An NDN based indoor positioning and navigation system
| bracu.degree.level | Undergraduate | |
| bracu.type.group | Student Works | |
| datacite.rights | Open Access | |
| dc.contributor.advisor | Chakrabarty, Amitabha | |
| dc.contributor.author | Taki, Sifat Ut | |
| dc.contributor.author | Hossain, Raiyan | |
| dc.contributor.author | Anwar, Sadia | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2020-03-08T06:14:44Z | |
| dc.date.available | 2020-03-08T06:14:44Z | |
| dc.date.copyright | 2019 | |
| dc.date.issued | 2019-12 | |
| dc.description | Cataloged from PDF version of thesis. | |
| dc.description | Includes bibliographical references (pages 53-57). | |
| dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019. | en_US |
| dc.description.abstract | Providing navigation services indoor is becoming a growing trend in recent years. Traditional GPS is not a viable solution for indoor use as it demands more accuracy and may be out of reach of GPS signals. Indoor positioning can be implmented using a variety of localized techniques that are not reliant on GPS. Among all the techniques, Wi-Fi RSSI ngerprinting based indoor positioning is very popular for its accuracy, reliability and ability to use the existing Wi-Fi infrastructure of a building. Large areas like shopping complexes, airports, universities, etc. already have an existing Wi-Fi network deployed. Making use of an existing network makes this technique cost e ective and easy to implement. However, a large indoor area with multiple oors will require a large database of Wi-Fi ngerprint data. The performance of the localization and navigation algorithms su er greatly due to this large database, both due to time requirements and computational complexity. This paper focuses on improving the performance of Wi-Fi RSSI ngerprinting based indoor positioning and navigation systems in large areas by making use of named data networking as the network architecture. We aim to demonstrate how named data networking can help improve the performance of both indoor localization and indoor navigation in various scenarios over traditional TCP/IP based solutions. | en_US |
| dc.description.degree | Bachelor of Science in Computer Science | |
| dc.description.statementofresponsibility | Sifat Ut Taki | |
| dc.description.statementofresponsibility | Raiyan Hossain | |
| dc.description.statementofresponsibility | Sadia Anwar | |
| dc.format.extent | 57 pages | |
| dc.identifier.other | ID 16101064 | |
| dc.identifier.other | ID 16101331 | |
| dc.identifier.other | ID 17201041 | |
| dc.identifier.uri | http://hdl.handle.net/10361/13836 | |
| 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 | Indoor positioning | en_US |
| dc.subject | Indoor localization | en_US |
| dc.subject | Indoor navigation | en_US |
| dc.subject | Named Data Networking | en_US |
| dc.subject | RSSI Fingerprinting | en_US |
| dc.subject.lcsh | Wireless communication systems | |
| dc.title | An NDN based indoor positioning and navigation system | en_US |
| dc.type | Thesis | en_US |