Paper Contents
Abstract
In today's fast-paced world, travelers seek quick, personalized, and hassle-free solutions for planning their journeys. Traditional travel planning methods often require extensive time, research, and coordination, making the experience complex and inefficient. This research introduces an AI-powered itinerary generator, a smart system designed to automate and personalize travel plans based on user preferences, location, budget, interests, and time constraints. The proposed system integrates artificial intelligence and machine learning techniques to recommend optimized travel itineraries, suggest nearby attractions, estimate travel times, and adjust plans dynamically based on weather and real-time data. By leveraging user inputs and external APIs, the generator creates flexible and efficient travel schedules tailored to individual or group needs. The paper discusses the methodology, system design, and implementation process, along with challenges like data accuracy, personalization, and adaptability. This research aims to contribute to the growing field of intelligent travel systems and highlights the potential of AI in transforming the tourism experience through automation, convenience, and smart decision-making. Keyword: Artificial Intelligence, Travel Planning, Itinerary Generator, Personalized Recommendations, Smart Tourism, Machine Learning, User Preferences, Travel Automation, Intelligent Systems, Location-Based Services
Copyright
Copyright © 2025 Rahul kumawat. This is an open access article distributed under the Creative Commons Attribution License.
