Once the site illegal hot work detection system finds abnormal fireworks or fire conditions, the system will quickly issue an early warning to make up for the lack of manpower inspection. The application of the illegal hot work detection system on the construction site not only greatly improves the efficiency and accuracy of fire prevention and control, but also reduces the losses caused by fire to a large extent, and provides a safer working environment for construction site workers. The core of the construction site illegal hot work detection system lies in AI artificial intelligence machine vision analysis and recognition technology. Through deep learning and image recognition algorithms, the system can automatically identify pyrotechnic anomalies and fire conditions in the monitoring screen.
On a busy jobsite, safety is a top priority. However, due to various reasons, fire accidents occur from time to time, which poses a serious threat to the safety of people's lives and property. In order to solve this problem, a construction site illegal hot work detection system based on AI artificial intelligence machine vision analysis and recognition technology came into being. In short, the detection system of illegal hot work on construction site based on AI artificial intelligence machine vision analysis and recognition technology plays an increasingly important role in fire prevention and control.
There are also many advantages to the application of the detection system for illegal hot work on construction sites. First of all, the illegal hot work detection system on the construction site can achieve 24-hour uninterrupted monitoring, which makes up for the lack of manpower inspection. Secondly, the system has a high degree of intelligence and adaptability, once an abnormality is found, the system will immediately send out an alarm and automatically link the fire fighting facilities to extinguish the fire. This process requires no human intervention, effectively avoiding fire accidents caused by human negligence or untimely response. It can be intelligently adjusted and optimized according to different scenarios and environments, which improves the accuracy and efficiency of fire prevention and control. Finally, the cost of the system is relatively low, and it can realize the return in a short time, with good economic and social benefits.