AI Travel Framework with Behavioural Analysis and Gamification

The mern stack, AI powered social travel planning system known as Plan Vise handles modern travel planning processes which currently require multiple separate components to operate. The system uses Generative AI technology to create personalized travel itineraries which adapt to user requirements that include destination selection and travel timing and travel companion selection and activity preferences and expense range and currency type and user provided text. The system architecture consists of three distinct components which operate as client and server and database. The system uses WebSocket technology to create a dedicated server which enables users to conduct real time group chats inside trip specific rooms that include typing indicators and GPS location sharing and real time member status updates. The platform provides a complete trip lifecycle management solution which monitors the entire trip process from planned status through active status to finished status while users can track expenses through categorisation and budget visualisation features. The social graph module enables users to establish mutual friend connections which allow direct messaging and trip sharing functions. The platform maintains user interest through a gamification system that includes eight badges which automatically grant points when users interact with the system. The itinerary reports created by the system feature weather predictions and hotel suggestions which include direct booking options and restaurant recommendations that provide map access and daily activity schedules which match companion type and travel advice for each group. This paper presents the complete system architecture, data flow diagrams, module decomposition, implementation details, and system requirements of Plan Vise.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-01
DOI
https://doi.org/10.5281/zenodo.19946973
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Travel Framework with Behavioural Analysis and Gamification

K. Butchiraju, Pothuganti Navanitha, Samrudhi Puranik, Akshaya Bathala et al.
Zenodo (CERN European Organization for Nuclear Research)
Transportation and Mobility Innovations
article

AI Travel Framework with Behavioural Analysis and Gamification

K. Butchiraju, Pothuganti Navanitha, Samrudhi Puranik, Akshaya Bathala, Nallaganti Sonalika, Tiragamalla Shivani
article en

Abstract

The mern stack, AI powered social travel planning system known as Plan Vise handles modern travel planning processes which currently require multiple separate components to operate. The system uses Generative AI technology to create personalized travel itineraries which adapt to user requirements that include destination selection and travel timing and travel companion selection and activity preferences and expense range and currency type and user provided text. The system architecture consists of three distinct components which operate as client and server and database. The system uses WebSocket technology to create a dedicated server which enables users to conduct real time group chats inside trip specific rooms that include typing indicators and GPS location sharing and real time member status updates. The platform provides a complete trip lifecycle management solution which monitors the entire trip process from planned status through active status to finished status while users can track expenses through categorisation and budget visualisation features. The social graph module enables users to establish mutual friend connections which allow direct messaging and trip sharing functions. The platform maintains user interest through a gamification system that includes eight badges which automatically grant points when users interact with the system. The itinerary reports created by the system feature weather predictions and hotel suggestions which include direct booking options and restaurant recommendations that provide map access and daily activity schedules which match companion type and travel advice for each group. This paper presents the complete system architecture, data flow diagrams, module decomposition, implementation details, and system requirements of Plan Vise.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Transportation and Mobility Innovations
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