Authors : Manali Sarkar; Aparajita Das; Sraddha Roy Choudhury; Siddhartha Chatterjee

Volume/Issue : Volume 10 - 2025, Issue 5 - May

Google Scholar : https://tinyurl.com/evxzd9fm

DOI : https://doi.org/10.38124/ijisrt/25may2352

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : An optimized travel recommendation system based on patterns of travel and difficulties is an intelligent system designed to provide customized route recommendations to travelers by analyzing their past travel behaviors and predicting potential challenges along suggested routes. The system uses machine learning to identify travel trends, such as frequently chosen paths, preferred pacing, and typical destination choices, tailoring route suggestions that are both engaging and aligned with user-specific preferences. Our paper presents an advanced Travel Route Suggestion System that leverages data driven insights to generate customized travel routes based on user travel patterns and anticipated route difficulties. By analyzing historical travel data, user preferences, and contextual factors - such as weather, terrain, and traffic conditions— the system provides route suggestions that align with each user’s unique interests, capabilities, and risk tolerance. It focuses on developing an intelligent travel route suggestion system to assist visitors in navigating from their source to their destination. It addresses these issues by leveraging traveler feedback and patterns to suggest the best possible routes and anticipate potential difficulties. In this paper an A* Based Optimized Travel Recommendation System for Smart Mobility has been developed.

Keywords : A* Algorithm, Travel Route, Smart Mobility, Recommendation System, Data-Driven Insights.

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