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Machine Vision Recycling System | Cities | Envisioning
  1. Home
  2. Research
  3. Cities
  4. Machine Vision Recycling System

Machine Vision Recycling System

This solution addresses inefficient urban waste management, which often leads to increased landfill use, pollution, and high operational costs. This technology leverages advanced image recognition and artificial intelligence to accurately identify and sort recyclable materials from waste streams. By automating the sorting process, these systems reduce contamination, enhance recycling rates, and lower the dependency on manual labour.

Related Organizations

AMP logo
AMP

US · Startup

98%

Applies AI and robotics to modernize recycling infrastructure.

Developer
TOMRA logo

TOMRA

NO · Company

95%

Provides sensor-based sorting solutions for the food, recycling, and mining industries.

Developer
ZenRobotics

FI · Company

95%

A supplier of AI-based robotic waste sorting systems, now part of Terex.

Developer

Supporting Evidence

Article

More efficient recycling with AI: Joint project develops automated sorting solution for bulky waste

DFKI (German Research Center for Artificial Intelligence) · Jun 15, 2025

The SmartRecycling-Up project, led by DFKI, developed an AI-based concept that automates the sorting of bulky and construction waste using cranes or excavators equipped with intelligent sensors.

Support 90%Confidence 95%

News

More efficient recycling with AI: Joint project develops automated sorting solution for bulky waste

DFKI (German Research Center for Artificial Intelligence) · Jun 15, 2025

The SmartRecycling-Up project, led by DFKI, has developed an AI-based concept that automates the sorting of bulky and construction waste using cranes and intelligent sensors, successfully tested at the ASO GmbH facility.

Support 90%Confidence 95%

Article

Automatic Eyes of the Sorting Plant – How Computer Vision Supports Recycling

xBerry · Nov 24, 2025

Discusses the role of Computer Vision as the 'automatic eyes' of sorting plants, enabling faster and more accurate waste classification than manual labor, driven by EU circular economy regulations.

Same technology in other hubs

Horizons
Horizons
Machine Vision Recycling System

AI and robotics automating waste sorting and material recovery.

Connections

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GXJauPRaSeG77TPJH4DieQ
Autonomous Sustainability Monitoring

This solution addresses urban challenges such as pollution, resource inefficiency, and disaster management. It integrates a network of sensors, artificial intelligence (AI), and data analytics to continuously track and manage environmental parameters like air and water quality, energy consumption, and waste management in real-time. By providing accurate, actionable data, these systems help city planners and policymakers design better sustainability strategies, enhancing urban living conditions and reducing environmental impacts.

Technology Readiness Level
6/9
Diffusion of Innovation
2/5

Explore this signal in your context

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BACK TO CITIESVIEW INTERACTIVE VERSION
Greyparrot logo
Greyparrot

GB · Startup

92%

Provides AI waste analytics to monitor and audit waste flows.

Developer
Recycleye

GB · Startup

92%

Brings advanced machine learning, computer vision, and robotics to the waste management industry.

Developer
EverestLabs

US · Startup

90%

Develops RecycleOS, an AI operating system for recycling plants.

Developer
Pellenc ST

FR · Company

90%

Manufacturer of intelligent optical sorting equipment for waste treatment.

Developer

CleanRobotics

US · Startup

88%

Creator of TrashBot, a smart waste bin that uses AI and computer vision to sort waste at the point of disposal.

Developer
Bin-e

PL · Startup

85%

An IoT smart waste bin that automatically recognizes, sorts, and compresses waste using AI-based object recognition.

Developer
Support 80%
Confidence 88%

Article

How AI Is Transforming Waste Management

Global Trash Solutions · May 1, 2025

Discusses the broader impact of AI in waste management, including robots and sensors for sorting recyclables with high accuracy and optimizing collection routes.

Support 80%Confidence 88%
Technology Life Cycle
1/4

Traditional recycling methods often suffer from inefficiencies, contamination, and high operational costs. The introduction of Machine Vision Recycling Systems (MVRS) offers a transformative solution to these problems, heralding a new era in urban waste management.

A machine vision recycling system utilises computer vision to identify and sort recyclable materials. This system operates through high-resolution cameras and sophisticated algorithms that can distinguish between different types of waste with remarkable accuracy. As waste moves along a conveyor belt, the machine vision system scans and categorises each item, directing it into the appropriate recycling stream. This process significantly reduces contamination and increases the purity of recyclable materials, enhancing the overall efficiency of recycling operations.

By automating the sorting process, MVRS reduces the reliance on manual labour, which is often prone to errors, accidents and inefficiencies. It also enables cities to handle larger volumes of waste without proportionally increasing costs or resource use. Moreover, the precision of machine vision ensures that more materials are correctly recycled, thereby reducing the environmental impact of waste and promoting sustainable urban living.

Another critical aspect of machine vision recycling systems is their adaptability. These systems can be programmed to recognise a wide variety of materials, from plastics and metals to paper and glass, making them versatile and highly effective. Additionally, continuous improvements in AI and machine learning mean that these systems can evolve and become more efficient over time, further enhancing their contribution to urban sustainability.

Technology Readiness Level
6/9Prototype Testing
Diffusion of Innovation
3/5Early Majority
Technology Life Cycle
2/4Growth
Category
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