An open-source framework for smartphone-based indoor localization

In the Ambient Assisted Living (AAL) scenario, indoor localization represents one of the main pillars for the development of contextaware applications. In this context, comparing and testing indoor positioning system is a hot topic in the indoor localization research community. In fact, after several years algorithms and methods have been developed and matured, no general frameworks exist yet to reliably compare them. The scarcity of common datasets for off-line test of emerging indoor positioning systems, together with the lack of available frameworks for real-time comparison and evaluation of indoor localization solutions, is one of the main barriers to their standardization. The lack of a common usable software framework for implementing and testing new algorithms, on a fair basis, is an additional barrier. In this work, we address this research challenge by proposing a free software framework enabling the development of indoor localization applications on the Android platform. It is composed of two applications: PrettyIndoor is a positioning app, FingerFood is a fingerprint-building app.We show that the framework's modular architecture can be exploited to easily develop many data fusion strategies, in order to easily compare and improve indoor positioning systems.