Abstract

AbstractBuilding mobile context‐aware systems is inherently complex and non‐trivial task. It consists of several phases starting from acquisition of context, through modeling to execution of contextual models. Today, such systems are mostly implemented on mobile platforms, that introduce specific requirements, such as intelligibility, robustness, privacy, and efficiency. Over the last decade, along with the rapid development of mobile industry, many approaches were developed that unevenly support these requirements. This is mainly caused by the fact that current modelling and reasoning methods are not crafted to operate in mobile environments. We argue that the use of rule‐based reasoning tailored to mobile environments is an optimal solution. Rules are based on symbolic knowledge representation, as such they meet the general tendency to enforce understandability, intelligibility, and controllability of artificial intelligence software, as stated in the recent European Union General Data Protection Regulation. To this goal, we introduce a lightweight rule engine dedicated for Android platform called HEARTDROID. It executes models in the HMR+ rule language that are capable of expressing uncertainty of knowledge, capturing dynamics of mobile environment and provide high level of intelligibility. We present a qualitative and quantitative comparison of HEARTDROID with the most popular rule engines available.

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