Abstract
In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.
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Acknowledgements
This work was supported by the European Union from the FP7-PEOPLE-2013-IAPP AutoUniMo project “Automotive Production Engineering Unified Perspective based on Data Mining Methods and Virtual Factory Model” (grant agreement no: 612207) and research work financed from funds for science in years 2016–2017 allocated to an international co-financed project (grant agreement no: 3491/7.PR/15/2016/2) and supported by Polish Ministry of Science and Higher Education with subsidy for maintaining research potential.
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Drewniak, M., Tokarz, K., Rędziński, M. (2017). ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_22
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