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Indoor Location Surveillance: Utilizing Wi-Fi and Bluetooth Signals
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Personal information nowadays have become valuable for many stakeholders. We want to find out how much information someone can gather from our daily devices such as a smartphone, using some budget devices together with some programming knowledge. Can we gather enough information to be able to determine a location to a target device? The main objectives of our bachelor thesis is to determine the accuracy of positioning for nearby personal devices using trilateration of short-distance communications (Wi-Fi vs Bluetooth). But also, how much and what information our devices leak without us knowing with respect to personal integrity. We collected Wi-Fi and Bluetooth data in total from four target devices. Two different experiments were executed, calibration experiment and visualization experiment. The data were collected by capturing the Wi-Fi and Bluetooth Received Signal Strength Indication(RSSI) transmitted wirelessly from target devices. We then apply a method called trilateration to be able to pinpoint a target to a location. In theory, Bluetooth signals are twice as accurate as Wi-Fi signals. In practise, we were able to locate a target device with an accuracy of 5 - 10 meters. Bluetooth signals are stable but have long response time while Wi-Fi signals have short response time but high fluctuation in the RSSI values. The idea itself, being able to determine a handheld device position is not impossible, as can be seen from our results. It may though require more powerful hardware to secure an acceptable accuracy. On the other hand, achieving this kind of results from such a cheap hardware as Raspberry Pi:s are truly amazing.

Place, publisher, year, edition, pages
2019. , p. 69
Keywords [en]
surveillance, positioning, trilateration, personal integrity
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:bth-17978OAI: oai:DiVA.org:bth-17978DiVA, id: diva2:1320998
Subject / course
PA1445 Kandidatkurs i Programvaruteknik
Educational program
PAGPT Software Engineering
Supervisors
Examiners
Available from: 2019-06-10 Created: 2019-06-06 Last updated: 2019-06-10Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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