Industrial safety
Safety in the production is extremely important, directly related to preserving the life and health of workers, as well as reducing the likelihood of damage to the environment.
Also, safe production reduces the costs associated with the consequences of accidents, the treatment of injuries, fines, and the elimination of consequences.
In addition, safe production has a good reputation among both potential employees and government agencies.

How it works

Machine learning and neural networks can be used to control security at various stages of production and beyond.
For example, the use of computer vision to automatically track the presence of uniforms (helmets, vests, safety belts), control the presence of people in the danger zone, observe safety precautions when unloading, unloading, etc.

When facts of safety violations are detected, sound, light or other alarms can be turned on, machines and mechanisms can be forcibly stopped. All violations are recorded in a journal for further analysis and the sanctions provided for by it.

Analysis of hazardous conditions such as temperature, pressure, speed, etc., and most importantly, predict possible hazardous conditions before they occur.

Monitor workers for workplace safety violations such as wearing goggles and other protective items.

Training employees on safety rules at work and timely response to possible hazards.

Usually, systems based on computer vision and neural networks are used to control safety in production, but motion, vibration, sound, and other sensors can also be used.

Security of equipment for possible breakdowns or failures.

Examples of using

The system is taught to recognize certain situations. For example, a head without a helmet, a body without insurance, the presence of people in the movement zone of an overhead crane or other dangerous area, etc.

Medical mask recognition