AI Based Automated Framework for Crime Detection and Crowd Management

Manual monitoring and surveillance methods are often time-consuming and prone to human error, necessitating innovative solutions. This research proposes the integration of AI and ML technologies to address these challenges. AI-based CCTV networks enable real-time data analysis, enhancing crowd manag...

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Bibliographic Details
Published in:	2024 Second International Conference on Advances in Information Technology (ICAIT) Vol. 1; pp. 1 - 6
Main Authors:	Basthikodi, Mustafa, Vidya, B, Pinto, Elvicia Miriam, Basith, Mohammed, Rao, Srinivas A
Format:	Conference Proceeding
Language:	English
Published:	IEEE 24-07-2024
Subjects:	Artificial intelligence CCTV networks Crime Detection Crowd Management Ethics Machine learning Pattern recognition Public security Real-time systems Security Streaming media Surveillance Urban areas YOLO
Online Access:	Get full text
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Summary:	Manual monitoring and surveillance methods are often time-consuming and prone to human error, necessitating innovative solutions. This research proposes the integration of AI and ML technologies to address these challenges. AI-based CCTV networks enable real-time data analysis, enhancing crowd management and crime detection across diverse environments. The system utilizes cutting-edge technologies, incorporating im- age and live video feeds for dynamic analysis, anomaly detection, and pattern recognition. Key features include timely security threat notifications and efficient crowd monitoring. Successful implementation requires a significant investment in technology, infrastructure, and robust data management systems. Ethical considerations, particularly privacy, are paramount. The project aims to revolutionize crime detection and crowd management, introducing a modern, accurate, and efficient system aligned with the evolving security landscape.
DOI:	10.1109/ICAIT61638.2024.10690527