TrashVision

the smart way to compliance

TrashVision^™

Helping your city achieve compliance

TrashVision™ is an innovative, AI-driven solution that helps cities address the impact of trash on surface water quality and meet compliance for the 2030 state deadline which establishes an enforceable statewide goal to prevent trash greater than 5mm from reaching ocean waters, bays, or local waterways.

Read Our Peer-Reviewed Paper

Policy

History

In 2015, the State Water Resources Control Board (SWRCB) adopted the Trash Amendments or Trash Provisions. This policy sets an enforceable statewide goal to prevent trash greater than 5mm from reaching ocean waters, bays, or local waterways by 2030.

Why do you need TrashVision™?

It’s Rapid & Repeatable

Fully understand the level of trash within your city in as little as two weeks

Streamlined Efficiency

TrashVision™ requires fewer man hours compared to OVTA

Accurate Results

TrashVision™ removes human subjectivity for a non-biased report

What TrashVision™ gives you…

Expert Oversight

You’ll get on-going expert oversight and experience from our TrashVision™ team

Graded Street Maps

You’ll receive a graded and color-coded map of driven street segments

Peace of Mind

You’ll have peace of mind knowing your city is in full compliance

The TrashVision™ Process

Step 1

Planning

Streets are planned out in GIS based on what needs to be surveyed. For example; needing to look at all streets around priority land use areas.

Step 2

Data Acquisition

High resolution images of the predetermined street segment are captured by the car-mounted camera – about 40 captured for a standard 200m segment.

Step 3

Data Processing

Images are geotagged, sorted by street segment, then processed through TrashVision™ AI model to determine the amount of trash in each photo.

Step 4

Quality Control

A quality control step is implemented to remove any detections by the model that are not trash, such as manholes, construction cones, etc.

Results you can rely on

Color Graded Report

Once all the data has been collected and images have been processed, TrashVision™ will produce a color-coded map of your city’s street segments along with their grade.

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“The recent proliferation of deep learning tools, datasets, and trash identification algorithms can help cities bridge the gap between sustainability frameworks and smart technologies leading to smart sustainable cities.”

Computers, Environment and Urban Systems, 2021

Meet Our Experts

Ian AdamVP, Specialty Services

Howard WenSenior Project Manager

Taylor HansonAssociate Project Manager

Cameron CastilloStormwater Specialist