Data4Mobility: Summarizing Secure Parking

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This week we want to summarize our idea “Secure Parking”. We also want to analyse the feedback we got and also give a view on what comes next.

Our idea “Secure Parking” is based on Bosch Secure Truck Parking. The main difference is that cars have a lot more spots to park and we do not want to create separated car parks or car lots. Our idea is to analyse police and insurance data about burglary and thefts and create a grid to determine if an area is secure or not. As feedback we received that police might not be allowed to give us the needed information and a crime database of Chicago was mentioned. We were able to find this kind of database actually for the whole US and Canada. In the Screenshot you see a part of the map for Chicago.

We could also create a map like this. The Bundeskriminalamt probably also has useful information for us, as there are statistics online available grouped by federal states. Maybe they have more detailed information which is allowed to be published if we ask. Analysing the data and creating a grid will be done with analytical methods. With this information, the knowledge where the car is actually stated and where the driver wants to go we can suggest a secure area to park at the destination point. It will also be possible to show if the current position is secure to park or not, if the driver did not insert a destination to the navigation system. This way we can try to prevent burglaries by routing the drivers to secure parking areas.

For the future we have to think about how to analyse the data exactly. We did not yet think about the value of the data during time. For example, if a burglary five years ago has the same impact making an area unsafe than a burglary just one week ago. We also have to think about where to get the latest data from and how to join old and new data. In the feedback we were also suggested to open our service to other occasions which could harm the car. For example including weather forecasts to prevent the car from damage by hailstorms.


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