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Data analytics have the potential to increase the value of data emitted from smart devices in usercentric Internet of Things environments, such as smart home, drastically. In order to allow businesses and end-consumers alike to tap into this potential, appropriate analytics architectures must be present. Current solutions in this field do not tackle all of the diverse challenges and requirements, which were identified in previous research. Specifically, personalized, extensible analytics solutions, which still offer the means to address big data problems are scarce. In this paper, we therefore present an architectural solution, which was specifically designed to address the named challenges. Furthermore, we offer insights into the prototypical implementation of the proposed concept as well as an evaluation of its performance against traditional big data architectures.

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The Internet of Things (IoT) is based on connected devices which are often heterogeneous in terms of supported communication protocols, interfaces and message formats. IoT-aware business processes, which are executed by process engines, are often bound to specific device types. This decreases their reusability when they are ought to be deployed in multiple IoT scenarios where the ability of supporting different device types is an important requirement. In this paper, we introduce a novel approach on how to overcome the heterogeneity of IoT devices, thus increasing the reusability of IoT-aware business processes. The contribution of this work to information systems research is twofold: First, we present a device abstraction model as the basis to define business process tasks across heterogeneous device types without the need of dealing with their technical implementations. Secondly, we propose a system architecture which supports the modeling, deployment, execution and reuse of IoT-aware business processes.