Travel-AI: A Comprehensive Intelligent Framework for Personalized Travel Planning, Predictive Analytics, and Secure booking

This paper presents Travel AI, an end-to-end intelligent travel platform designed to revolutionize the travel planning and management ecosystem. The system integrates multiple advanced machine learning models within a modern full-stack architecture to automate and personalize the entire travel lifecycle. Core innovations include a multi-algorithm itinerary planner that synergistically combines K-Means clustering for point-of-interest grouping with genetic algorithms for optimal activity sequencing under user constraints. A hybrid recommendation engine employs both collaborative and content-based filtering, enhanced by deep learning models for analyzing accommodation imagery and reviews. Predictive analytics are delivered through Long Short-Term Memory (LSTM) networks for dynamic flight and hotel price forecasting, empowering users with cost-efficient booking strategies. Real-time user interaction is facilitated by a transformer-based Natural Language Processing (NLP) chatbot, providing 24/7 conversational support. Critical security is embedded via a fraud detection module using Isolation Forest for anomaly detection and Logistic Regression for transaction classification. Additionally, Convolutional Neural Network (CNN)-based landmark recognition enables visual discovery. Deployed using a ReactJS frontend, Django backend, and cloud infrastructure, Travel AI establishes itself as a comprehensive, intelligent travel companion that effectively addresses prevailing challenges in personalization, financial optimization, and security within the global travel industry.