Identify energy efficiency level using AI

Below is a free classifier to identify energy efficiency level. Just upload your image, and our AI will predict the energy efficiency level of a building. - in just seconds.

energy efficiency level identifier

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    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("energy-efficiency-level", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/energy-efficiency-level/invoke', {
        method: 'POST',
        headers: {
            'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
            'Content-Type': 'application/json',
        },
        body: JSON.stringify(
            {"data": "your_image_url"}
        )
    })
    .then(response => response.json())
    .then(data => console.log(data));
                

    curl -X POST \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
        -d '{"data": "your_image_url"}' \
        https://www.nyckel.com/v1/functions/energy-efficiency-level/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the energy efficiency level of a building..

This pretrained image model uses a Nyckel-created dataset and has 7 labels, including Above Average, Average, Below Average, High, Poor, Very High and Very Poor.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the energy efficiency level of a building.).

Whether you're just curious or building energy efficiency level detection into your application, we hope our classifier proves helpful.

Need to identify energy efficiency level at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Energy Consumption Monitoring: This use case focuses on residential and commercial buildings using false image classification to assess energy efficiency levels through visual analysis of utility meters and appliances. By identifying energy use patterns, property managers can optimize energy consumption, reduce costs, and improve sustainability efforts.

  • Appliance Testing and Certification: Appliance manufacturers can employ false image classification to analyze the energy efficiency of their products visually. This assists in certifying appliances based on energy consumption standards and providing consumers with accurate information on energy use, driving informed purchasing decisions.

  • Smart Home Automation: Integration of false image classification in smart home systems allows for improved energy management by identifying inefficient appliances or systems. Homeowners can receive real-time alerts and recommendations for energy-saving actions, enhancing both comfort and cost-effectiveness.

  • Building Retrofits and Renovations: Construction firms can utilize false image classification to evaluate the energy efficiency of existing buildings during renovation projects. By visualizing structural components through aerial imagery or detailed scans, firms can identify areas for improvement, ultimately leading to better energy performance and value.

  • Energy Auditing Services: Energy auditors can leverage false image classification to enhance traditional auditing methods. By analyzing building images, auditors can pinpoint energy loss areas and provide precise recommendations for improvement, leading to more efficient energy use in commercial and residential spaces.

  • Urban Planning and Development: City planners can use false image classification to assess the energy efficiency of neighborhoods through aerial imagery analysis. This data helps in making informed decisions about infrastructure development, zoning policies, and sustainability initiatives aimed at improving urban energy performance.

  • Marketing for Energy-Efficient Products: Companies that produce energy-efficient products can utilize false image classification to create compelling visual content. By classifying and showcasing products based on energy efficiency levels, businesses can better target environmentally conscious consumers, enhancing their marketability and sales potential.

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