Employee working condition monitoring method and device, computer device and storage medium

Abstract

The invention relates to the machine learning in artificial intelligence, and provides an employee working condition monitoring method and device, a computer device and a storage medium. The method comprises the following steps of obtaining a staff working video, and intercepting video pictures from the staff working video at preset time intervals; obtaining an employee face image according to thevideo picture, and determining a corresponding employee identifier according to the employee face image; obtaining micro-expression characteristics according to the employee face image, inputting themicro-expression characteristics into a trained micro-expression recognition model for recognition to obtain micro-expression output characteristics, and obtaining corresponding micro-expressions according to the micro-expression output characteristics; determining an employee emotion state corresponding to the employee identifier according to the micro expression, obtaining an employee emotion state vector according to the employee emotion state, and inputting the employee emotion state vector into a trained risk early warning model to obtain a risk output vector; and obtaining a risk earlywarning level of the employee identifier according to the risk output vector. By adopting the method, the efficiency and the accuracy can be improved.

Description

technical field [0001] The present application relates to the technical field of the Internet, in particular to a method, device, computer equipment and storage medium for monitoring employee working conditions. Background technique [0002] In the current employee management of enterprises, it is rare to pay attention to the emotional changes of each employee. Employees of enterprises often have emotional changes due to work pressure, which leads to employee resignation or other unexpected events, resulting in the loss of talents and affecting the normal production and operation of the enterprise. Usually, enterprises only understand the working status of employees through face-to-face communication with long intervals, but cannot understand the working status of employees in real time, which is inefficient, and cannot accurately understand the emotional changes of employees through face-to-face communication, which is inaccurate. Contents of the invention [0003] Based...

AI Technical Summary

Problems solved by technology

Employees often have emotional changes due to work pressure, which leads to employee resignation or other unexpected events, which causes the loss of talents and affects the normal production and operation of the enterprise.

Usually, enterprises only understand the working status of employees through face-to-face communication with long intervals, and cannot understand the working status of employees in real time, which is inefficient. Moreover, it is impossible to accurately understand the emotional changes of employees through face-to-face communication, which is inaccurate.

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