Intelligent Itinerary Customization and Real-time Planning System for Private Travel Groups

Abstract

To address the limitations of traditional tourism services in meeting users' personalized and real-time needs, this study presents an intelligent assistant system designed for small private travel groups. The system integrates user preferences with multi-source real-time data to automatically generate and dynamically optimize personalized itineraries, supporting seamless multi-platform interactions across web browsers, progressive web applications (PWA), and WeChat official accounts. It features intelligent itinerary planning, real-time information pushes, and social interaction functions. Through a user behavior analysis and keyword-based recommendation algorithms, the system enables personalized content delivery and dynamic decision support. In addition, it incorporates real-time external data, such as weather and traffic conditions, to further enhance itinerary optimization. Built with Vue 3, Node.js, and MongoDB, the platform offers efficient performance and secure operation, significantly improving user experience and engagement and contributing to the intelligent development of smart tourism services.