US 12,008,883 B2
Alarm-based prevention and control method, internet of things system, and medium for safety risk of smart gas
Zehua Shao, Chengdu (CN); Yaqiang Quan, Chengdu (CN); Yuefei Wu, Chengdu (CN); and Bin Liu, Chengdu (CN)
Assigned to CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Chengdu (CN)
Filed by CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Sichuan (CN)
Filed on Sep. 11, 2023, as Appl. No. 18/465,127.
Claims priority of application No. 202310898714.8 (CN), filed on Jul. 21, 2023.
Prior Publication US 2023/0419811 A1, Dec. 28, 2023
Int. Cl. G08B 21/12 (2006.01); F24F 11/30 (2018.01); G08B 21/24 (2006.01)
CPC G08B 21/12 (2013.01) [F24F 11/30 (2018.01); G08B 21/24 (2013.01)] 6 Claims
OG exemplary drawing
 
1. An alarm-based prevention and control method for a safety risk of smart gas, performed by a smart gas safety management platform of an alarm-based prevention and control Internet of Things (IoT) system for a safety risk of smart gas, comprising:
obtaining gas monitoring data based on a data acquisition instruction, and determining whether a gas leakage occurs;
in response to a determination that the gas leakage occurs, generating a control instruction based on a fan operation strategy to control operation of a fan, and obtaining the gas monitoring data under the fan operation strategy, the fan being configured to remove leaking gas and assist in determining a type of the gas leakage; and
generating a notification instruction based on the gas monitoring data in conjunction with an operating strategy of an indicator light, and controlling the indicator light to issue an alarm notification based on the notification instruction; the type of the gas leakage including a continuous leakage and an occasional leakage; wherein the fan being configured to remove leaking gas and assist in determining a type of the gas leakage includes:
determining 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, the type determination model including an extraction layer and a determination layer; the extraction layer being configured to determine gas concentration change characteristics by processing the gas monitoring data of the at least one time point, wherein the gas concentration change characteristics include a change rate of gas concentration and a change range of gas concentration; and the determination layer being 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; and
determining, 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 frequency and a flicker state; wherein a gas concentration characteristics value is determined 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; the flicker frequency is determined based on the gas concentration characteristics value; a confidence level of the flicker frequency is determined based on the fan operation strategy; and the flicker frequency is adjusted based on the confidence level.