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@article{205452,
        author = {Sakshi Borse and Dr. Deepa Padalkar and Ojal Paturday and Saniya Sayyad},
        title = {DESTIFY: An Intelligent Web-Based Travel Insights Dashboard with Geospatial Visualization and AI-Assisted Travel Support},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {6800-6810},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205452},
        abstract = {The rapid growth of digital tourism platforms has created demand for intelligent systems that can integrate heterogeneous travel information into a single, interactive decision-support environment. Existing travel applications often provide fragmented services such as flight lookup, hotel browsing, map-based discovery, or chatbot assistance in isolation, which limits analytical exploration and informed itinerary planning. This paper presents DESTIFY, an intelligent web-based travel insights dashboard that unifies multi-source travel analytics, geospatial destination exploration, and AI-assisted user support within a single platform. The proposed system combines a web frontend for dashboard visualization and 3D destination browsing with a backend built on Express.js for API orchestration, regional data fallback generation, currency conversion, tourism insight delivery, and conversational assistance. The architecture follows a modular and service-oriented design, enabling seamless integration of multiple external data providers while maintaining scalability and maintainability. The prototype integrates weather, tourism, hotel, flight, and exchange-rate services, and supports 88 destinations with 12 application endpoints in an observed runtime configuration. A lightweight forecasting strategy is used for flight trend projection, while geospatial interaction and chart-driven analytics improve user comprehension of destination conditions. Additionally, the system incorporates interactive visualizations that enhance comparative analysis of destinations and facilitate data-driven travel planning. Prototype observations demonstrate that the system can deliver integrated travel intelligence, current weather snapshots, tourism indicators, predicted flight-price series, and contextual chatbot responses from a unified interface. Experimental evaluation indicates that the platform effectively consolidates dispersed travel information and reduces the effort required for destination analysis and itinerary preparation. The study shows that a modular, API-driven travel dashboard can improve accessibility, scalability, and decision support for tourism planning while remaining suitable for further extension into personalization, predictive recommendation, and smart tourism analytics tasks.},
        keywords = {AI-assisted tourism, geospatial visualization, intelligent dashboard, travel analytics, travel recommendation, web GIS, web-based tourism system.},
        month = {June},
        }