AI video surveillance in public spaces

Detection of vandalism, illegal dumping, and smoke and fire in real time

How AI video surveillance supports city operations in public spaces?

Tens of thousands of cases of illegal dumping, millions in costs caused by vandalism and fires—often recognized far too late—show a structural problem in cities. It’s not that there are no cameras; it’s that there’s no real-time detection. AI video surveillance in public spaces addresses exactly this by identifying anomalies at the moment they occur, thereby reducing damage and enabling rapid responses.

What is detected?

AI video surveillance in public spaces clearly detects well-defined incidents that cause damage, increase risks, or require rapid intervention.

Damages to infrastructure

Graffiti detection
Damage to bus stops, facades, or vending machines
Unusual actions at sensitive objects such as power cabinets

Illegal dumping

Illegal dumping on roads, parking lots, or green spaces
Recurring disposal at known problem areas

Smoke and Fire

Detect early smoke development
Identify open flames in the camera image

Detect environmental changes

Changes such as pollution, overturned objects, or blocked pathways
Events such as flooding or other exceptional changes in conditions

How does AI video surveillance work in public spaces?

The detection of vandalism, illegal dumping, or changes in the environment is based on specialized AI analyses that work directly on the camera image. Two central methods are used in particular: smoke and fire detection, as well as the analysis of changes in the scene image, also referred to as a scene change.

What happens after detection?

Detected changes are not only visualized, but directly translated into concrete measures. In critical conditions, real-time notifications are sent and immediately forwarded to the control room or the responsible maintenance teams. At the same time, all events are documented, enabling a continuous analysis and traceability without gaps. Based on historical data, processes can also be continuously optimized and future risks can be identified early.

Alarm

Verification

Reaction

Documentation

What benefits arise for cities?

The use of AI-supported video analytics for machine and process monitoring offers companies not only greater transparency, but above all measurable operational and economic benefits. Rather than reacting to disruptions, it creates a system that actively supports processes, reduces risks, and sustainably increases efficiency.

Reduce damage instead of removing it

Vandalism, illegal dumping, and fires cause high costs every year for cleaning, repairs, and maintenance. With early detection, cities can intervene before damage occurs or spreads. This not only reduces direct costs, but also prevents recurring issues at known hotspots.

React faster with real-time information

As soon as an event is detected, relevant information is immediately available. Response teams know where something is happening, what exactly is happening, and can react in a targeted way. This shortens response times and increases the efficiency of municipal works yards, public order services, and emergency responders.

Actively manage public spaces

Through continuous analysis, cities can identify early where problems are emerging and how they are developing. Resources can be deployed where they are actually needed, deployments can be prioritized, and measures can be implemented directly on the ground. Instead of reacting sporadically, active management of public spaces is created.

Create transparency and traceability

All detected events are systematically recorded and documented. This creates reliable data for analysis, reports, and strategic decisions. Measures can be justified, developments can be traced, and long-term planning can be made based on solid information.

AI video surveillance in public spaces not only detects damage and changes

In addition to detecting damage, fire incidents, and changes in condition, AI video surveillance in public spaces opens up further operational areas of application. These include analyzing traffic flows, detecting traffic offenses, and gaining early insight into crowds and critical dynamics in public spaces.