> ## Documentation Index
> Fetch the complete documentation index at: https://landinglens.docs.landing.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Detect Bird Nests on Transmission Towers with LandingLens

export const vp = 'Visual Prompting';

export const smartLabel = 'Smart Labeling';

export const productLL = 'LandingLens';

export const mi = 'Mobile Inference';

export const llsf = 'LandingLens on Snowflake';

export const companyName = 'LandingAI';

*This article applies to these versions of LandingLens:*

<table>
  <thead>
    <tr>
      <th>LandingLens</th>
      <th>LandingLens on Snowflake</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td><span class="check-icon">✓</span></td>
      <td><span class="check-icon">✓</span></td>
    </tr>
  </tbody>
</table>

<iframe width="560" height="315" src="https://www.youtube.com/embed/zDo0zThcjxw??si=5OeVyic87RNq2dTr&wmode=opaque&rel=0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen />

Detecting bird nests on transmission lines is a critical task for utilities, as these nests can pose significant risks to the safety and reliability of the electrical grid. Traditional methods of manual inspection are time-consuming, labor-intensive, and often hazardous.

LandingLens from LandingAI makes it super easy for utilities to leverage computer vision and machine learning to automate the detection of bird nests. This product demonstration shows how a non-technical user can develop a visual AI solution in as little as an afternoon.