Our project offers a big data marketplace as “One-Stop-Shop” to data customers who want to tap into the enormous opportunity that arises from collecting data from various cross-sectorial CPPs. 

In the Big Data Marketplace data customers have the possibility to filter their desired data from Cyber Physical Products (CPP) exactly to their needs. With the Context Monitoring & Extraction Framework we will introduce an additional useful way to pre-filter the huge amount of data with respect to the current context of each CPP.

 

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Context based suggestions

For modern vehicles mobile sensor networks can produce over 4000 signals per second per vehicle. Imagine if this raw sensor data comes with additional information, such as the circumstances under which the data has been collected, or the factors that can influence the sensor measurements that are being observed from vehicles. We are using an ontology model in the background to model the complex relationships between the different sensor measurement types in the CPPs which is the baseline for our knowledge network to extract the context out of. Based on the user’s current interest we then query this model, i.e. what kind of sensor signals should be recommended to him/her and which can additionally be chosen from and added to the individual choice of signals. Within Cross-CPP we offer this service for CPPs of the types vehicle and smart building.

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