AI INTELLIGENT VISUAL RECOGNITION SYSTEM
AI-powered video analytics has emerged as a hot topic in the surveillance industry, with high expectations surrounding its potential. Real-time monitoring and reviewing video footage remain challenging, especially when handling large-scale camera networks. Traditional manual methods not only prove inefficient but also risk missing critical details, requiring substantial human resources. By employing sophisticated algorithms, AI-driven video analysis processes video streams with pixel-level precision, ensuring near-complete coverage of all visual information.
System features
The algorithm is rich in monitoring scenarios, including human body detection,face detection, posture detection, wearable tool detection, vehicle detection,environment detection, price- related detection, etc., covering more than 100 kinds of behavior scenarios and target algorithms;
The functional services provide data services, file services, data reports, map display, voice broadcast, video services, voice alarm prompts, wechat mini program push, remote video playback and other functions;
One-click deployment means that there is no need to modify the existing equipment. It only needs to add Al edge computing servers in the existing monitoring network to complete the AI transformation and upgrade;
Data Big Screen Visualization AI monitoring supports Web big screen display,Web report, WeChat mini program and voice broadcast and other data presentation methods.
System functions
Object detection
It is a form of computer vision that can recognize objects in images or videos and locate them. Object recognition can use this identification and positioning method to calculate items in a scene and determine and label their exact positions.
Object recognition
Object recognition is a form of computer vision that identifies objects in images or videos. The primary outcomes of deep learning and machine learning algorithms are object recognition systems. Much like how humans can quickly spot and identify people, objects, and scenes when viewing images or movies, these technologies enable rapid visual analysis.
target following
Object tracking is an important subject in the field of machine vision, which is widely used in intelligent monitoring, action and behavior analysis, autonomous driving and other applications. For example, in a football match, the object is not only a person, but also a biological, a car or other important objects, such as a football.
Real-time video analysis
The camera system generates massive video data, and manual review of stored footage is sometimes impossible for incident handling. This necessitates AI-powered recognition and analysis to detect critical surveillance information such as perimeter intrusions,dangerous conduct, fireworks displays, suspicious individuals, and other anomalies.
Trigger real-time alerts
AI responds to abnormal behavior detected in video images, such as sending alerts to administrators. Video recognition technology improves situational awareness. Some examples include:
Alarms based on similar appearance: Video surveillance can customize alarms according to the needs of similar physical appearance, such as dangerous object detection, fire detection, etc.
Count-based alarm: An alarm can be triggered when a certain number of objects (vehicles or people) are detected at a predetermined location within a given time period.
Face recognition alarm: relevant departments can quickly identify criminals and issue alarm in real time according to the information extracted from video images.
