In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between experienced and novice rowers, or between a good and a bad technique. The analysis shows that the measured postural angles show no clear trend that would set apart experienced and novice rowers or a bad and a good technique. However, there are clear differences in absolute postural angle's consistency and timing consistency of strokes between novice and experienced rowers. We also applied a machine learning technique to the data to find the similarities between different rowers and an experienced reference rower. The results can be used to compare the quality of the rowing technique with respect to a reference. In this paper, we present our initial results as well as the challenges that need to be further explored.

IoT applications and other distributed control applications are characterized by the interaction of many hardware and software components. The inherent complexity of the distributed functionality introduces challenges on the detection and correction of issues related to functionality or performance, which are only possible to do after system prototypes or pilot installations have been built. Correcting these issues is typically very expensive, which could have been avoided by earlier detection. This paper makes four main contributions. (1) It presents a virtual prototyping approach to specify and analyze distributed control applications. The approach is based on a domain model, which can be configured for a specific application. It consists of eight domainspecific languages (DSLs), each describing one system aspect.(2) The DSLs provide each stakeholder in the application's lifecycle a natural and comprehensible way to describe his/her concerns in an unambiguous manner.(3) The paper shows how the DSLs are used to automatically detect common configuration errors and erroneous behavior. (4) The virtual prototyping approach is demonstrated using a lighting domain case study, in which the control system of an office floor is specified and analyzed.

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