Ensembles of indoor positioning systems based on fingerprinting: Simplifying parameter selection and obtaining robust systems

Selecting the appropriate parameters for an indoor positioning system may be a difficult task due to the large number of parameter combinations. It is more complex in realistic multi-building multi-floor environments, where severe wrong building and floor errors occur but they are not highlighted in the main evaluation metric. Moreover, a selected parameter configuration, that may seem appropriate in the system validation, may not have the expected behaviour in a real deployment. In order to address these issues, an ensemble of indoor positioning systems is introduced. A base estimator with 2.332 parameter combinations has been used. According to the results, this model simplifies the parameter selection and provides more robust systems.