System Architecture for Positioned Data Collection : An investigation and implementation of a system architecture for positioned data collection with focus on indoor environments and Android smartphones.

Abstract: With the location based service market being estimated to drastically increase in value to over 77 billion dollars in 2021, novel approaches to amass and combine data are being explored. One such novel approach is that of collecting positioned data (PD), which in turn consists of data gathered from radio signals associated to ground truth positions (GTP). This type of PD can be used to benefit such things as spatial network analysis or supportive data for positioning algorithms. In this thesis we investigate how such PD can be collected, managed and stored in an effective manner regardless of environment. As a means to investigate this, we have proposed a positioned data collection (PDC) system architecture.The proposed PDC system architecture has been designed based on documentation related to six different PDC related systems, the ADD method, the ATAM method, the three-tier architecture pattern and a proposed PDC system definition. Parts of the proposed architecture have been chosen for implementation and testing. The chosen parts were those which were designed to collect PD within indoor environments, as it is more scientifically interesting compared to outdoor environments. The results gathered from the tests proved that the implemented PDC system parts worked as intended, successfully associating radio signal data values to both local- and geographical GTP. Ways of altering the association between radio signal data and GTP were also explored and tested, with the most prominent alteration approach being that of spatial filtration. Both the proposed architecture and the results gathered from testing the implemented parts were assessed by stakeholders. The thesis work was generally well accepted by the stakeholders, meeting little criticism and providing valuable insights.