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@article{192356,
        author = {Shailesh Kamble and Vijay Pandey and Sahil Petewar and Om Buttekar and Vaishnavi Munginwar and Kunal Akkalwar and Prof. Divya Pogaku Mam},
        title = {AI-Driven Smart Travel Planner Using Intelligent Recommendation and Real-Time Optimization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {1416-1424},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192356},
        abstract = {Travel planning has gradually shifted from manual information search to intelligent decision-support platforms ca- pable of delivering personalized and adaptive travel experiences. However, many existing travel applications still offer fragmented services and static recommendations, forcing users to rely on multiple platforms for booking, navigation, attraction discovery, and schedule management. Moreover, real-world factors such as traffic conditions, weather variations, availability changes, and price fluctuations are often ignored, reducing itinerary feasibility and user satisfaction. This paper presents an AI-driven smart travel planner that integrates hybrid recommendation techniques, itinerary optimization, and real-time contextual adap- tation within a unified platform. The system captures user pref- erences including budget, interests, travel duration, and travel style to automatically generate feasible multi-day itineraries. Route ordering and temporal constraints are optimized to ensure efficient scheduling, while a dynamic re-planning mechanism continuously monitors live conditions and suggests alternate routes, substitute attractions, or schedule adjustments. The sys- tem is implemented using a modern web-based architecture with HTML, CSS, and ReactJS for the front-end, Java-based backend services for business logic, and MySQL for structured data management. The modular design enables scalability and future extensions such as AR-based previews, blockchain-supported booking transparency, and IoT-enabled smart tourism services. Overall, the proposed planner minimizes manual planning effort while improving itinerary relevance, feasibility, and adaptability.},
        keywords = {Artificial Intelligence, Smart Travel Planning, Intelligent Recommendation Systems, Personalized Itinerary Generation, Route and Time Optimization, Real-Time Contex- tual Adaptation, Web-Based Travel Applications, ReactJS, Java Backend, MySQL},
        month = {February},
        }