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dc.contributor.authorEbner, Frank
dc.date.accessioned2022-03-17T15:24:35Z
dc.date.available2022-03-17T15:24:35Z
dc.date.issued2021
dc.identifierONIX_20220317_9783832552329_2
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/79453
dc.description.abstractDuring the last century, navigation systems have become ubiquitous and guide drivers, cyclists, and pedestrians towards their desired destinations. While operating worldwide, they rely on line-of-sight conditions towards satellites and are thus limited to outdoor areas. However, finding a gate within an airport, a ward within a hospital, or a university's auditorium also represent navigation problems. To provide navigation within such indoor environments, new approaches are required. This thesis examines pedestrian 3D indoor localization and navigation using commodity smartphones: A desirable target platform, always at hand and equipped with a multitude of sensors. The IMU (accelerometer, gyroscope, magnetometer) and barometer allow for pedestrian dead reckoning, that is, estimating relative location changes. Absolute whereabouts can be determined via Wi-Fi, an infrastructure present within most public buildings, or by using Bluetooth Low Energy Beacons as inexpensive supplement. The building's 3D floorplan not only enables navigation, but also increases accuracy by preventing impossible movements, and serves as a visual reference for the pedestrian. All aforementioned information is fused by recursive density estimation based on a particle filter. The conducted experiments cover both, theoretical backgrounds and real-world use-cases. All discussed approaches utilize the infrastructure found within most public buildings, are easy to set up, and maintain. Overall, this thesis results in an indoor localization and navigation system that can be easily deployed, without requiring any special hardware components.
dc.languageEnglish
dc.relation.ispartofseriesHuman Data Understanding - Sensors, Models, Knowledge
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topicsen_US
dc.subject.otherProbabilistic Sensor Fusion
dc.subject.otherPedestrian Dead Reckoning
dc.subject.otherWi-Fi Location Estimation
dc.subject.otherIndoor Floorplans
dc.subject.other3D Movement Prediction
dc.titleSmartphone-Based 3D Indoor Localization and Navigation
dc.typebook
oapen.identifier.doi10.30819/5232
oapen.relation.isPublishedBy04b263a1-7fba-4491-9eae-1c394ac42fc3
oapen.relation.isbn9783832552329
oapen.imprintLogos Verlag Berlin
oapen.series.number1
oapen.pages351
oapen.place.publicationBerlin


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