Roamio: Leveraging Artificial Intelligence for Smart Traveler Matching, Itinerary Generation, and Solo Travel Safety

Abstract: The rise of social networking tools and mobile technologies has greatly influenced modern-day travel. Roamio is a full-stack cross-platform application that facilitates connections between compatible travel partners for solo travellers using AI-powered preference matching, real-time chat, intelligent trip planning, and SOS safety features. This paper outlines the design, development, implementation, and evaluation of Roamio using Visual Studio Code as the primary code editor, Expo React Native as the cross-platform mobile application development tool, and MongoDB as the NoSQL database backend. The application server uses Node.js/Express, MongoDB Atlas as a persistent cloud database, and various AI tools using LLM APIs. A cosine similarity algorithm is used to match users based on a multi-dimensional preference vector. A curated AI travel feed provides personalized travel recommendations to users, while an SOS feature allows users to send distress messages to up to five saved contacts. The results show that using AI to personalize travel recommendations with community-driven social networking for travel greatly reduces social friction for solo travellers.

Keywords: Travel companion platform, Expo React Native, MongoDB, AI trip planning, emergency SOS, social travel, preference matching, cross-platform mobile application