Aventra - AI Tourism Recommendation System

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Tourism has become one of the most popular activities for people who want to explore new places and experience different cultures.However, planning a trip can be challenging because travellers need to search through large amounts of information before choosing a destination.Many travel websites provide general information about tourist places, but they often do not offer personalized suggestions based on the user's interests and travel conditions.To address this problem, this paper proposes AVENTRA, an AI-based tourist recommendation system designed to help users discover suitable travel destinations quickly and easily.The system collects user inputs such as location, preferred climate, travel interest (adventure or culture), and trip type (local, domestic, or international).Based on these inputs, the system filters tourism data stored in a MongoDB database and generates personalized travel recommendations.The application is developed using HTML, CSS, and JavaScript for the user interface, while Node.js is used for backend processing and MongoDB is used for data storage.The system also provides useful travel information such as tourist attractions, famous food, nearby restaurants, and estimated travel budget for each destination.The main objective of the system is to simplify the travel planning process and provide users with relevant and customized travel suggestions.Experimental results show that the proposed system can effectively recommend destinations that match user preferences and improve the overall travel planning experience.