International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Powered Travel Itinerary Generator |
|---|---|
| ABSTRACT | Travel planning is often a time-consuming process that requires users to search across multiple platforms to decide destinations, schedules, and activities. Many travelers struggle to create a well-structured itinerary that fits their budget, travel duration, and personal preferences. This project focuses on simplifying this process by using artificial intelligence and data-driven techniques to automatically generate personalized travel itineraries. In this study, we explore how Natural Language Processing (NLP) and Large Language Models (LLMs) can be used to understand user inputs such as destination, travel dates, and budget, and convert them into a detailed, day-wise travel plan. The system is implemented using a Django-based web application, where user data is processed and analyzed before being passed to an AI model that generates meaningful travel recommendations. The output includes daily activities, local attractions, food suggestions, and travel tips tailored to the user’s requirements. What makes this system effective is its ability to adapt recommendations based on constraints like travel duration and budget, reducing the need for manual planning. The inclusion of real-time data such as weather further improves the practicality of the generated itinerary. By automating the planning process, the system saves time and enhances the overall travel experience. Overall, this project demonstrates how data science, machine learning, and AI-based recommendation systems can be applied to the travel domain to provide personalized and intelligent solutions. With future improvements, the system can be extended to include hotel recommendations, cost prediction, and collaborative trip planning features. |
| AUTHOR | PROF. RANJANA B JADEKAR, MOUIZ UR REHAMAN, P GAUTHAM, SYED KAIFUDDIN, SUNNY GOUD Assistant Professor, Department of CS&DS, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India U.G. Student, Department of CS&DS, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401024 |
| pdf/24_AI-Powered Travel Itinerary Generator.pdf | |
| KEYWORDS | |
| References | [1] Collaborative Filtering for AI-Powered Itinerary Planning, Journal of AI Applications, 2022. [2] R. Deshmukh, S. Kulkarni, and A. Patil, AI-Powered Travel Planner: A Smart Solution for Personalized and Efficient Travel Itineraries, International Journal of Computer Applications, 2023. [3] P. Patel and M. Shah, AI-Based Recommendation System for Travel Planning, International Journal of Advanced Research in Computer Science, 2022. [4] S. Singh, A. Sharma, and V. Mehta, A Review on AI-Driven Travel Planning Applications, International Journal of Innovative Research in Technology, 2021. [5] Research papers on NLP and Recommendation Systems [6] OpenWeather API Documentation [7] Google Maps API Documentation [8] Google Places API Documentation |
