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@article{177263,
        author = {SHREYASH GUJAR and SAKSHI DOMANE and ATHARV DIVATE and PRERANA MANE and Prof. R. A. BHARATIYA},
        title = {Central Rescue System using ML},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {427-429},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177263},
        abstract = {A Central Rescue System powered by machine learning represents a transformative approach to emergency response and disaster management. By leveraging intelligent data analysis techniques, this system is designed to collect, process, and interpret vast volumes of real-time and historical data from diverse sources, including emergency call logs, social media platforms, sensor networks, and geographic information systems (GIS). The integration of supervised machine learning models enables the accurate classification of emergency types—such as fires, medical incidents, or natural disasters—allowing for faster recognition and more informed decision-making. The system's predictive capabilities not only improve response times but also optimize the use of rescue personnel and equipment based on real-time risk assessments.},
        keywords = {},
        month = {May},
        }