Smart City Traffic Monitoring Using an AI Traffic Cloud,

Modern urbanization requires intelligent systems to handle the increasing difficulties in traffic control. In order to address important problems like traffic congestion, accident detection, and infrastructure assessment, our project combines drones, CCTV, and IoT devices into a strong cloud-based platform. We offer a comprehensive solution that is suited to the intricacies of smart cities by utilizing cutting-edge technology like deep learning, sophisticated analytics, and scalable cloud services.
The IoT framework tracks traffic factors like vehicle speeds and congestion levels from 325 PeMS Bay sensors. A Diffusion Convolutional Recurrent Neural Network can predict traffic flow at 5-minute intervals using metrics like MAE (0.85) and RMSE (1.54).
The CCTV module classifies vehicles, analyzes traffic flow, and detects accidents using YOLOv8 and ByteTrack. COCO and live Caltrans feeds are displayed in an interactive dashboard with 82\% accuracy. A unified admin interface makes registration, planning, and real-time monitoring easier, while the drone component improves mission-critical operations like emergency response and infrastructure inspection. YOLOv8 and deepsort algorithms guarantee 70\% precision.To create smarter, safer, and effective urban settings, this project provides a scalable, user-centric platform that revolutionizes traffic and infrastructure management.