AI-Powered Personalised Travel Itinerary Planning Application (Karnataka)

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

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-06-29
DOI
https://doi.org/10.22214/ijraset.2025.72818
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Personalised Travel Itinerary Planning Application (Karnataka)

Vinutha Prakash
International Journal for Research in Applied Science and Engineering Technology
Traffic Prediction and Management Techniques
article

AI-Powered Personalised Travel Itinerary Planning Application (Karnataka)

Vinutha Prakash
article en

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

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(6)
JSS Science and Technology University (IN)
Openalex Percentile: Top 84%
Traffic Prediction and Management Techniques
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