A software architecture for a personalized and context-aware indoor navigation system

This paper proposes a context-aware model for a mobile indoor navigation system in which users' needs play a key role. We will present an overview of the underlying architecture, describe the main data involved, and show how they are used; we will especially focus on the role of the users' preferences and accessibility needs, since they are the key elements that allow to build a personalized and inclusive user experience. Thanks to a service-oriented architecture, a mobile application will be able to retrieve the most adequate information for its user about a specific point of interest in the environment, and issue a personalized notification. Examples of interaction with the system from the perspective of back-end operators will also be provided, in which we will show how the model entities are translated into practice during the configuration phase of the system. We will pay particular attention to the case of visually impaired users, for whom accessible navigation apps have proven to be effective assistive solutions to achieve better social inclusion and autonomy. We will assume to be using BLE beacons and an Android mobile app for our simulations, anyway we will show that our model is generalizable. Finally, future possible enhancements of the system will be discussed.