Project Overview
The client needed an AI-driven system that could analyze large-scale vehicle traffic using aerial CCTV cameras. The goal was to detect and count vehicles, generate heatmaps of movement patterns, and analyze traffic flow direction to improve traffic management, road planning, and public safety. The system had to be scalable for use in highways, busy intersections, and urban areas.
Our Contribution
🎯 Developed an AI-powered detection system to identify and count vehicles in real time. 🎯 Implemented heatmap analysis to visualize traffic density and congestion points. 🎯 Built a traffic flow direction tracking module to analyze vehicle movement patterns.
Our Contribution
🎯 Optimized the system for high accuracy in aerial and wide-angle surveillance footage. 🎯 Designed a scalable and cloud-ready solution for easy integration with traffic control
KEY FEATURES
Tool & Technologies
Customer Feedback
John Doe
Codetic
Results
The system provided real-time traffic insights, making it easier to manage congestion, optimize road usage, and improve public safety. With AI-powered detection, heatmap visualization, and movement tracking, authorities could make data-driven decisions to reduce traffic jams and enhance urban mobility.
Deliverables
AI-Powered Vehicle Detection System
Built a computer vision solution that identifies and counts vehicles in real-time, even from wide-angle and aerial CCTV footage.
Heatmap Generation Module
Visualized traffic density and hotspots to support better decision-making in traffic management and planning.
Movement Pattern Tracking
Implemented directional flow analysis to monitor how vehicles move and where bottlenecks occur.
Scalable & Cloud-Ready Architecture
Designed the system to be easily deployable across large urban areas with seamless integration into existing traffic control infrastructure.
