Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156699
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dc.contributor.authorEng, Bryan Ze Enen_US
dc.date.accessioned2022-04-22T07:13:12Z-
dc.date.available2022-04-22T07:13:12Z-
dc.date.issued2022-
dc.identifier.citationEng, B. Z. E. (2022). Indoor localization and navigation via Wi-Fi & bluetooth fingerprinting. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156699en_US
dc.identifier.urihttps://hdl.handle.net/10356/156699-
dc.description.abstractNavigational systems have been an integral part of our everyday lives, and with the advancement in technology, Indoor localization (IL) has become a hot topic for research in recent years. There are numerous methodologies for IL, and one of the most popular methodologies is Wi-Fi fingerprinting. In this report, the author would further expand on the methodology by utilizing deep neural networks (DNN) and transfer learning (TL) on top of fingerprinting to build a model that is able to be integrated in an IL application. Apart from Wi-Fi, an experiment was also conducted with Bluetooth Low-level Energy (BLE) beacons for fingerprinting. In addition to conducting experiments on already available public datasets, this project also covers real-life data with data collected in two locations: Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), and a museum building complex. After the data collection and pre-processing of data, DNN experiments were conducted on 3 datasets (SCALE@NTU, museum building complex, UJI Indoor Dataset) to evaluate the performance of the DNN models with regards to the data collected. Transfer Learning was also implemented for the UJI Indoor Dataset to compare the accuracy and run-time performance against traditional DNN.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relation2019-1078en_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleIndoor localization and navigation via Wi-Fi & bluetooth fingerprintingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorOh Hong Lyeen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.organizationNCS PTE. LTD.en_US
dc.contributor.researchSingtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU)en_US
dc.contributor.supervisoremailhloh@ntu.edu.sgen_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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