AI-driven litter intelligence for cities

Streetwizer helps cities tackle litter faster, smarter and more effectively—using smartphone photos and advanced AI analysis. Our method turns what’s visible on the street into actionable data for policy, operations and long-term solutions.

Photo-driven litter research

From street to strategy

Streetwizer measures litter in a radically different way.
Instead of subjective estimations as in the CROW method or small samples, we use photography and a replicable research protocol and let AI do the photo-analysis.

The result:

– faster and cheaper measurements
– far more complete insights than traditional methods
– data that actually supports evidence-based policy

Cities using this approach have already reduced litter by more than 50%.

Our AI model is trained on the world’s most detailed litter dataset:

ten years of systematically tagged photos collected by Dirk Groot (Zwerfinator)—unique in scale, precision and continuity. Merijn Tinga (Plastic Soup Surfer) has been working in the field of litter and policy for over ten years and has been the driver behind the introduction of Deposit Return in the Netherlands. Together Groot and Tinga have great experience in the field of litter and policy.

How it works

Simple. Scalable. Ready in one day.

Streetwizer research can be carried out by our team, or by municipal staff trained in a one-day certification. Anyone with a smartphone can apply the method.

Together with the city we define fixed survey routes (±25 km), covering:
shopping streets

– residential areas
– business parks
– public transport hubs
– recreational areas
– waterways

These routes are surveyed three times per year to capture seasonal effects and long-term trends.

During each survey, researchers:

– photograph all visible litter using a clear protocol
– photograph public bins (including fill level)
– record disruptions such as side waste or overflowing bins

Our AI then analyses every image for:

– material type
– packaging type
– brand
– category
– geolocation

This creates a complete, reproducible dataset of what is happening in public space.

What you get

Clear insights, concrete action

Streetwizer translates data into practical reports, including:

– litter per kilometer and per area type
– trends over time
– most common materials and packaging
– hotspots and structural patterns
– recommendations for local measures and long-term policy

This goes far beyond traditional manual counts—because decisions are based on thousands of data points, not assumptions.

What the data does for your city

Identify blind spots

Discover where litter consistently accumulates—often outside current cleaning routes. Shift from reactive to proactive cleaning.

Optimize bin placement

See where bins are missing, redundant or ineffective, and measure whether changes actually work.

Trace litter back to its source

Packaging and brand recognition reveal which products and sectors contribute most. This enables:

– evidence-based conversations with businesses
– concrete agreements
– monitoring of impact over time

Work smarter with volunteers

Data shows where help is most needed, helps coordinate efforts, and makes impact visible and measurable.

Together, these insights turn litter policy from guesswork into accountable, data-driven action—saving time, money and frustration.

Working with cities

A pilot approach that scales

Streetwizer works with cities to run pilot projects that demonstrate real-world impact. Research in both small and large cities shows that litter patterns are remarkably consistent—meaning insights from one pilot are widely applicable.

A pilot allows cities to:

– test targeted interventions
– improve bin strategies and awareness campaigns
– see concrete results on the ground
– build a scalable model for city-wide rollout

Results can also support the case for structural solutions, such as Deposit Return Schemes, which address a large share of litter at its source.

Who are we

Merijn Tinga – Plastic Soup Surfer
Environmental campaigner with over 10 years of experience using expeditions and storytelling to drive systemic change with businesses and policymakers.

Dirk Groot – Zwerfinator
Litter researcher with over 10 years of photographic documentation. Developer of an AI litter detection model trained on nearly one million tagged images.

Together, as Streetwizer, we combine activism, science and AI to help cities understand litter—and actually reduce it.