An alarm-based prevention and control Internet of Things (IoT) system for a safety risk of smart gas, wherein the IoT system includes a smart gas user platform, a smart gas service platform, a smart gas safety management platform, a smart gas indoor equipment sensor network platform, and a smart gas indoor equipment object platform, wherein
- the smart gas user platform includes a plurality of smart gas user sub-platforms;
- the smart gas service platform includes a plurality of smart gas service sub-platforms;
- the smart gas safety management platform includes a plurality of smart gas indoor safety management sub-platforms and a smart gas data center;
- the smart gas indoor equipment sensor network platform is configured to interact with the smart gas data center and the smart gas indoor equipment object platform;
- the smart gas indoor equipment object platform is configured to obtain gas monitoring data based on a data acquisition instruction;
- the smart gas safety management platform is configured to obtain the gas monitoring data from the smart gas data center and determine whether a gas leakage occurs;
- in response to a determination that the gas leakage occurs, generate, based on a fan operation strategy, a control instruction to control operation of a fan, and obtain the gas monitoring data under different fan operation strategies, the fan being configured to remove leaking gas and assist in determining a type of the gas leakage;
- generate a notification instruction based on the gas monitoring data in conjunction with an operating strategy of an indicator light;
- and transmit the notification instruction to the smart gas service platform via the smart gas data center;
- the type of the gas leakage including a continuous leakage and an occasional leakage;
- the smart gas safety management platform is further configured to determine the type of the gas leakage by processing the fan operation strategy, an operating condition of the indicator light, and the gas monitoring data of at least one time point through a type determination model, the type determination model being a machine learning model;
- wherein the type determination model includes an extraction layer and a determination layer;
- the extraction layer is configured to determine gas concentration change characteristics by processing the gas monitoring data of the at least one time point;
- the gas concentration change characteristics including a change rate of gas concentration and a change range of gas concentration;
- and the determination layer is configured to determine the type of the gas leakage by processing the fan operation strategy, the operating condition of the indicator light, and the gas concentration change characteristics;
- the smart gas safety management platform is further configured to determine, based on the gas concentration, the gas concentration change characteristics, and historical gas leakage data, the operating strategy of the indicator light by a preset manner;
- the preset manner including a table looking up manner and a vector match manner;
- wherein the operating strategy of the indicator light includes a flicker state and a flicker frequency;
- the smart gas safety management platform is further configured to:
- obtain a gas concentration characteristics value based on a weighted sum of an influence degree of the gas concentration on the flicker frequency and an influence degree of the gas concentration change characteristic on the flicker frequency;
- determine the flicker frequency based on the gas concentration characteristics value;
- determine a confidence level of the flicker frequency based on the fan operation strategy;
- and adjust the flicker frequency based on the confidence level;
- and
- the smart gas service platform is configured to upload the notification instruction to the smart gas user platform, and the smart gas user platform issues an alarm notification based on the notification instruction.