Smart Parking Ravensburg
Sometimes, it’s easier to recognize the benefit of something once you can really picture it. So, here’s a fictional tour of the smart parking potential in Ravensburg, a city where we believe our tech can make a difference.
Ravensburg's Smart City Vision
On this page, we’d like to showcase how multi-use and camera-based sensors can serve the busiest areas of Ravensburg best. To demonstrate this, we’re looking at the area around Ravensburg’s main train station - an area which, like in most cities, is choc-o-bloc with cars, taxis, and buses. With our services, Ravensburg could alleviate traffic and thereby air pollution, as well as the frustration of drivers.
Want to know more about how we ensure privacy? Click here ->
What more could Ravensburg do?
At SONAH, we use camera-based sensors. This enables us to offer certain services - and multiple services at once - to cities. You can have a look through all of these by clicking on the map below.
What's At Stake In Ravensburg?
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Better Air Quality
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Safer Streets
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Happier Residents
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Less Parking Traffic
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High Return on Investment
Use Case 1: Single Parking Spot Detection
Our camera-based sensors are capable of detecting both marked and unmarked single spots at the same time. Just outside of Ravensburg’s main train station, both are in close proximity to one another and of course, there are street lamps within the same area. That solves two things: a high mounting point for optimum vision and a 24/7 power supply. It’s perhaps worth mentioning that even where the lamp posts are not able to be used as power supplies, batteries can fit well.
Read the following URBAN LEGEND to hear about how the city of Wuppertal used batteries in their solution.
We can also install solar-powered autarq systems. But no matter the system, the 24/7 power supply is needed in order to transfer live data via APIs to both operator and end-user frontends. More on that below.
Use Case 2: Multiple Parking Spot Detection
As well as single spot detection, we also offer counting systems. It’s the same sensor for both, so the points above are the same here regarding installation. But how is it relevant in Ravensburg?
Smart parking counting systems are used for counting cars in and out of one area. In Ravensburg, an installation of smart parking sensors at the entrance of some public parking areas would allow city administrators to know which car parks are full, when. This knowledge, shared with citizens via a parking guidance management system, would contribute to clearing the streets of parking search traffic. In essence, it simply makes parking decision-making infinitely easier.
Knowing there’s a certainty of finding paid parking within 2 minutes walk of the train station, you may avoid a 15 minute cruise around Ravensburg’s streets looking for a free spot. A simple solution for the driver, and the city benefits directly via payments and indirectly via the reduction in blocked roads, traffic, and parking violations.
Use Case 3: Parking Guidance Systems
As hinted at above, a lot of the benefits come from how live data is used. For parking lots/multi storey car parks, a parking guidance system can be LED/LCD signs that display information such as where or how many spots are to be found. With onground sensors or our single spot detection, the occupancy of specific areas can also be displayed.
Alternatively, digital parking guidance systems on mobile apps could be perfect for Ravensburg. By setting up the API and transferring the live data to a citizen-facing platform, drivers can make informed decisions, reduce parking search time, and save on fuel (and thereby, emissions!).
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This page is made by SONAH to demonstrate how our products could add value in real-life scenarios. They are not implemented projects nor is this page connected with the city of Ravensburg administration; we simply chose to highlight Ravensburg due to its innovative reputation.
Camera-based Sensors: Maintaining Privacy in a Residential Area
These are camera-based sensors - not CCTV cameras. They digitise parking spaces from above to generate live occupancy data, and, unless programmed to perform other tasks, that's it. No personal data collection.
How can the system be compliant with the GDPR?
STEP 1: The computers in the sensor get an image, blocking out all irrelevant parts first.
STEP 2: The detection process takes place in the computer of the sensor itself.
STEP 3: This means that no images are stored or sent to third party systems.
STEP 4: Occupancy data alone is communicated i.e. '90% of all parking spaces are occupied'.
No personal data is created, therefore NO personal data can be stored, processed or sent.