Review of Cloud-Based Public Security Video Investigation Systems: Architecture, Challenges, and Future Directions

Cloud computing has significantly transformed the way people investigate security video images by enhancing the analytical ability of surveillance technology, scaling and efficiency. Ordinary video surveillance systems have limitations in storage, real-time processing, and analysis of data, cloud computing addresses these issues quite satisfactorily. This paper explores different types of cloud computing models, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), and its applications in public security video studies. The concept of cloud-based video surveillance systems is mentioned along with the methods of data collection, cloud storage solutions, real-time processing, and analytics powered by artificial intelligence. The paper highlights the key benefits of cloud-based security systems which include improved scalability, cost efficiency, real-time monitoring, and AI-based threat detection. To ensure optimal performance, however, issues such as data privacy issues, cyber attacks, interoperability issues and dependency on constant internet connectivity need to be addressed. The paper also examines Indian case studies that have conducted cloud-based video analysis in the law enforcement system and smart city monitoring programs. By implementing the recently emerging technologies such as artificial intelligence, 5G, and edge computing, cloud-based public security systems can enhance the capability to prevent and respond to crimes. The essay discusses the future that should occur and highlights that regulatory frameworks, moral implementation of AI, and superior cloud protection measures are required.