Gas leakage precision detection and rapid linkage early warning response system based on internet of things

Abstract

This invention provides an IoT-based accurate gas leak detection and rapid emergency response system, relating to the field of IoT technology. It includes: a data acquisition module for collecting detection data sent by a smart base; a data analysis module for analyzing the detection data to determine whether an emergency response is triggered; and an emergency response module for generating and executing an emergency response task when triggered. This IoT-based accurate gas leak detection and rapid emergency response system enables accurate detection of gas leaks and rapid emergency handling after a gas leak occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly relates to a precise gas leakage detection and rapid linkage warning response system based on the Internet of Things. Background Art

[0002] Although most modern families transport gas to each household through gas pipelines, liquefied gas cylinders are still widely used gas supply devices, providing energy support for cooking (for example: food stalls making fried rice, etc.), hot water supply and other needs. Especially in old communities without planned gas pipelines, liquefied gas cylinders are still used as the main gas storage tools. The leakage of household liquefied petroleum gas is likely to cause major safety accidents. Therefore, precise leakage detection of gas and how to quickly respond after gas leakage are technical problems that need to be solved urgently. Summary of the Invention

[0003] One of the purposes of the present invention is to provide a precise gas leakage detection and rapid linkage warning response system based on the Internet of Things to achieve precise detection of gas leakage and rapid emergency treatment after gas leakage.

[0004] A precise gas leakage detection and rapid linkage warning response system based on the Internet of Things provided by an embodiment of the present invention includes: a data acquisition module for acquiring detection data sent by a smart base; A data analysis module for analyzing the detection data to determine whether to trigger a linkage warning response; A linkage response module for generating and executing a linkage warning response task when a linkage warning response is triggered.

[0005] Preferably, the data analysis module analyzes the detection data to determine whether to trigger a linkage warning response, including: Analyzing the detection data to determine the gas concentration in the environment where the smart base is located; When the gas concentration is greater than or equal to a preset first threshold, triggering a linkage warning response; And / or, When the gas concentration is greater than or equal to a preset second threshold and shows an upward trend, triggering a linkage warning response.

[0006] Preferably, when a linkage warning response is triggered, the linkage response module generates and executes a linkage warning response task, including: Based on the positioning data of the smart base, determining the task target location of the linkage response task; Based on the identification code of the smart base, determining the pre-configured and managed user terminals and users; Based on the task target location, determining the parties and their terminals participating in the linkage warning response task; The task target location is used as the task target of the joint early warning and response task, the user terminal and various parties' terminals are used as communication terminals, and the personnel of various parties and users are used as joint staff to build the joint early warning and response task.

[0007] Preferably, the IoT-based gas leak precision detection and rapid linkage early warning response system also includes: a risk classification module, used to conduct risk assessment of the task target and determine the risk level when the linkage early warning response is triggered; Among them, the risk level is used to guide the construction of joint early warning and response tasks; The risk grading module assesses the risks to the task objectives and determines the risk level, including: Retrieve environmental description data associated with the smart dock; Send supplementary environment description queries to the user terminal and receive supplementary data sent by the user terminal; Feature extraction is performed on environmental description data, supplementary data, and detection data. Based on the extracted feature parameters and a pre-configured risk assessment library, the risk level is determined.

[0008] Preferably, the IoT-based gas leak precision detection and rapid linkage early warning response system also includes: The detection and control module is used to adjust the time interval for the data acquisition module to collect the detection data sent by the smart base according to the current state of the smart base. The detection and control module performs the following operations: When the current state of the smart base is the gas cylinder replacement reminder stage, the detection data is collected at a preset first time interval. When the current state of the smart base is the initial stage of using a new gas cylinder, the detection data is collected at a preset second time interval. The first time interval is longer than the second time interval.

[0009] Preferably, the detection and control module also performs the following operations: When the current state of the smart base is the continuous gas discharge stage of the gas cylinder, the detection data is collected using a preset third time interval. When the current state of the smart base is when the gas cylinder stops discharging gas, the detection data is collected using a preset fourth time interval. The third time interval is shorter than the fourth time interval.

[0010] Preferably, the emergency response point analysis and construction module is used to analyze the distribution and usage of smart base stations and construct emergency response points; The emergency response point analysis and construction module analyzes the distribution and usage of smart base stations to construct emergency response points, including: A distribution map is constructed based on the distribution of smart bases; Based on usage data, the smart bases within the distribution map are filtered to identify valid targets; Identify points on the distribution map that can be recommended as emergency response points as analysis points; Based on the effective targets and the positional relationships between the analysis points, at least one location is determined from the analysis points as the location for constructing an emergency response point.

[0011] Preferably, based on effective targets and the positional relationships between analysis points, at least one location is determined from the analysis points as a location for constructing an emergency response point, including: Using the line connecting the two outermost smart bases as the baseline, starting from the position of any smart base at either end of the baseline, the points on the baseline at the preset first distance are used as reference points. Centered on the analysis point with the smallest distance from the reference point, the smart bases within a preset second distance are statistically analyzed. When the statistical data meets the preset conditions, an emergency response point is constructed at the analysis point, and the area where the smart bases corresponding to the statistical data are distributed is taken as the emergency response area corresponding to the emergency response point. When the statistical data does not meet the preset conditions, the reference point is moved by a preset first step length, and the analysis point is reselected for analysis. Remove the emergency response area from the distribution map, move the reference point by the preset second step size, reselect the analysis point for analysis, and when the reference point moves to the other end of the baseline, reselect the baseline and perform the analysis of the reference point; until all the smart bases on the distribution map are removed.

[0012] Preferably, the smart base stations within the distribution map are filtered based on usage to determine valid targets, including: Feature extraction is performed on usage data to construct a usage dataset; Usage evaluation is performed based on a pre-configured usage evaluation library and usage dataset; When the evaluation is greater than or equal to the preset threshold, the smart base is considered a valid target; When the usage evaluation is less than a preset threshold, find the nearest smart base with the same usage evaluation less than the preset threshold, accumulate the usage evaluation, and when the accumulated evaluation is greater than or equal to the preset threshold, calculate the center point based on the position of the smart base participating in the accumulation, construct a virtual target at the center point and use it as a valid target.

[0013] Preferably, the intelligent base includes: a main body, a weighing module, a gas detection module, a display module, an identification module, a processing module, and a communication module disposed on the upper surface of the main body; The weighing module, gas detection module, display module, identification module, and communication module are all electrically connected to the processing module.

[0014] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of an IoT-based accurate detection and rapid linkage early warning response system for gas leaks, as described in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the construction of a coordinated early warning task in an embodiment of the present invention; Figure 3 This is a schematic diagram of the appearance of the smart base in an embodiment of the present invention; Figure 4 This is a schematic diagram showing the connection of the various components of the smart base in an embodiment of the present invention; Figure 5 This is an external view of an intelligent base with gas detection and weighing functions according to an embodiment of the present invention; Figure 6 This is a schematic diagram showing the installation position of the sleeve in an embodiment of the present invention. Detailed Implementation

[0017] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0018] This invention provides an IoT-based system for accurate detection and rapid early warning response of gas leaks, such as... Figure 1 As shown, it includes: a data acquisition module 1-1, used to acquire detection data sent by the smart base; Data analysis modules 1-2 are used to analyze the detection data and determine whether a linkage early warning response is triggered. Linkage response modules 1-3 are used to generate and execute linkage warning response tasks when a linkage warning response is triggered.

[0019] The gas leakage precise detection and rapid linkage early warning response system based on the Internet of Things according to the present invention relies on a smart base. As an Internet of Things terminal device, when a user daily uses a liquefied gas cylinder, the liquefied gas cylinder is placed on the smart base. The weighing sensor and gas detection sensor on the smart base conduct detections to obtain detection data, which is uploaded to the system through the Internet of Things. The system analyzes the detection data to determine whether an abnormality occurs and conducts a linkage early warning response, realizing multi-level linkages among the user side, the community, the gas company, and the emergency department, and further realizing the precise detection of gas leakage and the rapid emergency treatment after gas leakage.

[0020] In one embodiment, the data analysis module analyzes the detection data to determine whether to trigger a linkage early warning response, including: Analyze the detection data to determine the gas concentration in the environment where the smart base is located; When the gas concentration is greater than or equal to a preset first threshold, trigger a linkage early warning response; And / or, When the gas concentration is greater than or equal to a preset second threshold and shows an upward trend, trigger a linkage early warning response.

[0021] This embodiment provides the situations for triggering a linkage early warning response: the detected gas concentration is greater than or equal to the first threshold (0.15%Vol (1500 ppm / 7.5%LEL)), which is the direct alarm limit. This embodiment also provides a predicted alarm limit to make the early warning more intelligent and provide more time for response, that is, when it is greater than or equal to the second threshold (0.5 to 0.95 times the first threshold), for N (3 to 10 data samplings) consecutive data, and each data increases, it is determined to show an upward trend, and the triggering of a linkage early warning response can be directly carried out.

[0022] To realize the construction of a linkage early warning response task, as Figure 2 shown, when a linkage early warning response is triggered, the linkage response module generates and executes a linkage early warning response task, including: Based on the positioning data of the smart base, determine the task target location of the linkage response task; Based on the identification code of the smart base, determine the user side and the user pre-configured and managed; Based on the task target location, determine the parties and their terminals participating in the linkage early warning response task; Take the task target location as the task target of the linkage early warning response task, take the user side and each terminal as the communication terminals, and take each party and the user as the linkage working staff to construct a linkage early warning response task.

[0023] The participants include: gas company, community, and emergency response department; the emergency response department mainly consists of personnel assigned to emergency response points corresponding to the target locations of the mission. In one embodiment, the IoT-based gas leak precision detection and rapid linkage early warning response system further includes: a risk classification module, used to perform risk assessment on the task target and determine the risk level when the linkage early warning response is triggered; Among them, the risk level is used to guide the construction of joint early warning and response tasks; The risk grading module assesses the risks to the task objectives and determines the risk level, including: Retrieve environmental description data associated with the smart dock; Send supplementary environment description queries to the user terminal and receive supplementary data sent by the user terminal; Feature extraction is performed on environmental description data, supplementary data, and detection data. Based on the extracted feature parameters and a pre-configured risk assessment library, the risk level is determined.

[0024] The risk grading module in this embodiment grades the risk of the tasks corresponding to the linkage early warning response, thereby determining the difference in the number of personnel required when constructing the task. That is, the higher the risk level, the more personnel are required. In addition, a medical group can be configured. When the risk level is high enough, the medical group will join the linkage early warning response.

[0025] In one embodiment, the IoT-based gas leak detection and rapid early warning response system further includes: The detection and control module is used to adjust the time interval for the data acquisition module to collect the detection data sent by the smart base according to the current state of the smart base. The detection and control module performs the following operations: When the smart base is in the gas cylinder replacement reminder stage, the detection data is collected at a preset first time interval. During this stage, the amount of gas in the gas cylinder is relatively small, and the probability of a major safety accident is relatively low, so the data collection frequency is reduced. When the smart base is in the initial stage of using a new gas cylinder, the detection data is collected at a preset second time interval; when a new gas cylinder is replaced, the risk of leakage is higher due to the reconnection of the pressure reducing valve, etc., so the data sampling frequency is increased. The first time interval is longer than the second time interval.

[0026] To further optimize the allocation of IoT data transmission resources, the detection and control module also performs the following operations: When the current state of the smart base is the continuous gas cylinder discharge stage, the detection data is collected at the preset third time interval; continuous gas discharge indicates that the gas cylinder is in use, which is a high risk and requires increasing the data sampling frequency. When the current state of the smart base is that the gas cylinder has stopped discharging gas, the detection data is collected at the preset fourth time interval; the cessation of gas discharging indicates that the gas cylinder has stopped being used, the risk is low, and the data sampling frequency needs to be reduced. The third time interval is shorter than the fourth time interval.

[0027] In order to enable the rapid linkage and early warning response tasks of users corresponding to each smart base; in one embodiment, an emergency response point analysis and construction module is used to analyze the distribution and usage of smart bases and construct emergency response points; The emergency response point analysis and construction module analyzes the distribution and usage of smart base stations to construct emergency response points, including: A distribution map is constructed based on the distribution of smart bases; Based on usage data, the smart bases within the distribution map are filtered to identify valid targets; Identify points on the distribution map that can be recommended as emergency response points as analysis points; Based on the effective targets and the positional relationships between the analysis points, at least one location is determined from the analysis points as the location for constructing an emergency response point.

[0028] Specifically, based on effective targets and the positional relationships between analysis points, at least one location is determined from the analysis points as the location for constructing an emergency response point, including: Using the line connecting the two outermost smart bases as the baseline, starting from the position of any smart base at either end of the baseline, the points on the baseline at the preset first distance are used as reference points. Centered on the analysis point with the smallest distance from the reference point, the smart bases within a preset second distance are statistically analyzed. When the statistical data meets the preset conditions, an emergency response point is constructed at the analysis point, and the area where the smart bases corresponding to the statistical data are distributed is taken as the emergency response area corresponding to the emergency response point. When the statistical data does not meet the preset conditions, the reference point is moved by a preset first step length, and the analysis point is reselected for analysis. Remove the emergency response area from the distribution map, move the reference point by the preset second step size, reselect the analysis point for analysis, and when the reference point moves to the other end of the baseline, reselect the baseline and perform the analysis of the reference point; until all the smart bases on the distribution map are removed.

[0029] Among these, the smart bases within the distribution map were filtered based on usage to determine valid targets, including: Feature extraction is performed on usage data to construct a usage dataset; Usage evaluation is performed based on a pre-configured usage evaluation library and usage dataset; When the evaluation is greater than or equal to the preset threshold, the smart base is considered a valid target; When the usage evaluation is less than a preset threshold, find the nearest smart base with the same usage evaluation less than the preset threshold, accumulate the usage evaluation, and when the accumulated evaluation is greater than or equal to the preset threshold, calculate the center point based on the position of the smart base participating in the accumulation, construct a virtual target at the center point and use it as a valid target.

[0030] This embodiment analyzes the distribution of smart docks, configures corresponding emergency response points based on the analysis, and deploys staff at the emergency response points to enable rapid emergency response for users of each smart dock.

[0031] In one embodiment, such as Figure 3 and Figure 4 As shown, the smart base includes: a main body 1, a weighing module 3 set on the upper surface of the main body, a gas detection module 4, a display module 5, an identification module 6, and a processing module 7; The weighing module 3, gas detection module 4, display module 5, and identification module 6 are electrically connected to the processing module 7. The processing module 7 analyzes the weighing data from the weighing module 3 to determine if a gas cylinder placement event has been triggered. Upon triggering, the identification module 6 identifies the gas cylinder. If identification is successful, the cylinder is cleared, its tare weight is recorded, the cylinder model is identified, and the original tare weight is set according to the cylinder model. Based on the original tare weight and weighing data, the remaining gas volume is determined and displayed on the display module. The processing module 7 also detects the gas concentration in the environment via the gas detection module and displays the current concentration on the display module 5. This intelligent base performs gas detection and weighing on liquefied petroleum gas (LPG) cylinders placed on it, and displays the remaining gas volume based on the weighing to meet the safety needs of users in temporary gas usage scenarios. Figure 5This is a physical illustration corresponding to this embodiment. Specifically, the weighing function works as follows: when the gas cylinder is placed on the base and the weight stabilizes, a cylinder placement event is triggered, and the screen illuminates to display the current weighing value. After the gas cylinder is removed from the base, the weight stabilizes, a cylinder removal event is triggered, and the screen illuminates to display the current weighing value. The gas concentration detection module implements the gas concentration detection function, specifically: it detects the ambient gas concentration in real time and displays the current concentration value on the screen in Vol. When the gas concentration detection value exceeds 0.15%Vol (1500ppm / 7.5%LEL), a gas concentration alarm is triggered, the valve is closed, a buzzer alarm sounds, and a gas leak alarm event is reported. Under the gas concentration alarm state, when the detected gas concentration value drops below 0.01%Vol (100ppm / 0.5LEL), the buzzer alarm sounds, and a gas leak alarm clearing event is reported.

[0032] To facilitate unified management of the platform, the processor connects to the server (rapid response system) via communication module 8. Communication module 8 can use a 4G communication module, which can interact with data through the connected 4G-IoT. The 4G communication module uploads data such as gas cylinder RFID, weighing weight, gas volume (displaying "--" if no tare operation has been performed), gas concentration, solenoid valve switch, location information, gas cylinder replacement time, abnormal status detection, and backup battery power information (0-100%) to the cloud platform for monitoring and analysis. The 4G communication module can report attribute changes at a frequency of 10 minutes. If there are no differences, it will not update the report and wait for the next cycle. When an event occurs, it will update the event immediately.

[0033] The identification module includes an RFID reader. When a gas cylinder placement event is triggered, the reader reads the gas cylinder's RFID tag. If the RFID reading is successful and valid, the RFID icon illuminates on the display module, a gas cylinder RFID update event is reported, the gas cylinder tare record is cleared, the gas cylinder model is identified, and the original tare weight is configured based on the gas cylinder model. If the RFID reading is successful but invalid, the RFID icon turns off the screen, and a gas cylinder RFID invalid event is reported. If the RFID reading fails, the RFID icon turns off the screen, and a gas cylinder RFID invalid event is reported. When a gas cylinder removal event is triggered, the RFID icon turns off the screen, and no gas cylinder RFID event is reported.

[0034] The processing module analyzes the weighing data from the weighing module to determine whether a gas cylinder placement event has been triggered, and performs the following operations: When the cylinder is first turned on, the weight data is tracked and determined. When the data is greater than or equal to a preset first threshold (any value between 0.5KG and 5KG), the cylinder placement event is triggered. During use, if the difference between the previous data and the next data is greater than or equal to the preset second threshold (any value between 0.2KG and 3KG), a gas cylinder placement event is triggered.

[0035] The gas detection module includes: a gas sensor disposed within the main body; and at least one detection window disposed on the surface of the main body, the detection window being in communication with the gas sensor. To enable rapid monitoring of gas leaks when the gas cylinder outlet connection is not tight during use, the gas detection module also includes: a gas sensor and a sleeve disposed within the main body; such as... Figure 6 As shown, the sleeve 11 is fitted onto the connection between the gas cylinder outlet 10 and the pressure reducing valve 12. A pipe is provided on the sleeve 11 that connects to the gas sensor. The sleeve can be made of rubber material in one piece; a cavity is provided in the middle to facilitate the gas being guided to the gas sensor by the pipe.

[0036] In actual use, the gas cylinder needs to be connected to a pressure reducing valve before being connected to the gas-using equipment. Due to the weight of the pressure reducing valve and the gas pipeline, the weight detected by the weighing module is actually higher than the weight of the gas cylinder. In one embodiment, the processing module also performs the following operations: The system extracts and stores weighing data within a preset time (any value between 2 min and 10 min) after the gas cylinder placement event is triggered; when the stored data meets the preset analysis conditions, the system analyzes and determines the additional weight; based on the additional weight, the estimated gas volume is calculated; and the estimated gas volume is displayed through the display module.

[0037] The process involves extracting weighing data at preset time intervals (any value between 1 second and 1 minute). The preset analysis conditions are as follows: Statistical parameters are configured and set to zero; starting from the last data point, adjacent data points are compared sequentially; when the difference is less than or equal to a preset difference threshold, the statistical parameter is incremented by one; starting from the first data point with a difference greater than the preset difference threshold, adjacent data points are compared sequentially; when the difference is less than or equal to the preset difference threshold, the data points are grouped together; when the difference is greater than the preset difference threshold, the preceding data points are grouped again; the largest data point in each group is used as an indicator parameter; when the statistical parameter is greater than or equal to a preset data volume threshold (any value between 10 and 100) and the indicator parameter is greater than or equal to a preset second data volume threshold (any value between 2 and 10), this data point is considered usable for weight-bearing analysis; when the number of stored data points usable for weight-bearing analysis is greater than or equal to a preset number (any value between 2 and 10), the stored data is determined to meet the preset analysis conditions. The process involves: analyzing the weight distribution; specifically, processing a data set suitable for weight analysis to determine the last step value and the preceding step value; using the average difference between the last step value and the preceding step value for all data as the weight value; the determination of the last step value and the preceding step value is as follows: starting from the last position, compare adjacent data points sequentially backwards; when the difference is less than or equal to a preset difference threshold (any value from 1g to 100g), use that data as the basis for determining the last step value; starting from the Nth position (any value from 2 to 30), extract a preset number of data points (any value from 2 to 29) and average them to obtain the last step value; starting from the first data point used as the basis for determining the last step value, compare adjacent data points sequentially backwards; when the difference is less than or equal to a preset difference threshold, group the data into a single group; when the difference is greater than the preset difference threshold, group the data at the beginning of the group again; use the average value of the group with the largest amount of data as the preceding step value. Finally, based on the added weight, the estimated gas volume is calculated; that is, the weight obtained by subtracting the original weight after tare from the weighed weight, and then subtracting the added weight, is used to calculate the estimated gas volume. This embodiment estimates the weight by repeatedly recording the impact of the weight of the pressure reducing valve and gas pipeline connected to the gas cylinder on the weighing module. Following this estimation, the gas volume is then estimated, resulting in a volume estimate that more closely approximates actual usage. Furthermore, when the pressure reducing valve is also an IoT device, its parameter information (model, manufacturer, etc.) can be obtained through short-range communication. The corresponding weight data can then be requested from the weight analysis module of the IoT-based gas leak detection and rapid response system. In this case, the weight provided by the weight analysis module should be considered the accurate estimate. To ensure the accuracy of the added weight data, the added weight analysis module also performs the following operations: Receives ventilation and weighing operation request instructions sent by staff after operating the smart base; The smart base outputs a prompt message: "Please disconnect the gas cylinder and close the gas valve." After the staff operates according to the prompts, the weight data of the smart base is obtained as the first reference data; The second reference data is determined from the historical data uploaded by the smart base; the second reference data is the weighing data from the last data half an hour before the ventilation weighing operation request command. The difference between the first reference data and the second reference data is used as the weight data corresponding to the smart base.

[0038] In addition, most people are not very aware of how long the remaining gas can be used. Therefore, the processing module also performs the following operations: records historical gas usage; when the historical gas usage records meet the preset conditions (time length and / or data volume), performs gas usage event analysis and configuration; and analyzes and displays the remaining number of gas usages based on the gas usage event analysis and configuration results.

[0039] For example: when the preset condition is that the amount of data is greater than or equal to 10 records; the recording rule for historical gas usage is: from the time gas is supplied from the cylinder to the time gas is not supplied is considered as one data point; when the interval between two adjacent data points is less than or equal to the preset time threshold (any value between 10 seconds and 3 minutes), they are considered as the same record. The maximum gas consumption of the last N records (any one of the 2 to 8 records) is used as the gas consumption for a single transaction.

[0040] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A gas leak precision detection and rapid linkage early warning response system based on the Internet of Things, characterized in that, include: The data acquisition module is used to collect the detection data sent by the smart base; The data analysis module is used to analyze the detection data and determine whether a linkage warning response has been triggered. The linkage response module is used to generate and execute linkage warning response tasks when a linkage warning response is triggered.

2. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 1, characterized in that, The data analysis module analyzes the detection data to determine whether a coordinated early warning response has been triggered, including: Analyze the detection data to determine the gas concentration in the environment where the smart base is located; When the gas concentration is greater than or equal to a preset first threshold, a linkage warning response is triggered. And / or, When the gas concentration is greater than or equal to the preset second threshold and shows an upward trend, a linkage warning response is triggered.

3. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 1, characterized in that, When a coordinated early warning response is triggered, the coordinated response module generates and executes a coordinated early warning response task, including: Based on the positioning data of the smart base, the target location of the linkage response task is determined; Based on the identification code of the smart base, the pre-configured and managed user terminal and user are identified; Based on the target location of the mission, identify the personnel and terminals of all parties involved in the joint early warning response mission; The task target location is used as the task target of the joint early warning and response task, the user terminal and various parties' terminals are used as communication terminals, and the personnel of various parties and users are used as joint staff to build the joint early warning and response task.

4. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 3, characterized in that, It also includes: a risk classification module, which is used to assess the risk of the task target and determine the risk level when a linkage early warning response is triggered; Among them, the risk level is used to guide the construction of joint early warning and response tasks; The risk grading module assesses the risks to the task objectives and determines the risk level, including: Retrieve environmental description data associated with the smart dock; Send supplementary environment description queries to the user terminal and receive supplementary data sent by the user terminal; Feature extraction is performed on environmental description data, supplementary data, and detection data. Based on the extracted feature parameters and a pre-configured risk assessment library, the risk level is determined.

5. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 1, characterized in that, Also includes: The detection and control module is used to adjust the time interval for the data acquisition module to collect the detection data sent by the smart base according to the current state of the smart base. The detection and control module performs the following operations: When the current state of the smart base is the gas cylinder replacement reminder stage, the detection data is collected at a preset first time interval. When the current state of the smart base is the initial stage of using a new gas cylinder, the detection data is collected at a preset second time interval. The first time interval is longer than the second time interval.

6. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 5, characterized in that, The detection and control module also performs the following operations: When the current state of the smart base is the continuous gas discharge stage of the gas cylinder, the detection data is collected using a preset third time interval. When the current state of the smart base is when the gas cylinder stops discharging gas, the detection data is collected using a preset fourth time interval. The third time interval is shorter than the fourth time interval.

7. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 1, characterized in that, The emergency response point analysis and construction module is used to analyze the distribution and usage of smart base stations and construct emergency response points. The emergency response point analysis and construction module analyzes the distribution and usage of smart base stations to construct emergency response points, including: A distribution map is constructed based on the distribution of smart bases; Based on usage data, the smart bases within the distribution map are filtered to identify valid targets; Identify points on the distribution map that can be recommended as emergency response points as analysis points; Based on the effective targets and the positional relationships between the analysis points, at least one location is determined from the analysis points as the location for constructing an emergency response point.

8. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 7, characterized in that, Based on effective targets and the positional relationships between analysis points, at least one location is determined from the analysis points as a site for constructing an emergency response point, including: Using the line connecting the two outermost smart bases as the baseline, starting from the position of any smart base at either end of the baseline, the points on the baseline at the preset first distance are used as reference points. Centered on the analysis point with the smallest distance from the reference point, the smart bases within a preset second distance are statistically analyzed. When the statistical data meets the preset conditions, an emergency response point is constructed at the analysis point, and the area where the smart bases corresponding to the statistical data are distributed is taken as the emergency response area corresponding to the emergency response point. When the statistical data does not meet the preset conditions, the reference point is moved by a preset first step length, and the analysis point is reselected for analysis. Remove the emergency response area from the distribution map, move the reference point by the preset second step size, reselect the analysis point for analysis, and when the reference point moves to the other end of the baseline, reselect the baseline and perform the analysis of the reference point; until all the smart bases on the distribution map are removed.

9. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 7, characterized in that, Based on usage data, the smart docks within the distribution map were filtered to identify valid targets, including: Feature extraction is performed on usage data to construct a usage dataset; Usage evaluation is performed based on a pre-configured usage evaluation library and usage dataset; When the evaluation is greater than or equal to the preset threshold, the smart base is considered a valid target; When the usage evaluation is less than a preset threshold, find the nearest smart base with the same usage evaluation less than the preset threshold, accumulate the usage evaluation, and when the accumulated evaluation is greater than or equal to the preset threshold, calculate the center point based on the position of the smart base participating in the accumulation, construct a virtual target at the center point and use it as a valid target.

10. The IoT-based accurate detection and rapid linkage early warning response system for gas leaks as described in claim 1, characterized in that, The intelligent base includes: a main body, a weighing module, a gas detection module, a display module, an identification module, a processing module, and a communication module, all mounted on the upper surface of the main body. The weighing module, gas detection module, display module, identification module, and communication module are all electrically connected to the processing module.

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