Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{174025,
        author = {Prof. Shah Saloni Niranjan and Bhosale Jayash and Thakre Raj and Mandlik Omkar},
        title = {A Survey on AI Travel Planner},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2757-2760},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174025},
        abstract = {Adaptive trip recommendation system under development delivers an appropriate traveling experience by providing a personalized itinerary in real time which considers personal user choices, the environmental conditions, and location-specific data. Different from the existing systems where one receives static recommendations or very limited logistics support, the proposed system involves an integration of real time data that would include weather, seasonal events, and user interests in order to maximize each traveler's enjoyment in the journey. The outstanding adaptable itineraries proposed by the system would result not only in increased satisfaction and exploration but also in more balanced experience changes relative to a traveler's individual conditions and travel goals. This condition ensures that the itineraries remain continuously relevant and personal; hence, offering an overall new experience of traveling quality and fulfilment.},
        keywords = {Adaptive Trip Recommendation, Personalized Itineraries, Real-Time Travel Planning, Tourism Technology, Dynamic Itinerary.},
        month = {March},
        }