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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 14, ISSUE 10, OCTOBER 2025

“AI Driven Emergency Response System"

Mr. Rushikesh Dnyaneshwar Patil, Prof. Kaustubh bhave, Prof. Manoj Vasant Nikum*

DOI: 10.17148/IJARCCE.2025.141039

Abstract: The AI-Driven Emergency Response System enhances emergency management by integrating artificial intelligence, real-time data analysis, and automation. The system uses machine learning, computer vision, and natural language processing to detect and classify incidents such as accidents, fires, or medical emergencies from various data sources including CCTV, IoT sensors, and public reports. It automatically alerts the nearest response units and optimizes routes using GPS to ensure rapid assistance. A centralized dashboard provides real-time monitoring and predictive insights for authorities. This AI-based framework reduces human error, shortens response time, and supports the development of safer and smarter cities.

Keywords: Artificial Intelligence, Emergency Response, Machine Learning, Smart City, Automation.

How to Cite:

[1] Mr. Rushikesh Dnyaneshwar Patil, Prof. Kaustubh bhave, Prof. Manoj Vasant Nikum*, ““AI Driven Emergency Response System",” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141039