GateReady

• 

  Landing Page - Day's Flight Booking, Start Trip and track time to the airport gate

• 

  Timeline Page - Real Time update of TSA, Arrival Time, Check-In, Walk Time to Gate predictions

• 

  Timeline Page - Grey Icons indicate incomplete checkpoints in the entire process

• 

  Recomendation and Search Engine - Recommendations to add nearby shops to calculate walk time to and fro back to the gate

Inspiration

It's always uncertain how long the wait times will be at airports, especially with baggage check-in and TSA checks. We often find ourselves running late to the gate because of our miscalculations. To make things easier for all passengers, we've decided to address this issue.

What it does

GateReady is a cutting-edge airport time management application designed to streamline and enhance the travel experience for air passengers. With real-time updates and personalized recommendations, GateReady ensures that travelers are well-informed, efficiently guided, and able to make the most of their time at the airport.

Features

• TSA Wait Time Calculation: Provides real-time TSA security check wait times.
• Airport Arrival Time Calculation: Offers calculated airport arrival times based on flight schedules and current conditions.
• Side Quest Recommendations: Suggests activities and amenities post-TSA checks, tailored to individual preferences.
• Gate Time Calculator: Estimates the time needed to reach the departure gate from TSA checkpoints.
• User Activity History: Tracks user preferences for more personalized future recommendations.
• Miscellaneous Time Management: Helps manage various pre-flight activities for a stress-free airport experience.

How we built it

We developed a full-stack application, utilizing Django for the backend and React.js for the frontend. We employed a KNN model to classify stores and amenities in the vicinity of passengers and cross-referenced it with their preferences to recommend stores they can visit on their way to the gate.

Challenges we ran into

One of the biggest challenges was the absence of real-life data. Therefore, if and when we obtain access to such data, I believe we will be able to make predictions with much higher accuracy and subsequently integrate this feature with the American Airlines application.

Accomplishments that we're proud of

Even though we formed our team only after meeting at the event and had no prior idea about the problem we would tackle, we ended up working together exceptionally well. Our skills complemented each other effectively.

What we learned

We learned a great deal about the various complexities involved in the pre-flight processes for passengers and gained insight into how dynamic the entire process is. Additionally, we learned how to integrate clustering and other machine learning concepts to perform effective recommendations. Moreover, we had the opportunity to understand the passengers' pain points and were able to address them effectively. Overall, it is a streamlined, one-stop solution that effectively supports passengers.

What's next for Gate Ready

One of the biggest challenges was the absence of real-life data. Therefore, if and when we obtain access to such data, I believe we will be able to make predictions with much higher accuracy and subsequently integrate this feature with the American Airlines application.

Built With

• django
• python
• react.js