AI-Based Airport Passenger Flow Prediction System for Efficient Resource Management
NTPL Digital Private Limited Aviation & Airport ManagementProject Objectives:
Develop an AI-driven system to predict passenger flow at airports, enabling efficient allocation of check-in counters, security staff, and boarding gates. Students will explore predictive analytics, AI algorithms, and real-time monitoring to optimize airport operations
Project Tasks:
Collect historical passenger data from check-in counters, boarding gates, and security.
Preprocess and clean data for AI modeling.
Train predictive models using machine learning algorithms such as regression or LSTM.
Visualize passenger flow trends on a dashboard with real-time updates.
Provide resource allocation recommendations for peak and off-peak hours.
Test the system with simulated data for accuracy and efficiency.
Document data sources, model performance, and implementation methodology.
