Abstract: An AI-powered system called the Travel-Bot Planner is developed to enhance and simplify the travel planning experience for users by combining intelligent route analysis, destination discovery, and automated itinerary generation. The platform provides an interactive, adaptive, and scalable travel-assistance environment by utilizing advanced technologies such as Large Language Models (LLMs) for natural language understanding, Retrieval-Augmented Generation (RAG) for real-time information retrieval, and geospatial services for accurate routing and map-based visualization. Users are guided through AI-driven conversations where their queries, preferences, and destinations are processed using NLP and vector-based search to deliver personalized recommendations, travel timelines, and route-specific popular attractions. The system enables travellers to receive structured itineraries, budget estimates, and booking simulations instantly, reducing manual effort and ensuring informed decision-making powered by intelligent automation.
Keywords: Travel Assistance, Large Language Models (LLM), Retrieval-Augmented Generation, Geospatial Intelligence.
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DOI:
10.17148/IJARCCE.2025.1412128
[1] Dr. Chetana Prakash, Akangnungba Walling, Anusha V, Bhagyashree S A, Bhavana P, "Travel-Bot Planner using Large Language Models (LLM) and Retrieval Augmented Generation (RAG)," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.1412128
