Design of Neural Network-Based Smart City Security Monitoring System
Yao Yao
Abstract
This paper presents a smart city security system using AI to enhance urban monitoring and public safety. It features a hierarchical architecture, processes video and multimodal data, and employs CNNs and RNNs for detecting 173 types of violations with 93.6% accuracy. The system, hosted on Kubernetes, shows excellent scalability, with a query response time of 246.8 milliseconds and 98% of events processed under 1 second. Future work will focus on improving complex scene recognition and optimizing GPU resources.
Topics & Concepts
Computer scienceArtificial neural networkSecurity systemEmbedded systemComputer securityArtificial intelligenceWireless Sensor Networks and IoTAdvanced Sensor and Control Systems