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title = 'Benefits of CircularNet'
date = 2024-07-30T17:02:23Z
draft = true
weight = 2
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The following table describes some of the benefits of using CircularNet as your automated tool for waste identification:

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<table>
  <thead>
    <tr>
      <th colspan="2"><strong>CircularNet benefits</strong></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td class="color">Cost optimization</td>
      <td><ul>
<li><strong>No upfront costs:</strong> Access free, open-source models and code, eliminating the need for expensive software licenses or proprietary solutions.</li>
</ul>
<ul>
<li><strong>Reduced labor expenses:</strong> Minimize the need for manual material identification and sorting, freeing up personnel for other critical tasks and reducing labor costs.</li>
</ul>
<ul>
<li><strong>Pay-as-you-go flexibility:</strong> Leverage cloud-based deployment options to pay only for the computing resources you use, scaling up or down as needed without investing in dedicated hardware.</li>
</ul>
<ul>
<li><strong>Accelerated implementation:</strong> Jumpstart your AI-powered waste analysis initiatives with pre-trained models and avoid the time and expense of collecting and annotating large datasets.</li>
</ul>
<ul>
<li><strong>Adaptable to your needs:</strong> Fine-tune the pre-trained models on your own data to further improve accuracy and tailor the solution to your specific waste stream characteristics.</li>
</ul>
</td>
    </tr>
    <tr>
      <td class="color">Automation</td>
      <td><ul>
<li><strong>Uninterrupted waste analysis:</strong> Capture and analyze images of waste streams continuously during operating hours, enabling consistent monitoring and identification of materials without manual intervention.</li>
</ul>
<ul>
<li><strong>Visualized insights:</strong> Access a simple and user-friendly dashboard to visualize and analyze data in real-time or in aggregate, empowering decision-making and proactive process adjustments.</li>
</ul>
<ul>
<li><strong>Streamlined operations:</strong> Reduce the need for manual labor in material identification and sorting, leading to increased operational efficiency and lower labor costs.</li>
</ul>
<ul>
<li><strong>Minimized errors:</strong> Eliminate human errors associated with manual sorting, resulting in more accurate waste characterization and improved recycling outcomes.</li>
</ul>
<ul>
<li><strong>Automated reporting:</strong> Generate detailed, customizable reports on material composition and contamination levels, saving time and effort compared to manual reporting methods.</li>
</ul>
</td>
    </tr>
    <tr>
      <td class="color">Residual analysis</td>
      <td><ul>
<li><strong>Realize lost value:</strong> Reduce and quantify recyclables sent for disposal through precise material identification.</li>
</ul>
<ul>
<li><strong>Optimize bale quality:</strong> Accurately assess the composition and purity of materials on the baling line to ensure they meet market demands and command higher prices.</li>
</ul>
<ul>
<li><strong>Pinpoint contamination sources:</strong> Identify and track contaminants within the waste stream to identify their sources and take corrective action to improve sorting processes and reduce contamination.</li>
</ul>
</td>
    </tr>
  </tbody>
</table>

## Use cases for CircularNet

While you can deploy the fundamental technology underpinning CircularNet in various areas across the waste management ecosystem, CircularNet has been trained on and designed for deployment in material recovery facilities (MRFs) and recycling facilities. Typical users include MRF and recycling operators, technology integrators, system and machine learning engineers, and academic researchers. Examples of solutions you can implement through CircularNet include:

-  Bale quality analysis
-  Residual line analytics
-  Identification of recyclable materials and contaminants in mixed waste streams
-  Recycling and contamination reporting in MRF facilities

For case studies by industry and application, refer to the following external articles:

-  [CircularNet: How Recykal built Asia's largest circular economy marketplace using Google AI](https://sustainability.google/operating-sustainably/stories/circular-economy-marketplace/)
-  [CircularNet: Reducing waste with Machine Learning](https://blog.tensorflow.org/2022/10/circularnet-reducing-waste-with-machine.html)