.subject.lcshWireless sensor networks.
dc.subject.lcshIndoor positioning systems (Wireless localization)
dc.titleIndoor positioning techniques using RSSI from wireless networksen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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