Abstract
The ubiquity and the low prices of mobile devices like smartphones and tablets as well as the availability of radio networks hold the opportunity for companies to reorganize and optimize their business processes. These mobile devices can help users to execute their process steps by showing instructions or by augmenting reality. Moreover, they can improve the efficiency and effectiveness of business processes by adapting the business process execution. This can be achieved by evaluating the user’s context via the many sensor-data from a smart device and adapting the business process to the current context. The data, not only collected from internal sensors but also via networks from other sources, can be aggregated and interpreted to evaluate the context. To use the advantages of context recognition for business processes an simple way to model this data collection and aggregation is needed. This would enable a more structured way to implement supportive mobile (context-aware) applications. Today, there is no modeling language that supports the modeling of data collection and aggregation to context and offers code generation for mobile applications via a suitable tool. Therefore, this paper presents a domain specific modeling language for context and a model-driven architecture (MDA) based approach for mobile context-aware apps. The modeling language and the MDA-approach have been implemented in an Eclipse-based tool.
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Dörndorfer, J., Hopfensperger, F., Seel, C. (2019). The SenSoMod-Modeler – A Model-Driven Architecture Approach for Mobile Context-Aware Business Applications. In: Cappiello, C., Ruiz, M. (eds) Information Systems Engineering in Responsible Information Systems. CAiSE 2019. Lecture Notes in Business Information Processing, vol 350. Springer, Cham. https://doi.org/10.1007/978-3-030-21297-1_7
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