Magni - A framework for developing context-aware mobile applications

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Abstract

The advent of Internet and ubiquitous technologies has been fostering the appearance of intelligent mobile applications aware of their environment and the objects nearby. Despite its popularity, mobile devel-opers are often required to write large and disorganized amounts of code, mixing UI with business logic and interact, in a ad-hoc fashion, with sensor devices and services. These habits hinder the code maintenance, refactoring and testing, while negatively influencing the consistency and performance of mobile applications. In this paper we present Magni as an abstract framework for the design and implementation of personalized and context-aware mobile applications. The corner stone of the frame-work is its architectural pattern based on the Model–View–Presenter pattern in the UI layer relying in REST services the majority of the app features. This paradigm fosters the modular design, implementing the separation of concerns concept and allowing an easier implementation of unit tests. In order to validate the framework, we present a prototype for an healthcare automotive app. The main goal of the app is to facilitate the access to health related points of interest such as hospitals, clinics and pharmacies.

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Queirós, R., Portela, F., & Machado, J. (2017). Magni - A framework for developing context-aware mobile applications. In Advances in Intelligent Systems and Computing (Vol. 571, pp. 417–426). Springer Verlag. https://doi.org/10.1007/978-3-319-56541-5_43

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