Paper Details

Travel planning can be a time-consuming process because users often need to explore multiple platforms to find destinations, compare travel options, manage budgets, and organize daily activities. This paper presents WanderIQ, an AI-driven travel recommendation and itinerary planning system designed to simplify the travel planning process. The proposed system aims to provide personalized destination recommendations and structured travel itineraries based on user preferences, budget, travel duration, and interests. It also focuses on organizing travel-related information in a single platform to improve convenience and planning efficiency. Depending on the implemented features, the system can support destination exploration, daily itinerary generation, budget estimation, and travel information management. The proposed approach seeks to reduce manual planning effort and provide users with a more organized and personalized travel planning experience. The system can be developed using web technologies and artificial intelligence techniques to support flexible and user-friendly interactions. Its effectiveness can be evaluated using criteria such as recommendation relevance, itinerary quality, response time, and user satisfaction. WanderIQ aims to demonstrate how intelligent recommendation techniques can contribute to a more efficient and personalized travel planning process.

Rutuja Fakkad Kauthale, Drushti Vijay Patil, Aryan Yeshwant Singh, Rohit Tukaram Khatake, prof. Pradnya Patange, “WanderIQ: An AI-Driven Travel Recommendation and Intelligent Itinerary Planning System”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 13, Issue 10, pp. 27-30, November 2026, DOI: 10.5281/zenodo.24071073.