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| Type | Bachelor's Thesis |
| Scope | Discipline-based scholarship |
| Title | BluePIL 2.0: Toward Automated Deployment and Operation |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2022 |
| Abstract Text | Recent studies in the field of localization and identification of persons indoors have shown that there are various possibilities to track individuals indoors. Such localization techniques can be divided into either active or passive indoor localization systems, needing a direct or no direct connection with the system respectively. The corona pandemic unveiled the importance and benefit of applying such techniques to trail possible infections of persons to contain the spread. In other fields, it has also been valuable for marketing analysis. In a recent master’s thesis at UZH, a passive localization and identification tool for tracking devices using only passive Bluetooth signals was explored in collaboration with Livealytics. The solution called BluePIL provided moderate accuracy, which can be considered to work despite the underlying naturally noisy data. The time consuming deployment, calibration and analysis yield a second version of it, called BluePIL 2.0, on which this thesis focuses on. Using new hardware, additional power-banks and by adding a new analysis tool with adjustable parameters, a new version is developed. The experiments have shown that BluePIL 2.0 improves the system by reducing the manual steps to deploy the system and improving mobility. The time to launch the system is 7.32 seconds on average. In addition, the analysis tool contributes to a better understanding of the indoor scenarios by displaying an updating plot of the tracked devices and providing the option to calibrate the path loss coefficient of the localization algorithm during data collection. The near-real-time plot is set to update within 0.5 seconds. In general, BluePIL 2.0 met the goals in a requirements-based evaluation. |
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