Human identification using wifi signal
Cataloged from PDF version of thesis report.
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| Kieli: | English |
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BRAC University
2018
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| Linkit: | http://hdl.handle.net/10361/9505 |
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10361-9505 |
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10361-95052022-01-26T10:08:26Z Human identification using wifi signal Nipu, Md. Nafiul Alam Talukder, Souvik Chakrabarty, Amitabha Islam, Md. Saiful Department of Computer Science and Engineering, BRAC University Fingerprint identification Face recognition Wifi signal Human identification Cataloged from PDF version of thesis report. Includes bibliographical references (pages 45-49). This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. There have been a large number of methods already exists to identify human(e.g.,face recognition, gait recognition, fingerprint identification, etc.). Channel State Information(CSI) obtained from Wifi chipsets already has proven to be a efficient for detecting humans uniquely. We are presenting a system which can identify human uniquely and we are showing that Wifi signal can be used for identifying humans. We are working on the channel properties of a communication link which describes how a signal propagates from the transmitter to receiver and represents the combined effect. Each of the individuals have unique gait and also it is proven. Therefore, for that every human would have distract signal uniquely in the same Wifi spectrum. Our system will analysis the Channel State Information(CSI) to acquire unique features of an individual which will allow us to identify a human precisely. We have used two separate algorithms with an accuracy of 95% to 84% in Decision Tree and 97.5% to 78% in Random Forest between a group of 2 to 5 people. We propose that this technology can be used in office or in smart homes for security reasons as it is allowing us to identify humans. Nipu, Md. Nafiul Alam Talukder, Souvik B. Computer Science and Engineering 2018-02-19T04:27:11Z 2018-02-19T04:27:11Z 2017 12/26/2017 Thesis ID 13201006 ID 13201061 http://hdl.handle.net/10361/9505 en BRAC University thesis reports 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. 49 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Fingerprint identification Face recognition Wifi signal Human identification |
| spellingShingle |
Fingerprint identification Face recognition Wifi signal Human identification Nipu, Md. Nafiul Alam Talukder, Souvik Human identification using wifi signal |
| description |
Cataloged from PDF version of thesis report. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Nipu, Md. Nafiul Alam Talukder, Souvik |
| format |
Thesis |
| author |
Nipu, Md. Nafiul Alam Talukder, Souvik |
| author_sort |
Nipu, Md. Nafiul Alam |
| title |
Human identification using wifi signal |
| title_short |
Human identification using wifi signal |
| title_full |
Human identification using wifi signal |
| title_fullStr |
Human identification using wifi signal |
| title_full_unstemmed |
Human identification using wifi signal |
| title_sort |
human identification using wifi signal |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9505 |
| work_keys_str_mv |
AT nipumdnafiulalam humanidentificationusingwifisignal AT talukdersouvik humanidentificationusingwifisignal |
| _version_ |
1814307623061684224 |