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The goal is to create an IT environment for the integration and analysis of data streams originating from mass-produced products with cyber-physical characteristics as well as from open data sources. In doing so, new cross-sector services will be offered, with a focus on commercial confidentiality, privacy and intellectual property rights protection, and ethical issues, using a context-sensitive approach. The project addresses cross-stream big data analysis of mass-produced cyber-physical products (CPPs) from various industries such as automotive and home automation. The business objective of the research is to enable the analysis of such data streams in combination with other (non-industrial, open) data streams and to establish various improved sectoral and cross-sectoral services. The project will develop the following: (i) New models for the integration and analysis of data streams originating from cross-sector CPPs, including common systems of entity identifiers applicable to cross-sector CPPs (as well as the definition of agreed data models for data streams from multiple CPPs with the goal of a defacto standard; (ii) ecosystem, including a common marketplace and methodology for leveraging such models to build cross-sector cloud-based services; (iii) toolbox for real-time and predictive cross-stream analytics, context modeling and extraction, and dynamically changing conditions/rules for security policy, privacy, and intellectual property rights; and (iv) a set of services, e.g. e.g., services based on a combination of data streams from home automation and (electric) vehicles to enable improved local weather forecasting and predict and optimize energy consumption in households. The project will build on the results of previous and ongoing projects, using the results of the AutoMat project, which deals with services developed based on data streams from vehicles, as a basis for further development to extend it to integrated, cross-sector analysis of data streams.

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