Identify passenger mood analysis
using AI
Below is a free classifier to identify passenger mood analysis. Just upload your image, and our AI will predict the mood of passengers. - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("passenger-mood-analysis", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/passenger-mood-analysis/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/passenger-mood-analysis/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the mood of passengers..
This pretrained image model uses a Nyckel-created dataset and has 12 labels, including Anxious, Bored, Content, Excited, Frustrated, Happy, Neutral, Optimistic, Overwhelmed and Pessimistic.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the mood of passengers.).
Whether you're just curious or building passenger mood analysis detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify passenger mood analysis at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- In-Flight Service Optimization: Airlines can use passenger mood analysis to optimize in-flight services. By understanding the overall mood of passengers, flight attendants can tailor their interactions and services, enhancing customer satisfaction and potentially increasing on-board sales.
- Real-Time Mood Monitoring: Passenger mood analysis can provide real-time insights during flights, allowing airlines to address negative moods promptly. This proactive approach can help mitigate issues before they escalate, ensuring a more pleasant flight experience for everyone on board.
- Targeted Advertising and Promotions: By analyzing passenger moods, airlines can create targeted advertising campaigns and promotions that resonate with travelers. For instance, if passengers appear anxious, airlines could offer relaxation packages or entertainment options tailored to improve their experience.
- Feedback Improvement: Integrating mood analysis with feedback mechanisms can help airlines better understand customer satisfaction. By correlating mood data to feedback, airlines can identify specific pain points and address them in future services or policies.
- Loyalty Program Enhancement: Airlines can analyze mood trends related to loyalty program members during flights. Tailoring rewards or messaging based on passengers' moods can increase engagement and foster stronger loyalty, ultimately leading to higher retention rates.
- Crisis Management and Evacuation Procedures: Implementing mood analysis can aid in managing emergency situations more effectively. Understanding passenger anxiety levels can guide crew decisions in crisis scenarios, helping them to maintain calm and facilitate orderly evacuations.
- Personalized Travel Experience: Airlines can leverage mood analysis to offer personalized travel experiences, enhancing customer comfort. By predicting mood changes and recommending related services, such as meal options or entertainment choices aligned with the current ambiance, airlines can create a unique flying experience tailored to each passenger.