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@article{169282,
        author = {Rohit Shinde and Vedant Salunkhe and Bharat Sharma and Shrushti Sabale},
        title = {TripInsight: A Comprehensive Travel Analytics and Review Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {601-604},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169282},
        abstract = {Travel planning has become increasingly complex due to the vast amount of online information available to users. TripInsight, a travel analytics platform, is designed to address this issue by providing personalized recommendations, real- time crowd predictions, cost transparency, and user-generated reviews. This paper details the platform’s architecture, the role of machine learning in crowd prediction, and the infrastructure that ensures scalability. Through Trip Insight, travelers can make more informed decisions by accessing real-time, trustworthy data. This paper also explores the system’s workflow and discusses its potential for future enhancements, ultimately positioning Trip- Insight as a crucial tool for modern travelers seeking efficiency and reliability in their planning processes.},
        keywords = {Travel analytics, machine learning, crowd prediction, MongoDB, Django},
        month = {November},
        }