AI-Travel Planner

Abstract

Theproposedsystempresentsafullyintegrated,AI-poweredtravelplanning system that combines conversational AI, minimalist budget-based itinerary generation, an interactive offline safety map, and a hybrid SOS emergency system capable of both manualandautomaticactivation.Thesystem’sofflinesafetymapcategorizesareasusing a three-tier risk model (Red—High risk, Yellow—Moderate risk, Green—Safe) allowing users to travel safely even when internet connectivity is limited. The SOS module automatically detects loss of network connectivity and sends the user’s real-time GPS coordinates through SMS to registered emergency contacts. The design synthesizes techniques from machinelearning, multi-objective optimization, NLP-based interaction, and offline emergency communication protocols. The result is a robust travel safety and planning system useful for solo travelers, trekkers, and urban commuters.

Introduction

Traditional travel planning requires manual analysis of destinations, budgets, routes, and safety, while most existing travel applications lack offline safety awareness, automatic SOS support, AI-driven personalization, and budget-focused itinerary generation. To overcome these gaps, the proposed AI-TRAVELPLANNER integrates intelligent planning, safety intelligence, and emergency support into a single unified system designed for both online and offline use.

The system aims to provide conversational travel planning through an AI chatbot, generate budget-optimized itineraries using machine learning and genetic algorithms, and offer offline safety maps with color-coded risk zones (red, yellow, green). A key feature is its hybrid SOS mechanism, which supports both manual activation and automatic triggering during network failure or high-risk situations. Emergency alerts are transmitted via SMS with location details and secure user identity tokens, ensuring usability even without internet connectivity.

The literature review highlights that existing research focuses on isolated components such as route optimization, personalization, or SOS tools, but lacks a comprehensive framework combining planning, safety, budgeting, and offline emergency support. The proposed system addresses this gap by unifying these functionalities into a coherent architecture.

The AI-TRAVELPLANNER architecture consists of six integrated modules: an AI chatbot engine, budget planning and cost estimation, itinerary optimization, offline safety mapping, an SOS controller, and an offline SMS emergency module. The methodology includes NLP-based user interaction, budget filtering, AI-powered itinerary generation, offline safety zone classification, continuous network monitoring, and a hybrid SOS system with automatic SMS transmission during emergencies.

Experimental results show significant improvements over existing travel applications, including better itinerary efficiency, enhanced cost optimization, high SOS delivery success, reliable offline safety mapping, and reduced user decision fatigue. User testing across urban, semi-urban, and remote locations confirmed the system’s effectiveness, particularly its offline safety and emergency features.

Overall, the AI-TRAVELPLANNER establishes a new benchmark in travel assistance by combining intelligent planning, safety awareness, offline operability, and automated emergency response, with future scope for wearable integration, predictive crime mapping, and real-time group safety synchronization.

Conclusion

TheAI-TRAVELPLANNERsuccessfullyintegratesintelligenttravelassistance,budget-optimizeditinerary generation, offline safety visualization, and a hybrid SOS emergency system into a unified and dependable platform. By combiningAI-driven personalization with a robust offline architecture, the system overcomes major limitations of existing travel applications, particularly in scenarios involving poor connectivity, unfamiliarenvironments,oremergencysituations.Theincorporationofcolor-codedsafetyzonesempowers users to make informed decisions about their surroundings, while the automatic SOS mechanism enhances personal security by transmitting GPS coordinates through SMS during network failure. Experimental evaluationsdemonstratenotable improvementsinusersafety,costefficiency,andoveralltravelexperience. This work establishes a foundation for next-generation travel technologies, positioningAI-TRAVEL PLANNER as a practical, reliable, and comprehensive solution for solo travelers, trekkers, budget tourists, and individuals navigating high-risk or remote areas.

References

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Copyright

Copyright © 2025 Dr. Hema Jagadish, Chiranjeevi M Chethan, Veerana Gouda , Gagana G S, Chitra B. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.