Emergency Security: AI Vision for Perimeter Intrusion Detection

In the field of emergency security, perimeter intrusion detection is of great importance. WeLinkirt provides a reliable solution for perimeter safety with advanced AI vision technology.

User Scenario: A leading emergency security manufacturer is responsible for the perimeter security protection of multiple important sites. The main process in its production line is to monitor the perimeter area in real-time and detect whether there are any personnel climbing over or intruding. The detection objects are the perimeter fence and the personnel activities in the surrounding area. The manufacturer needs to ensure that intrusion behaviors can be accurately detected in various complex environments, such as at night or in bad weather, to guarantee the safety of the sites.

Pain Points: Traditional perimeter monitoring systems have many problems. Firstly, the miss-detection rate is relatively high. In complex environments, such as insufficient light or with obstructions, intrusion behaviors are easily missed, with a miss-detection rate of about 5%. Secondly, false alarms are serious. Wind blowing branches or animals passing by can trigger alarms, and the false-alarm rate is as high as 30%. This not only increases the workload of security personnel but may also cause real intrusion behaviors to be ignored. In addition, traditional systems are difficult to adapt to different perimeter environments and monitoring requirements, and the model change time is long. Usually, it takes hours or even days to adjust parameters and models, seriously affecting work efficiency.

Technical Principle

WeLinkirt uses advanced AI vision algorithms to solve the problem of perimeter intrusion detection. Its core algorithm is based on deep-learning object detection and behavior recognition technology. Through training with a large amount of sample data, the model can accurately identify the characteristics and behavior patterns of personnel. In terms of imaging, high-definition cameras are combined with intelligent image enhancement technology, so that clear images can be obtained even under low-light or bad-weather conditions. In hardware, high-performance computing devices are used to ensure that the algorithm can run in real-time and process image data quickly. This combination of technologies is effective because the deep-learning model has strong feature extraction and classification capabilities, which can accurately identify personnel and their behaviors from complex images. The intelligent image enhancement technology compensates for the impact of environmental factors on imaging and ensures the image quality. The support of high-performance hardware enables the entire system to respond in real-time and detect intrusion behaviors in time.

• Deep-learning object detection: Identify and locate objects in the image through a convolutional neural network.
• Behavior recognition technology: Analyze the actions and trajectories of personnel to determine whether it is an intrusion behavior.
• Intelligent image enhancement: Improve the clarity and contrast of the image and enhance the visibility of the target.
• High-performance computing hardware: Ensure the real-time operation and data processing of the algorithm.

WeLinkirt Solution and Product Introduction

WeLinkirt provides the SkyVision 0-code video monitoring AI platform. This platform has the ability to train its own model on site within hours. Users do not need to have professional programming knowledge and can quickly train a suitable model according to different perimeter environments and monitoring requirements. In the implementation, high-definition cameras are first installed in the perimeter area, and the video data is transmitted to the SkyVision platform. The platform uses advanced algorithms to analyze the video in real-time, identify intrusion behaviors and issue alarms in time. At the same time, the platform also supports 100% local private deployment, and the data does not leave the factory, ensuring data security.

The SkyVision platform enables perimeter monitoring to change from 'seeing' to 'understanding'.

Quantitative Results: After using the WeLinkirt solution, the emergency security manufacturer has achieved remarkable results. The detection rate has been greatly improved, reaching 98%, and the miss-detection rate has been reduced to 2%. The false-alarm rate has also been significantly reduced to 5%, a reduction of about 83%. The model change time has been shortened from hours or even days to less than 1 hour, greatly improving work efficiency.