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@article{199687,
        author = {Madhuchetan and Challa Ashok Kumar Reddy and Chepala Shaik Shoaib Basha and P S Lalith Sahan},
        title = {Lazy Wanderer – A Smart Travel Planner},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {15509-15518},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199687},
        abstract = {Planning a trip is normally associated with dealing with many aspects of the process at once, such as choosing destinations, estimating budgets, scheduling itineraries, among others. Traditionally, people have to go across several interfaces and manually manage everything which leads to inefficiencies and inability to be personalized. This paper aims at developing a solution which would simplify this process by means of designing and presenting "Lazy Wanderer," the Smart Travel Planner. The proposed system is implemented using the architecture that consists of the client (the front-end) and the server (the back-end). The client-side is developed using Angular. The back-end utilizes Spring Boot with MySQL. Using the developed system, one can plan his/her trips in a way that takes into account individual preferences concerning budget, length, and destinations. Furthermore, it suggests routes, manages expenses during the trip, and considers real-time information like weather predictions to help with better decision-making. The suggested system implements the client-server paradigm, where requests from users are processed by the back-end, combined with pre-stored and actual data. It then returns results in the form of itineraries. According to preliminary evaluation, this approach helps in improving planning effectiveness and user experience. The developed Lazy Wanderer Smart Travel Planner shows the potential of applying contemporary web technologies and intelligent data processing algorithms to develop practical solutions for smart tourism applications. Possible extensions may include adding machine learning techniques, enabling mobile platforms' support, and integrating booking functionality.},
        keywords = {},
        month = {April},
        }