Identify whether classroom lights are on using AI

Below is a free classifier to identify whether classroom lights are on. Just upload your image, and our AI will predict if the classroom lights are on - in just seconds.

whether classroom lights are on identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("whether-classroom-lights-are-on-identifier", "your_image_url", credentials)
            

fetch('https://www.nyckel.com/v1/functions/whether-classroom-lights-are-on-identifier/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/whether-classroom-lights-are-on-identifier/invoke
            

How this classifier works

To start, upload your image. Our AI tool will then predict if the classroom lights are on.

This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Lights On and Lights Off.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if the classroom lights are on).

Whether you're just curious or building whether classroom lights are on detection into your application, we hope our classifier proves helpful.

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Need to identify whether classroom lights are on at scale?

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



  • Smart Energy Management: This use case focuses on optimizing energy consumption in educational institutions by automatically monitoring classroom lighting. The system can identify if the lights are on or off, enabling automated energy-saving measures when classrooms are unoccupied.

  • Classroom Utilization Analytics: Educational administrators can analyze classroom usage patterns by tracking when lights are activated. This information can help optimize scheduling, ensuring that classrooms are utilized efficiently based on demand.

  • Security Monitoring: The binary classification function can be integrated into a security system to detect unauthorized access or activities in classrooms. If lights are turned on after hours, alerts can be generated to notify security personnel.

  • Remote Learning Assistance: In a hybrid learning environment, this function can simplify the setup for teachers and students attending classes remotely. The system can check whether classroom lights are on, indicating whether the classroom is active and ready for participants to join.

  • Maintenance Notifications: By monitoring classroom lighting, the system can notify maintenance staff when lights are left on for extended periods. This helps in reducing energy wastage and ensuring that maintenance is conducted timely to replace malfunctioning lighting.

  • Interactive Learning Environment: The system can be integrated with an interactive classroom technology solution to create a more engaging learning experience. For instance, if lights are detected to be on, it can trigger multimedia presentations or other interactive tools to enhance teaching.

  • Automated Feedback to Educators: Educators can receive automated insights on their classroom management practices. They can be informed, for example, when classes tend to leave lights on for prolonged periods, prompting discussions on energy saving and classroom habits.

Want this classifier for your business?

In just minutes you can automate a manual process or validate your proof-of-concept.

Get Access