Year: 2025
Type: article
Abstract: The use of AI for personalized travel planning augmentsitsefficiencywhichisaremarkableadvancedfeatureof smarttourism.Unlikepreviousplanningmethods,itenablesboth adaptive and fully independent support for users. Considering how contemporary societies place more value on individually curated travel experiences, traditional travel tools still seem to lack appropriate recommendations that are timely, relevant, and user-friendly.Toaddresstheseissues,thispaperpresentsanautomatedtravelplanningsolutionpoweredwithever-evolvingartifi- cialintelligenceandmachinelearningtechnologiesthatadaptsto the user’s context and creates fully personalized itineraries. The systemintegratesvarioustravelerprofiles,includingsolotourists, family groups with children, and adventure seekers, by blending user’smoods,interests,travelbudgets,andtripduration.Crucial aspects include user-definable real-time profiling with Adaptive Preference Classification (APC) and behavioral-driven activity and destination selection via the Multi-Constraint Itinerary OptimizationAlgorithm(MCIOA).Withenhancedrelevanceand agilitytoimprovesystemadaptability,real-timeweatherforecasts and local events updates can be integrated. Tests show that the adaptive system has greatly enhanced planning accuracy anduser satisfaction and engagement. The system has potential for use by tourism offices, augmented and virtual reality previews, and sustainable development initiatives
Author: Vinutha Prakash
Institution: JSS Science and Technology University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411761776