AI-Powered Personalised Travel Itinerary Planning Application (Karnataka)

TLDR

Tests show that the adaptive system has greatly enhanced planning accuracy and user satisfaction and engagement, and has potential for use by tourism offices, augmented and virtual reality previews, and sustainable development initiatives.

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