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 Trip Planner: Personalized Travel Optimization and Recommendation Framework |
|---|---|
| ABSTRACT | This research work proposes an AI-based intelligent trip planning system that can automatically generate travel itineraries, cost estimates, route planning, and customized destination suggestions. Unlike the conventional manual and search-based planning process, the system uses machine learning-based preference modeling and real-time travel data to dynamically respond to the user’s needs for budget, weather, seasonal crowd, hotel, historical, and transportation-related preferences. The adaptive algorithm designed by the system generates optimized itineraries, hotel, and flight suggestions, and dynamic adjustments based on changes in location, unexpected delays, or environmental disruptions. The AI-based Trip Planner system shows better accuracy in personalizing travel itineraries and better efficiency in planning with less human intervention during experimental implementation. The combination of automated intelligence, real-time data optimization, and continuous decision support is a major breakthrough in modernizing travel planning systems with smart, proactive, and responsive approaches. |
| AUTHOR | PROF. KAVYASHREE E D, KIRAN KUMAR V, DHANUSH P L, AMRUTHESH CHANDRASHEKHAR ANNIGERI, SINDHU H S Assistant Professor, Department of Computer Science and Engineering, ATME College of Engineering, Mysuru, Karnataka, India UG Students, Department of Computer Science and Engineering, ATME College of Engineering, Mysuru, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401076 |
| pdf/76_AI-Powered Trip Planner Personalized Travel Optimization and Recommendation Framework.pdf | |
| KEYWORDS | |
| References | [1] Singh, A., Patel, R., and Mehta, V., “Collaborative Filtering-Based Travel Recommendation System,” Journal of Tourism Informatics, vol. 9, no. 1, pp. 45–53, 2020. [2] Chen, X., Huang, Z., and Lin, Y., “Genetic Algorithm-Based Optimization for Travel Itinerary Planning,” Journal of Optimization and Applications, vol. 10, no. 4, pp. 267–275, 2020. [3] Iyer, K., Joshi, P., and Deshmukh, R., “Location-Aware Travel Recommendation System Using Contextual Data,” International Conference on Mobile Computing, pp. 112–118, 2021. [4] Roeder, J., Müller, A., and Chen, K., “Intelligent Travel Plan Optimization Using Artificial Intelligence Techniques,” IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 98–106, 2021. [5] Wang, L., Zhou, Y., and Liu, X., “Weather-Aware Machine Learning Model for Travel Recommendations,” International Journal of Data Science and Analytics, vol. 11, no. 2, pp. 120–129, 2021. [6] Dube, R., Kumar, S., and Pate, S., “Reinforcement Learning Approach for Travel Itinerary Optimization,” Journal of Artificial Intelligence Research, vol. 15, no. 2, pp. 145–154, 2022. [7] Garcia, M., Santos, J., and Rivera, L., “Cloud-Based Smart Travel Assistant Using AI Algorithms,” Procedia Computer Science, vol. 189, pp. 345–352, 2022. [8] Park, J., Kim, H., and Lee, S., “Deep Learning Model for Predicting Travel Preferences and Behavior,” Journal of Artificial Intelligence Applications, vol. 16, no. 1, pp. 56–64, 2022. [9] Edward, M., Thompson, R., and Lee, R., “AI-Based Trip Planning Using Natural Language Processing and Machine Learning,” International Journal of Intelligent Systems, vol. 18, no. 3, pp. 210–219, 2023. [10] Rahman, S., Ali, T., and Khan, M., “Tourist Attraction Clustering for Intelligent Itinerary Planning,” International Journal of Advanced Computer Science, vol. 14, no. 3, pp. 188–196, 2023. [11] Sharma, R., Gupta, A., and Malhotra, S., “Real-Time AI-Based Travel Planning with Traffic and Weather Integration,” IEEE International Conference on Smart Systems, pp. 221–228, 2023. [12] Kumar, P., Sharma, N., and Verma, N., “Dynamic AI-Based Travel Planning Application for Personalized Itineraries,” International Conference on Smart Computing, pp. 301–308, 2025. [13] Almeida, F., Costa, D., and Pereira, J., “Multi-Criteria Decision Support System for Intelligent Travel Planning,” International Journal of Decision Support Systems, vol. 8, no. 2, pp. 90–99, 2021. [14] Bose, S., Nair, M., and Krishnan, R., “Hybrid Machine Learning Approach for Personalized Trip Planning,” Journal of Computational Intelligence, vol. 19, no. 3, pp. 175–184, 2024. [15] Kaur, H., Singh, V., and Arora, P., “AI-Based End-to-End Travel Planning Assistant for Personalized Experiences,” International Journal of Smart Tourism Systems, vol. 6, no. 1, pp. 33–41, 2024. [16] M. S. Sharmila, P. Rajalakshmi, “AI-Based Intelligent Travel Recommendation and Route Optimization System, IEEE International Conference on Computational Intelligence and Data Science, Vol. 3, pp. 112–120, 2022. [17] Fundamentals of Database Systems by Ramez Elmasari and Shamkant B. Navathe. [18] https://www.w3schools.com/ [19] https://www.geeksforgeeks.org/ [20] https://www.tutorialspoint.com/ |
