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A Cost-Efficient Bluetooth Low Energy Based Indoor Positioning System for IoT Applications
Linköping University, Department of Computer and Information Science.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The indoor positioning system is a series of networking systems used to monitor/locate objects at indoor area as opposed that of GPS which does the same at outdoor. The increase in the popularity of the Internet of Things made the demand for Bluetooth Low Energy technology more and more essential due to their compatibility in the smartphones which makes it to access easier. The BLE’s reliable signal and accuracy in calculating the distance has a cutting edge on others in IPS. In this thesis, the Bluetooth Low Energy indoor positioning system was designed and implemented in the office area, and the positionofIoTdevicesweremonitored. OntheIoTdevices,thebeaconswereplaced. And thesebeaconswerecoveringtheofficearea. Thereceiver,smartphoneinourcase,recorded theReceivedSignalStrengthIndicationofthetransmittedsignalsfromthebeaconswithin the range of the signal and stored the collected data in a database. Two experiments have beenconducted. Oneisforbeaconsthatarestationaryandonethatismoving. Toevaluate these experiments, a few tests were performed to predict the position of beacons based on therecordedreceivedsignalstrength’s. Inthecaseofstationarybeacons, itoffersaccuracy range from 1 m to 5 m, and 3 m to 9.5 m in anticipating the position of each beacon in the case of moving beacon. This methodology was a mixture of fingerprinting and an algorithm of multilateration. Finally, the experiments show that the algorithm used provides the most accurate indoor position using BLE beacons that can be monitored through an Android-based application in real-time.

Place, publisher, year, edition, pages
2019. , p. 67
Keywords [en]
Indoor positioning system, Internet of Things, Bluetooth Low Energy technology, RSSI, fingerprinting, multilateration.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-162208ISRN: LIU-IDA/LITH-EX-A--19/090--SEOAI: oai:DiVA.org:liu-162208DiVA, id: diva2:1372490
External cooperation
NavAlarm AB
Subject / course
Computer science
Presentation
2019-10-24, Muhammad al-Khwarizmi, Linköping, 11:00 (English)
Supervisors
Examiners
Available from: 2019-11-26 Created: 2019-11-24 Last updated: 2019-11-26Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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More styles
Language
  • de-DE
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  • Other locale
More languages
Output format
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