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@article{208182,
        author = {Akifa Taskeen and Apoorva B Kumar and Dipa Mishra and K Mohammed Tabrez and Prof Najmusher H},
        title = {CityVerse AI: Review on Intelligent Data-Driven Urban Optimization System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {4},
        pages = {856-862},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208182},
        abstract = {With rapid urbanization growth in the last few decades, the management of urban transportation, facilities, infrastructure and resources had been quite challenging. Urban areas generate enormous data, but many of them are still underutilized or only treated in isolation for the planning of cities. In this article, a review on the applications of the state-of-the-art machine learning, deep learning, data analysis and optimization in smart cities are presented, along with an explanation of the City Verse AI – an integrated framework of urban optimization, developed based on these survey findings. The developed model integrates real time traffic data to provide an overall plan for energy, population, resources and facilities based on simulation-based data, which consists of six interconnected modules data acquisition, data pre-processing, traffic forecasting, infrastructure planning, resource allocation and interactive simulation/visualization framework. Here LSTM is applied for forecasting traffic demand and K-Means can assist the process of identification of areas having urgent infrastructure development needs, whereas the optimization processes would help to determine placement of facilities and allocation of resources at their optimal location and amount.},
        keywords = {Smart Cities, Urban Optimization, Traffic Forecasting, LSTM, K-Means.},
        month = {September},
        }