Restaurant kitchen safety detection method based on edge calculation

Abstract

The invention provides a restaurant kitchen safety detection method based on edge computing, and the method comprises the steps: indicating different cameras to shoot the entrance and exit of a restaurant kitchen and the internal environment through an edge computing platform terminal, and obtaining the state information of people entering and exiting and the activity state information of people in and out; therefore, the access control open state and the alarm equipment working state of the kitchen of the restaurant are adjusted; the gas sensor is indicated to obtain the internal environment air component information of the restaurant kitchen so as to adjust the working state of ventilation equipment of the restaurant kitchen, multi-angle camera monitoring and air component monitoring are conducted on the restaurant kitchen, it is ensured that only authorized personnel can enter the kitchen, and operation of personnel in the kitchen is normative; therefore, the operation orderliness in the kitchen is improved, accidents such as fire disasters in the kitchen are avoided, and the operation environment and safety of the kitchen are improved to the maximum extent.

Description

technical field [0001] The invention relates to the technical field of restaurant monitoring and management design, in particular to a restaurant kitchen safety detection method based on edge computing. Background technique [0002] The internal environment of the restaurant's back kitchen is complex, and ingredients such as ingredients are stored. The safety of the restaurant's back kitchen is directly related to the normal operation of the restaurant as a whole. In the prior art, a camera is usually set in the back kitchen of a restaurant to obtain a real-time image of the internal operating state of the back kitchen, and whether the operating state of the back kitchen is normal or not is judged by manual inspection. The above method cannot effectively cover the entire area of ​​the restaurant rear kitchen, and cannot perform timely and automatic monitoring of the restaurant rear kitchen, thereby reducing the safety and reliability of the restaurant rear kitchen operation....

AI Technical Summary

Problems solved by technology

The above method cannot effectively cover the entire area of ​​the restaurant back kitchen, and cannot conduct timely and automatic monitoring of the restaurant back kitchen, thereby reducing the safety and reliability of the restaurant back kitchen operation

Images