Smart Travel Planning System Using Artificial Intelligence

@article{1719363,
      author = {Faishal Malik},
      title = {Smart Travel Planning System Using Artificial Intelligence},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {4180-4181},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719363.pdf},
      abstract = {Artificial Intelligence (AI) has significantly transformed the tourism industry by enabling intelligent decision-making and personalized user experiences. Traditional travel planning often requires users to visit multiple websites and applications to compare destinations, accommodation, transportation, weather conditions, and travel expenses. This fragmented approach is time-consuming and may lead to inefficient travel decisions. This study presents a Smart Travel Planning System Using Artificial Intelligence, a web-based application designed to simplify travel planning by integrating personalized destination recommendations, budget estimation, route planning, and weather information within a single platform. The application was developed using Python, Flask, HTML, CSS, JavaScript, and SQLite. A rule-based recommendation engine analyzes user preferences, travel budget, destination interests, and travel duration to generate customized travel suggestions. The system also estimates travel expenses and assists users in selecting suitable destinations according to their financial constraints and preferences. The developed prototype was evaluated through functional testing, including user registration, authentication, recommendation generation, budget estimation, route optimization, and weather information modules. The results demonstrate that the system successfully provides personalized recommendations, improves travel planning efficiency, and reduces the manual effort required during trip preparation. Although the current implementation is based on rule-based recommendation logic and a limited dataset, the proposed system establishes a practical foundation for future AI-driven travel planning platforms. Future enhancements may include machine learning algorithms, real-time travel APIs, online booking facilities, multilingual support, and mobile application development.},
      keywords = {Artificial Intelligence, Smart Tourism, Recommendation System, Travel Planning, Flask, Python, Route Optimization, Budget Estimation.},
      month = {July},
  }