Huge amount of data
Data are input or output data managed in a digital information system. We as Datacadabra collect data in different types and sizes. Here you can think of different types. Consider, for example, the MowHawk, a camera system installed on a roadside mower. This solution brings in data, about locations, times and observed objects, for example.
If you have all these data separately, they may not be very interesting. This is the case: if you only know what object has been spotted, but do not know where, then it is not relevant information. As soon as you know where the object has been spotted, it becomes interesting. We structure data in such a way that relationships can be derived. For example, object X is very often seen at location Y. We can then link conclusions and actions to it.
Secure and privacy-proof
The most important thing when working with data is to handle it securely. Storing data is not always allowed, especially if it is privacy-sensitive. Datacadabra only stores data from which no personal data can be derived. In the case of images, we will always cut out and remove parts with people or cars.
Handling data responsibly is what Datacadabra stands for!
Responsible data handling in practice
As you may have read earlier, we are currently developing the Luistervinq. The Listenervinq is a privacy-proof solution that can be placed in various places in public spaces. It pulls in data based on audio devices and AI algorithms. This data is converted into information and thus the sports use of that specific spot can be monitored. In this way, the presence as well as the classification of use (is cycling or walking) can be determined.
Of course, the Luistervinq is completely privacy-proof, for we do not listen to what people say. The area of sound that contains speech is rendered unrecognizable. This happens not only at the final product, but also at any intermediate steps. Also, we make sure that the audio is not stored, but only passed on in absolute counts.
