Makes visitor flows at hotspots easy to read and proposes measures to manage them, including a public transport alternative.
Developed in Germany · Hosted in the EU or on-premises
Delivered together with
Sovereign hosting in Germany, single-tenant from the first user.
Legal, tax and compliance expertise for legally sound deployment.
Advisory and implementation for the public sector, starting with the AI readiness assessment.
At the hotspot, cars are double-parked, the counting station records the peak, and nobody sees the two together. Whoever has to explain the situation afterwards opens the count data, timetable and map one at a time and does the sums by hand.
One Sunday, three departments, the same three sources, and the reply to the council contains not one hourly figure backed by data. The 35% reduction in overload days from the data sheet assumes that the recurring pattern is analysed once, stored on the map and still retrievable there three weeks later.
This sequence describes a typical weekend at a hotspot. The percentage comes from the headline figure in the data sheet, not from this worked example.
The agent reads the count series from the hotspot counting stations and overlays the timetable data of the lines serving the area. It marks the hours in which the count is above the weekly average and no extra service is scheduled.
Count series hotspot_a3_kw28.csv with 168 hourly values, 4 lines within 800 metresThe agent transfers the peak hours to the hotspots and car parks in the GIS. For each area it shows the hour at which capacity was exceeded.
GIS layer besucherlenkung_kw28 with 6 hotspots and 3 car parksThe agent keeps measured values and recommendations in separate sections. For every proposal it names the public transport alternative with departure time and the count series behind it.
Draft lenkungsvorschlag_kw28.docx, 2 pages, measured values and recommendations shown separatelyClosures, diversions and parking bans are signed off by the road traffic authority. The agent supplies the hourly values the order can rest on.
It describes measured load and recurring patterns. It does not issue a prediction for a particular Sunday.
It works with the series from the counting stations and the timetable data of the lines serving the area. A parking strip with no counting station stays blank on the map, even if cars are double-parked there on a Sunday.
Connected systems
Operations
A pilot typically runs on your own data within 4 to 6 weeks. The agent connects to your existing systems rather than running as a separate, parallel environment.
EU cloud, private cloud or on-premises. Processing is GDPR-compliant and models are never trained on your data. Details in the Trust Center.
It is based on experience from comparable projects and process benchmarks, not a commitment. We work out the realistic effect for your organisation during the assessment before the pilot.