The selection points you need to know about the helmet identification system

The safety helmet identification system can identify whether workers are wearing safety helmets in the construction scene, which is a strong guarantee for safe production.There are many helmet identification systems on the market, and how to choose depends on which points.

It is critical for a good system to do the same job with minimal cost.So where should the cost savings be?First, optimize the system algorithm. The configured server does not need GPU, but only needs CPU to run the system.Second, the existing resources at the construction site, such as front-end cameras, can be utilized.Through the optimization of these algorithms and the reduction of external hardware, the deployment cost is greatly reduced.

Scenarios on construction sites are often complex and large-scale, and omissions are inevitable through manpower.For the large-scale supervision requirements of such a large-scale scene, we need a hard hat identification system that can access multi-channel video for large-scale analysis.Multiple construction sites are arranged with multiple cameras to achieve large-scale supervision without dead ends. Dozens of video lines can be connected to one host for large-scale analysis, which perfectly solves our application needs.

In the construction site, there is not only the supervision of wearing helmets, but also fire prevention, smoke prevention, and intrusion into dangerous areas, which will lead to safety problems.Each is deployed separately, the cost is undoubtedly huge, and it is difficult to manage, and the idea of ​​​​we want to facilitate security management upside down.The Hard hat wearing recognition system can be concurrent with other recognition algorithms. The algorithm can be set according to the needs. One camera can concurrently have multiple algorithms, and users can freely mix and match, which is a function that a good supervision system needs to have.

The most basic requirement of the helmet recognition system is the recognition accuracy.For artificial intelligence to identify different construction scenarios, training and deep learning are required.Each company has its own training model. An excellent training model can reduce the number of samples required by a system, reduce learning time, improve development efficiency, and achieve high-precision recognition.

The multi-channel alarm method of the helmet identification system can flexibly remind supervisors to conduct on-site inspections and corrections.When the system finds that someone is not wearing a helmet, the system can push WeChat messages in real time, alarm light alarms, voice alarms at points, local voice alarms, and various channel alarm methods, and can also perform linkage alarms to remind the person in charge to carry out safety management., to prevent the occurrence of safety accidents.

In addition to this, the helmet identification system should also have some other functions.Real-time alarm: Real-time analysis of surveillance video, timely processing of violations to avoid causing greater harm; flexible deployment: support local physical machines, virtual machines, cloud and other deployment methods; efficient computing: software recognition speed is millisecond level, supportDeformed image preprocessing can be accurately identified at a long distance, and the analysis interval can also be set; integrated management: upload the scattered analysis data to the web platform, which is convenient for users to view and manage.

With this in mind, you can choose a helmet identification system that is right for you.

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