The Vehicle Flow Statistics
AI Camera is an intelligent device that utilizes artificial intelligence technology and advanced image recognition algorithms to monitor count the traffic flow on roads. Below is a detailed introduction to it:
Working Principle
Target Detection: The camera captures real-time video images of the road, uses deep learning algorithms and image processing techniques to identify vehicles in the video frames. These algorithms have undergone extensive training and can accurately identify various types of vehicles, regardless their color, shape, or type. Even in complex traffic scenarios, such as when vehicles are blocking each other or when the light changes, the camera can maintain high accuracy rate.
Vehicle Tracking: Once a vehicle is detected, the camera tracks the vehicle's movement across different frames, recording its trajectory. This typically involves multi tracking algorithms, such as SORT and DeepSORT, combined with Kalman filters for state prediction and update. This allows the camera to accurately track each vehicle's driving, ensuring that the same vehicle is neither counted twice nor missed in the entire video segment.
Traffic Statistics: When a vehicle passes through a pre-set monitoring area or coil, the algorithm detects the change in the vehicle's position and uses this information to count the number of vehicles, their speed, and direction. A virtual coil a line or curve defined in the road area of the video frame, usually perpendicular to the lane direction. When a vehicle crosses the virtual coil, it is counted.
Features
High Precision Statistics: It can provide accurate traffic flow data, offering reliable support for traffic management departments and related research institutions. Compared to traditional manual counting simple sensor-based methods, the AI camera's results are more precise, significantly reducing errors.
All-Weather Operation: It is not affected by environmental factors such as and light. Whether it's day or night, sunny or rainy, the camera can operate normally, continuously monitoring and counting the traffic flow on the road.
Real Data: It can obtain traffic flow information in real-time and transmit the data to the traffic management center or other related systems. This allows managers to promptly understand the conditions on the road, quickly make decisions, and take appropriate measures.
Vehicle Type Recognition: In addition to counting the number of vehicles, it can also identify different of vehicles, such as small cars, large buses, trucks, and motorcycles. This provides a more comprehensive analysis of the traffic composition and characteristics, offering more detailed for traffic planning and management.
Application Scenarios
Traffic Management: Assists traffic management departments in real-time monitoring of road traffic flow. Based on traffic data, it timely adjusts duration of traffic signals, optimizes traffic organization at intersections, improves road passage efficiency, and alleviates traffic congestion.
Urban Planning: Provides crucial data support for urban departments, which is used to evaluate road capacity, plan new road construction, and optimize public transportation routes.
Commercial Decision-making: For commercial venues such as shopping, supermarkets, and parking lots, the AI camera traffic counting can help managers understand the arrival and departure of customers, optimize parking lot management, and reasonably arrange commercial.