Využití bezdrátové komunikace pro lokalizaci: Za hranice fingerprintingu

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but.committeeDr. Adriano Moreira (předseda) Dr. Enrique Quintana Orti (místopředseda) Dr. Antonio Crivello (člen) Dr. Sergi Trilles Oliver (člen) Dr. Maria Cristina Rodriguez Sanchez (člen)cs
but.defenceDefense report The thesis defense took place on the morning of 18 December 2023 and consisted of two parts. Firstly, the candidate presented the work carried out within the framework of the doctoral thesis for 45 minutes. Afterwards, the members of the evaluation panel discussed with the candidate, asking questions and discussing the answers for about 60 minutes. The candidate made an adequate defense of his doctoral thesis, showing a good disposition and answering all the questions correctly. In his answers, the candidate demonstrated a good command of the subject matter of the dissertation as well as sufficient knowledge of the state of the art in the field.cs
but.jazykangličtina (English)
but.programElectronics and Information Technologies (Double-Degree)cs
but.resultpráce byla úspěšně obhájenacs
dc.contributor.advisorFrýza, Tomášen
dc.contributor.authorBravenec, Tomášen
dc.contributor.refereeSanchez, Maria Cristina Rodriguezen
dc.contributor.refereeCrivello, Antoninoen
dc.contributor.refereeMoreira, Adrianoen
dc.contributor.refereeOrti, Enrique Quintanaen
dc.contributor.refereeOliver, Sergi Trillesen
dc.date.accessioned2024-01-05T15:22:50Z
dc.date.available2024-01-05T15:22:50Z
dc.date.created2023cs
dc.description.abstractThe field of Location-based Services (LBS) has experienced significant growth over the past decade, driven by increasing interest in fitness tracking, robotics, and eHealth. This dissertation focuses on evaluating privacy measures in Indoor Positioning Systems (IPS), particularly in the context of ubiquitous Wi-Fi networks. It addresses non-cooperative user tracking through the exploitation of unencrypted Wi-Fi management frames, which contain enough information for device fingerprinting despite MAC address randomization. The research also explores an algorithm to estimate room occupancy based on passive Wi-Fi frame sniffing and Received Signal Strength Indicator (RSSI) measurements. Such room occupancy detection has implications for energy regulations in smart buildings. Furthermore, the thesis investigates methods to reduce computational requirements of machine learning and positioning algorithms through optimizing neural networks and employing interpolation techniques for IPS based on RSSI fingerprinting. The work contributes datasets, analysis scripts, and firmware to improve reproducibility and supports advancements in the LBS field.en
dc.description.abstractThe field of Location-based Services (LBS) has experienced significant growth over the past decade, driven by increasing interest in fitness tracking, robotics, and eHealth. This dissertation focuses on evaluating privacy measures in Indoor Positioning Systems (IPS), particularly in the context of ubiquitous Wi-Fi networks. It addresses non-cooperative user tracking through the exploitation of unencrypted Wi-Fi management frames, which contain enough information for device fingerprinting despite MAC address randomization. The research also explores an algorithm to estimate room occupancy based on passive Wi-Fi frame sniffing and Received Signal Strength Indicator (RSSI) measurements. Such room occupancy detection has implications for energy regulations in smart buildings. Furthermore, the thesis investigates methods to reduce computational requirements of machine learning and positioning algorithms through optimizing neural networks and employing interpolation techniques for IPS based on RSSI fingerprinting. The work contributes datasets, analysis scripts, and firmware to improve reproducibility and supports advancements in the LBS field.cs
dc.description.markPcs
dc.identifier.citationBRAVENEC, T. Využití bezdrátové komunikace pro lokalizaci: Za hranice fingerprintingu [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2023.cs
dc.identifier.other154914cs
dc.identifier.urihttps://hdl.handle.net/11012/244179
dc.language.isoencs
dc.publisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologiícs
dc.rightsStandardní licenční smlouva - přístup k plnému textu bez omezenícs
dc.subjectmachine learningen
dc.subjectindoor positioningen
dc.subjectprivacyen
dc.subjectWi-Fien
dc.subject802.11en
dc.subjectdata analysisen
dc.subjectpresence detectionen
dc.subjectoccupancy estimationen
dc.subjectmemory optimizationen
dc.subjectradio map interpolationen
dc.subjectmachine learningcs
dc.subjectindoor positioningcs
dc.subjectprivacycs
dc.subjectWi-Fics
dc.subject802.11cs
dc.subjectdata analysiscs
dc.subjectpresence detectioncs
dc.subjectoccupancy estimationcs
dc.subjectmemory optimizationcs
dc.subjectradio map interpolationcs
dc.titleVyužití bezdrátové komunikace pro lokalizaci: Za hranice fingerprintinguen
dc.title.alternativeExploiting Wireless Communications for Localization: Beyond Fingerprintingcs
dc.typeTextcs
dc.type.driverdoctoralThesisen
dc.type.evskpdizertační prácecs
dcterms.dateAccepted2023-12-18cs
dcterms.modified2023-12-30-08:32:23cs
eprints.affiliatedInstitution.facultyFakulta elektrotechniky a komunikačních technologiícs
sync.item.dbid154914en
sync.item.dbtypeZPen
sync.item.insts2024.01.05 16:22:49en
sync.item.modts2024.01.02 19:48:56en
thesis.disciplinebez specializacecs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav radioelektronikycs
thesis.levelDoktorskýcs
thesis.namePh.D.cs
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