AI- DRIVEN SURVEILLANCE SYSTEMS FOR PUBLIC SAFETY

Kepeghom, Oruan Memoye.

dc.contributor.author	Kepeghom, Oruan Memoye.
dc.date.accessioned	2024-10-11T10:27:59Z
dc.date.available	2024-10-11T10:27:59Z
dc.date.issued	2024-11-06
dc.identifier.issn	3027-0650
dc.identifier.uri	http://hdl.handle.net/123456789/681
dc.description	Artificial intelligence (AI) adoption in surveillance represents a significant advancement in the field of public safety Doe. J. (2024). AI-driven surveillance systems for public safety enhances effectiveness while safeguarding privacy. Traditional surveillance techniques often have demerit in addressing the complexities of modern urban environments and evolving threats. AI-driven surveillance systems, which incorporate sophisticated algorithms, machine learning, and real-time data analysis, offer a more effective approach to monitoring and managing security issues. Haggerty, K. D and Ericson, R. V (2023)[2]. The surveillance assemblage Technology, power, and privacy systems employ technologies such as computer vision for facial recognition, anomaly detection, and predictive analytics to identify and respond to potential threats with increased accuracy. Extensive data analysis quickly allows for earlier detection and improved response strategies.	en_US
dc.description.abstract	Artificial intelligence (AI) is reshaping public safety through advanced surveillance technologies. AI-driven surveillance systems use machine learning, computer vision, and real-time data processing to enhance monitoring and threat detection capabilities. These systems offer improvements over traditional methods by providing more accurate, immediate insights, detecting anomalies and predicting potential threats with great precision. This paper explores the evolution, implementation, and impacts of AI-based surveillance systems on public safety, and focuses on their advantages, challenges, and ethical considerations. Through case studies and technological analysis, the study aims to offer a comprehensive view of AI's influence on public safety and its broader implications for privacy and civil liberties.	en_US
dc.language.iso	en	en_US
dc.publisher	[Federal College of Education Technical Omoku]	en_US
dc.relation.ispartofseries	American University of Nigeria, 2nd International Conference Proceeding;
dc.title	AI- DRIVEN SURVEILLANCE SYSTEMS FOR PUBLIC SAFETY	en_US
dc.type	Article	en_US