Vehicle Flow Counting
Using AI & Computer Vision

Challenge

Design an AI-powered system that can accurately count the number of vehicles passing through a designated area, using computer vision techniques. The system should be able to process real-time video streams and generate statistical reports on vehicle flow rates, direction, and other relevant metrics. The solution should be scalable, modular, and easily adaptable to different types of environments and traffic patterns. The system should also have a user-friendly interface for visualization and data analysis.

Solution

As part of our research and development efforts, we tackled the challenge of vehicle flow counting using AI and computer vision. To achieve this, we leveraged OpenCV, an open-source computer vision library, and developed a user interface and server to handle the processing and analysis of the captured video data.

The vehicle flow counting system we developed involves a camera that captures video footage of the target area, which is then processed and analyzed using OpenCV algorithms. The processed data is then displayed in real-time through the user interface, providing valuable insights into vehicle flow patterns.

By using computer vision and AI, we were able to achieve accurate vehicle flow counting, reducing the need for manual counting and improving the overall efficiency of traffic management systems. This POC project demonstrates the potential of these technologies to revolutionize traffic management and transportation systems.