AI-Optimized Itinerary Design: Transforming the Future of Travel Planning

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 12 | Issue : 02 | Page : –
    By

    Deepali Jawale,

  • Pooja Mishra,

  • Pratik Kamble,

  • Dewang Mhatre,

  • Shubham Jadhav,

  • Luv Singh,

  1. Assistant Professor, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India
  2. Student, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India
  3. Student, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India
  4. Student, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India
  5. Student, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India
  6. Assistant Professor, Department of Computer Science and Engineering, Dr. DY Patil Institute of Engineering, Management and Research, Akurdi, Pune, Maharashtra, India

Abstract

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The travel industry is struggling to meet the rising demand for efficient and personalized trip planning. Traditional methods often lack real-time updates and fail to adapt to individual preferences, necessitating innovative solutions. This study presents an AI-powered travel planner utilizing the Gemini API to enhance itinerary creation. By analyzing user preferences, interests, and real-time data, the system delivers tailored travel recommendations. Leveraging advanced technologies such as cloud computing, machine learning, and natural language processing, the AI trip planner provides accurate and dynamic travel insights. Key features include user-centric recommendation algorithms, robust data processing pipelines, and an intuitive front-end interface forseamlessinteraction. Automating itinerary planning and real-time updates ensures better travel decisions, reduces planning time, and enhances user experience. This study details the design, architecture, and evaluation of the AI trip  planner, demonstrating how intelligent automation and personalized service can transform digital travel assistance.

Keywords: AI-powered travel planner, real-time information, personalized recommendations, machine learning, intelligent automation, cloud computing, natural language processing, data-driven insights, itinerary optimization, user-centric design

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Deepali Jawale, Pooja Mishra, Pratik Kamble, Dewang Mhatre, Shubham Jadhav, Luv Singh. AI-Optimized Itinerary Design: Transforming the Future of Travel Planning. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):-.
How to cite this URL:
Deepali Jawale, Pooja Mishra, Pratik Kamble, Dewang Mhatre, Shubham Jadhav, Luv Singh. AI-Optimized Itinerary Design: Transforming the Future of Travel Planning. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):-. Available from: https://journals.stmjournals.com/joaira/article=2025/view=0



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Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 26/03/2025
Accepted 14/04/2025
Published 19/04/2025
Publication Time 24 Days
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