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@article{206676,
        author = {Deepak Kumawat and Dr. Abhijit Thakur and Dr. Anuja Bokhare},
        title = {PREDICTIVE ANALYTICS FOR SMART CITY INFRASTRUCTURE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {2472-2475},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206676},
        abstract = {Unpredictable weather, trash overflow, and changing energy consumption are some of the major obstacles to urban sustainability. Traditional planning methods frequently don't account for unexpected spikes brought on by seasonal changes or cultural festivities. This study offers a hybrid forecasting platform that combines festival effect mapping, real-time weather data from APIs, and machine learning algorithms into an interactive dashboard. Strong predictive accuracy is demonstrated by the system, which was developed using Python and Streamlit and validated using metrics like MAE, RMSE, and R2. The framework facilitates proactive resource allocation and supports sustainable smart city management by integrating historical datasets, artificial seasonal weather patterns, and cultural event markers.},
        keywords = {},
        month = {July},
        }