Methods, systems, and storage media for emergency supervision of open flame areas in smart cities based on internet of things large models

A method for emergency supervision of an open flame area in a smart city based on an Internet of Things (IoT) large model, the method being executed by an emergency supervision management platform, and the method comprising:

• determining a first hazardous area based on a gas output flow rate of at least one gas storage tank and a gas usage flow rate of at least one gas device in at least one area;
• generating an Unmanned Aerial Vehicle (UAV) acquisition command based on the first hazardous area;
• controlling a UAV to travel to the first hazardous area based on the UAV acquisition command, and acquiring a device image sequence;
• determining, based on the device image sequence, a flame feature through a feature recognition large model, wherein the feature recognition large model is a machine learning model;
• determining an explosion risk of the first hazardous area based on the flame feature and an air flow rate;
• and
• determining a valve closure command based on the explosion risk, and closing a target valve based on the valve closure command.

A non-transitory computer-readable storage medium, storing computer instructions, wherein when a computer reads the computer instructions in the storage medium, the computer executes a method for emergency supervision of an open flame area in a smart city based on an Internet of Things (IoT) large model, the method being executed by an emergency supervision management platform and comprising:

• determining a first hazardous area based on a gas output flow rate of at least one gas storage tank and a gas usage flow rate of at least one gas device in at least one area;
• generating an Unmanned Aerial Vehicle (UAV) acquisition command based on the first hazardous area;
• controlling a UAV to travel to the first hazardous area based on the UAV acquisition command, and acquire a device image sequence;
• determining, based on the device image sequence, a flame feature through a feature recognition large model, wherein the feature recognition large model is a machine learning model;
• determining an explosion risk of the first hazardous area based on the flame feature and an air flow rate;
• and
• determining a valve closure command based on the explosion risk, and closing a target valve based on the valve closure command.