TRIPPER: A Smart Travel and- accommodation Management System

Abstract

The tourism industry is growing fast with smart systems that give travelers personalized experiences. This paper discusses about a smart tour where users pick dates, places, and budgets, and algorithms make customized packages with the best options for accommodation, travel, and sightseeing. This paper introduces a new way to design tourism systems based on what users want. The proposed method uses machine learning to study different data. According to this article, the system makes travel plans tailored to users' preferences, history, and sightseeing habits. This research also suggests the best places to stay, travel options, and attractions based on what users like and can afford. To see if this idea works, a study with many tourists were done. The results show that using personalized recommendations from algorithms boosts tourist satisfaction and business earnings. This research shows it's important to have personalized recommendation systems in smart tourism to make travel better overall.