Gas abnormity monitoring method, system and terminal of Internet of Things cloud platform

Abstract

The invention discloses a gas abnormity monitoring method, system and terminal of an Internet of Things cloud platform, and the method comprises the steps: obtaining the gas concentration of a current environment and the historical gas consumption data of a user, and carrying out the prediction of the gas concentration in a preset time period according to the historical gas consumption data, and obtaining the predicted concentration; judging whether the difference value between the current environment gas concentration and the predicted concentration is greater than a normal threshold value and less than a dangerous threshold value or not; if the difference value is larger than a normal threshold value and smaller than a dangerous threshold value, a gas consumption curve of the gas meter and working state parameters of the gas meter within the preset duration are obtained according to the current environment gas concentration; and according to the gas consumption curve and the working state parameters, calculating an abnormal index of the current environment gas concentration, and when the abnormal index exceeds a preset index, determining that the current environment gas concentration is abnormal and sending an alarm prompt to a user. The gas concentration is monitored in real time, future changes are predicted, abnormity is judged, an alarm is given, and user safety is ensured.

Description

Technical Field

[0001] The present invention relates to the field of gas monitoring technology, and in particular to a gas anomaly monitoring method, system, terminal and computer-readable storage medium for an Internet of Things cloud platform. Background Art

[0002] In modern society, fire accidents occur more and more frequently, among which fire accidents caused by gas leaks are also becoming more and more frequent. Gas leaks greatly threaten people's property and life safety. How to prevent fires and gas leaks and reduce the loss of life and property caused by fires or gas leaks is a hot issue that needs to be solved urgently in today's society. In the prior art, gas leak alarms are often used to detect and alarm gas leaks.

[0003] Existing technologies usually predict gas concentration based on simple statistical models of historical gas usage data and compare it with the current ambient gas concentration to preliminarily determine whether there is a gas leak. However, the prediction accuracy of the above method is low and it can only be used for detection when the anomaly is more obvious. It is often difficult to detect more hidden anomalies, resulting in insufficient detection accuracy.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide a gas anomaly monitoring method, system and computer-readable storage medium for an Internet of Things cloud platform, aiming to solve the problem that the accuracy of predicting gas leakage in the prior art is low, and detection can only be performed when the anomaly is more obvious. It is often difficult to detect more hidden anomalies, resulting in insufficient detection accuracy.

[0006] To achieve the above object, the present invention provides a method for monitoring gas anomalies on an Internet of Things cloud platform, and the method for monitoring gas anomalies on an Internet of Things cloud platform comprises the following steps:

[0007] Obtain the current ambient gas concentration and the user's historical gas usage data, and predict the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration;

[0008] Determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold;

[0009] If the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve of the gas meter and the working status parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration;

[0010] The abnormality index of the current ambient gas concentration is calculated according to the gas usage curve and the working state parameter. When the abnormality index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user.

[0011] Optionally, in the gas anomaly monitoring method of the Internet of Things cloud platform, the historical gas usage data includes average gas usage, maximum gas usage and minimum gas usage;

[0012] The obtaining of the current ambient gas concentration and the historical gas usage data of the user, and performing gas concentration prediction within a preset time period according to the historical gas usage data to obtain the predicted concentration specifically includes:

[0013] According to a preset collection frequency, obtaining the gas concentration of the gas meter in the current environment collected by the gas detection module, wherein the gas detection module is pre-installed on the gas meter;

[0014] The average gas usage, maximum gas usage and minimum gas usage of the user are obtained, and the gas concentration is predicted within a preset time period according to the average gas usage, the maximum gas usage and the minimum gas usage to obtain a predicted concentration.

[0015] Optionally, in the gas anomaly monitoring method of the Internet of Things cloud platform, the obtaining of the current ambient gas concentration specifically includes any one of the following methods:

[0016] Acquiring the current ambient gas concentration at every preset time interval;

[0017] In response to the user's query operation on the gas concentration, the current ambient gas concentration is acquired.

[0018] Optionally, the method for monitoring gas anomalies on the Internet of Things cloud platform, wherein the step of judging whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold, further comprises:

[0019] If the current ambient gas concentration is greater than or equal to the danger threshold, an emergency evacuation message is sent to a preset speaker to notify the user to evacuate, and the emergency evacuation message includes prompting information to avoid using electrical appliances and switches.

[0020] Optionally, the method for monitoring gas anomalies on the Internet of Things cloud platform, wherein if the difference is greater than the normal threshold and less than the dangerous threshold, a gas usage curve of the gas meter and a working status parameter of the gas meter within a preset time period are obtained according to the current ambient gas concentration, and then the method further includes:

[0021] Get the gas concentration rising speed;

[0022] Inputting the gas concentration rising speed and the current gas concentration into a preset regression model to obtain a relationship curve between gas concentration and time;

[0023] Obtaining the time point at which the current ambient gas concentration reaches a dangerous threshold according to the relationship curve;

[0024] Calculate according to the current ambient gas concentration and the time point to obtain a predicted gas leakage processing time;

[0025] The predicted gas leak processing time is used to remind the user of the time period when the current ambient gas concentration reaches a dangerous threshold, so that the user can evacuate in time.

[0026] Optionally, the gas anomaly monitoring method of the Internet of Things cloud platform, wherein the calculating the anomaly index of the current ambient gas concentration according to the gas usage curve and the working state parameter, specifically includes:

[0027] Obtaining the smoothness and fluctuation amplitude of the gas consumption curve;

[0028] An abnormality index of the gas concentration is calculated according to the smoothness and the fluctuation amplitude.

[0029] Optionally, the gas anomaly monitoring method of the Internet of Things cloud platform, wherein the anomaly index of the current ambient gas concentration is calculated according to the gas usage curve and the working state parameter, and when the anomaly index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user, and then further includes:

[0030] Constructing a corresponding relationship between the current ambient gas concentration and the current time;

[0031] Storing the current ambient gas concentration, the current time and the corresponding relationship in a preset gas leakage database to construct and update the preset gas leakage database;

[0032] In response to the user's query operation regarding gas leakage, obtaining a query time input by the user;

[0033] Searching the preset gas leakage database for the gas concentration corresponding to the query time;

[0034] The gas concentration corresponding to the query time is displayed to the user.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a gas anomaly monitoring system for an Internet of Things cloud platform, wherein the gas anomaly monitoring system for an Internet of Things cloud platform:

[0036] A gas concentration prediction module is used to obtain the current ambient gas concentration and the user's historical gas usage data, and to predict the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration;

[0037] A gas concentration determination module, used to determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold;

[0038] A gas meter data acquisition module, configured to acquire a gas usage curve of the gas meter and working status parameters of the gas meter within a preset time period according to the current ambient gas concentration if the difference is greater than the normal threshold and less than the dangerous threshold;

[0039] The abnormal warning module is used to calculate the abnormal index of the current ambient gas concentration according to the gas consumption curve and the working state parameter. When the abnormal index exceeds the preset index, it is determined that the current ambient gas concentration is abnormal and an alarm prompt is sent to the user.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a gas anomaly monitoring program of the Internet of Things cloud platform, and when the gas anomaly monitoring program of the Internet of Things cloud platform is executed by the processor, the steps of the gas anomaly monitoring method of the Internet of Things cloud platform as described above are implemented.

[0041] The present invention obtains the current environment gas concentration and the user's historical gas usage data, predicts the gas concentration within a preset time period based on the historical gas usage data, and obtains the predicted concentration; determines whether the difference between the current environment gas concentration and the predicted concentration is greater than the normal threshold and less than the dangerous threshold; if the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve and the working state parameters of the gas meter within the preset time period are obtained based on the current environment gas concentration; the abnormal index of the current environment gas concentration is calculated based on the gas usage curve and the working state parameters, and when the abnormal index exceeds the preset index, it is determined that the current environment gas concentration is abnormal and an alarm is sent to the user. The present invention ensures user safety by real-time monitoring of gas concentration, predicting future changes, determining abnormalities and issuing alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a preferred embodiment of the method for monitoring gas anomalies on the Internet of Things cloud platform of the present invention;

[0043] Figure 2 It is a structural diagram of a preferred embodiment of the gas anomaly monitoring system of the Internet of Things cloud platform of the present invention;

[0044] Figure 3 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] The existing technology can only detect when the gas leakage is more obvious, and it is often difficult to detect more hidden abnormalities, resulting in insufficient detection accuracy. Therefore, a gas anomaly monitoring method for an Internet of Things cloud platform is needed, which can improve the detection accuracy of gas leakage.

[0047] The gas anomaly monitoring method of the Internet of Things cloud platform described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the gas anomaly monitoring method of the Internet of Things cloud platform includes the following steps:

[0048] Step S10: obtaining the current ambient gas concentration and the user's historical gas usage data, and predicting the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration.

[0049] Specifically, the historical gas usage data includes average gas usage, maximum gas usage and minimum gas usage (after obtaining the historical gas usage data, these data are processed and analyzed by statistical analysis methods. For example, the average gas usage, maximum gas usage and minimum gas usage of the user in the same time period can be calculated, and the gas usage of the user in a preset time period can be predicted based on these statistical data). According to the preset collection frequency, the gas meter collected by the gas detection module in the current environment gas concentration (in response to the set trigger condition, according to the preset collection frequency, the gas detection module collects the current gas concentration of the device through the gas detection module). The gas detection module is pre-installed on the gas meter; the average gas usage, maximum gas usage and minimum gas usage of the user are obtained, and the gas concentration is predicted within a preset time period according to the average gas usage, the maximum gas usage and the minimum gas usage to obtain a predicted concentration (after obtaining the historical gas usage data, these data are processed and analyzed by statistical analysis methods. For example, the average gas usage, maximum gas usage and minimum gas usage of the user in the same time period can be calculated, and the gas concentration is predicted based on these statistical data to obtain a predicted concentration).

[0050] Furthermore, the obtaining of the current ambient gas concentration specifically includes any one of the following methods: obtaining the current ambient gas concentration at intervals of a preset time period; obtaining the current ambient gas concentration in response to the user's query operation on the gas concentration (the length of the preset time period can be set according to the needs of the staff. Generally, when the preset time period is set to be shorter, the Internet of Things cloud platform can obtain the gas concentration more frequently, and thus can more promptly discover possible abnormal conditions of the gas; another method is that the Internet of Things cloud platform responds to the user's gas concentration query operation, obtains the current gas concentration, and displays it to the user; according to the user's setting, one query operation can simultaneously obtain the gas concentration values ​​of multiple areas, so as to perform multi-area monitoring at the same time).

[0051] Step S20: Determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold.

[0052] Specifically, if the current environmental gas concentration is greater than or equal to the danger threshold, an emergency evacuation message is sent to a preset speaker to notify the user to evacuate. The emergency evacuation message includes prompts to avoid using electrical appliances and switches (for example, when the current gas concentration is greater than or equal to the danger threshold, it means that the gas in the regulatory area has leaked to a level that may endanger life. At this time, the IoT cloud platform sends the emergency evacuation message to pre-set speakers and other information-transmitting devices. In addition, the gas leakage information will also be sent to the gas safety regulatory department and the user's pre-reserved terminal to promptly prompt the user and management personnel to handle and assist. At the same time, the emergency evacuation message also includes precautions for evacuation. For example, when the methane concentration is within the range of 5%-15%, it will explode when encountering a fire source. At this time, prompts will be added that switches and other electrical appliances or switches that may produce sparks and other heat sources cannot be used).

[0053] Step S30: If the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve of the gas meter and the working status parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration.

[0054] Specifically, the gas concentration rising rate is obtained; the gas concentration rising rate and the current gas concentration are input into a preset regression model to obtain a relationship curve between gas concentration and time, that is, the IoT cloud platform obtains the gas concentration rising rate through the gas alarm, and the specific acquisition method is to select a time period with a shorter time interval including the current moment (such as a time period with a time length of 0.1 seconds), obtain the gas concentration at the two end points of the time period, and perform a difference calculation to obtain the concentration difference, and then divide the concentration difference by the length of the time period to approximately obtain the gas concentration rising rate at the current moment; in order to make the prediction of the length of gas leakage treatment time more accurate, the gas concentration rising rates at several different moments can be obtained, and these data and the current gas concentration can be input into a preset regression model trained in advance to obtain a predicted gas concentration and time relationship curve, in which each time point There is a corresponding gas concentration value; the gas concentration value where the danger threshold value appears for the first time is retrieved on the curve, and the danger threshold arrival time corresponding to this gas concentration value is obtained; the danger threshold arrival time is subtracted from the current time to obtain the predicted gas leakage processing time; the time point when the current environment gas concentration reaches the danger threshold is obtained according to the relationship curve; the predicted gas leakage processing time is obtained according to the current environment gas concentration and the time point; the predicted gas leakage processing time is used to remind the user of the time period when the current environment gas concentration reaches the danger threshold, so that the user can evacuate in time (when the Internet of Things cloud platform determines that the current gas concentration is greater than the normal threshold and less than the danger threshold, it means that the gas concentration has not reached a very dangerous level at this time, and there is still a better evacuation time; the Internet of Things cloud platform calculates and predicts the gas leakage processing time according to the current gas concentration and the danger threshold).

[0055] Step S40: Calculate the abnormal index of the current ambient gas concentration according to the gas usage curve and the working state parameter. When the abnormal index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and send an alarm prompt to the user.

[0056] Specifically, the smoothness and fluctuation amplitude of the gas consumption curve are obtained; based on the smoothness and the fluctuation amplitude, the abnormality index of the gas concentration is calculated (the first abnormality index of the gas meter is calculated by combining the smoothness and the fluctuation amplitude. This index comprehensively considers the stability and fluctuation amplitude of the gas consumption. Through these characteristics, abnormal gas consumption can be effectively identified, such as a sudden surge or decrease in gas consumption, which may indicate abnormal phenomena such as gas leakage, equipment failure or illegal use), and a corresponding relationship between the current environmental gas concentration and the current time is constructed; the current environmental gas concentration, the current time and the corresponding relationship are stored in a preset gas leakage database to construct and update the preset gas leakage database; in response to the user's query operation on gas leakage, the query time input by the user is obtained; the gas concentration corresponding to the query time is searched in the preset gas leakage database; the gas concentration corresponding to the query time is displayed to the user (the Internet of Things cloud platform can respond to the user's query operation on historical gas leakage, obtain the query time input by the user, search for the corresponding gas concentration through the corresponding relationship between gas concentration and query time, and display the gas concentration corresponding to the query time to the user).

[0057] Furthermore, if Figure 2 As shown, based on the above-mentioned gas anomaly monitoring method of the Internet of Things cloud platform, the present invention also provides a gas anomaly monitoring system of the Internet of Things cloud platform, wherein the gas anomaly monitoring system of the Internet of Things cloud platform includes:

[0058] The gas concentration prediction module 51 is used to obtain the current ambient gas concentration and the user's historical gas usage data, and to predict the gas concentration within a preset time period according to the historical gas usage data to obtain a predicted concentration;

[0059] The gas concentration determination module 52 is used to determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold;

[0060] The gas meter data acquisition module 53 is used to acquire the gas usage curve of the gas meter and the working state parameters of the gas meter within a preset time period according to the current ambient gas concentration if the difference is greater than the normal threshold and less than the dangerous threshold;

[0061] The abnormal warning module 54 is used to calculate the abnormal index of the current ambient gas concentration according to the gas usage curve and the working state parameter. When the abnormal index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user.

[0062] Furthermore, if Figure 3As shown, based on the gas anomaly monitoring method and system of the above-mentioned Internet of Things cloud platform, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0063] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the memory 20 stores a gas anomaly monitoring program 40 of an Internet of Things cloud platform, and the gas anomaly monitoring program 40 of the Internet of Things cloud platform can be executed by the processor 10, thereby realizing the gas anomaly monitoring method of the Internet of Things cloud platform in this application.

[0064] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the gas anomaly monitoring method of the Internet of Things cloud platform.

[0065] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other via a system bus.

[0066] In one embodiment, when the processor 10 executes the gas anomaly monitoring program 40 of the Internet of Things cloud platform in the memory 20, the following steps are implemented:

[0067] Obtain the current ambient gas concentration and the user's historical gas usage data, and predict the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration;

[0068] Determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold;

[0069] If the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve of the gas meter and the working status parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration;

[0070] The abnormality index of the current ambient gas concentration is calculated according to the gas usage curve and the working state parameter. When the abnormality index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user.

[0071] The historical gas consumption data includes average gas consumption, maximum gas consumption and minimum gas consumption;

[0072] The obtaining of the current ambient gas concentration and the historical gas usage data of the user, and performing gas concentration prediction within a preset time period according to the historical gas usage data to obtain the predicted concentration specifically includes:

[0073] According to a preset collection frequency, obtaining the gas concentration of the gas meter in the current environment collected by the gas detection module, wherein the gas detection module is pre-installed on the gas meter;

[0074] The average gas usage, maximum gas usage and minimum gas usage of the user are obtained, and the gas concentration is predicted within a preset time period according to the average gas usage, the maximum gas usage and the minimum gas usage to obtain a predicted concentration.

[0075] The method of obtaining the current ambient gas concentration specifically includes any of the following methods:

[0076] Acquiring the current ambient gas concentration at every preset time interval;

[0077] In response to the user's query operation on the gas concentration, the current ambient gas concentration is acquired.

[0078] Wherein, the step of judging whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold may further include:

[0079] If the current ambient gas concentration is greater than or equal to the danger threshold, an emergency evacuation message is sent to a preset speaker to notify the user to evacuate, and the emergency evacuation message includes prompting information to avoid using electrical appliances and switches.

[0080] Wherein, if the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve and the working state parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration, and then it also includes:

[0081] Get the gas concentration rising speed;

[0082] Inputting the gas concentration rising speed and the current gas concentration into a preset regression model to obtain a relationship curve between gas concentration and time;

[0083] Obtaining the time point at which the current ambient gas concentration reaches a dangerous threshold according to the relationship curve;

[0084] Calculate according to the current ambient gas concentration and the time point to obtain a predicted gas leakage processing time;

[0085] The predicted gas leak processing time is used to remind the user of the time period when the current ambient gas concentration reaches a dangerous threshold, so that the user can evacuate in time.

[0086] The step of calculating the abnormality index of the current ambient gas concentration according to the gas usage curve and the working state parameter specifically includes:

[0087] Obtaining the smoothness and fluctuation amplitude of the gas consumption curve;

[0088] An abnormality index of the gas concentration is calculated according to the smoothness and the fluctuation amplitude.

[0089] Wherein, the abnormal index of the current ambient gas concentration is calculated according to the gas usage curve and the working state parameter, and when the abnormal index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user, and then it also includes:

[0090] Constructing a corresponding relationship between the current ambient gas concentration and the current time;

[0091] Storing the current ambient gas concentration, the current time and the corresponding relationship in a preset gas leakage database to construct and update the preset gas leakage database;

[0092] In response to the user's query operation regarding gas leakage, obtaining a query time input by the user;

[0093] Searching the preset gas leakage database for the gas concentration corresponding to the query time;

[0094] The gas concentration corresponding to the query time is displayed to the user.

[0095] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a gas anomaly monitoring program for an Internet of Things cloud platform, and when the gas anomaly monitoring program for the Internet of Things cloud platform is executed by a processor, the steps of the gas anomaly monitoring method for the Internet of Things cloud platform as described above are implemented.

[0096] In summary, the present invention provides a method, system and computer-readable storage medium for monitoring gas anomalies on an Internet of Things cloud platform, the method comprising: obtaining the current environment gas concentration and the user's historical gas usage data, predicting the gas concentration within a preset time period according to the historical gas usage data, and obtaining the predicted concentration; judging whether the difference between the current environment gas concentration and the predicted concentration is greater than the normal threshold and less than the dangerous threshold; if the difference is greater than the normal threshold and less than the dangerous threshold, obtaining the gas usage curve and the working state parameters of the gas meter within the preset time period according to the current environment gas concentration; calculating the abnormal index of the current environment gas concentration according to the gas usage curve and the working state parameters, and when the abnormal index exceeds the preset index, determining that the current environment gas concentration is abnormal and sending an alarm prompt to the user. The present invention ensures user safety by real-time monitoring of gas concentration, predicting future changes, judging abnormalities and issuing alarms.

[0097] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or terminal system including the element.

[0098] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0099] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A gas anomaly monitoring method for an Internet of Things cloud platform, characterized in that: The gas anomaly monitoring method of the Internet of Things cloud platform includes: Obtain the current ambient gas concentration and the user's historical gas usage data, and predict the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration; Determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold; If the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve of the gas meter and the working status parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration; The abnormality index of the current ambient gas concentration is calculated according to the gas usage curve and the working state parameter. When the abnormality index exceeds a preset index, it is determined that the current ambient gas concentration is abnormal and an alarm is sent to the user.

2. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: The historical gas consumption data includes average gas consumption, maximum gas consumption and minimum gas consumption; The obtaining of the current ambient gas concentration and the historical gas usage data of the user, and performing gas concentration prediction within a preset time period according to the historical gas usage data to obtain the predicted concentration specifically includes: According to a preset collection frequency, obtaining the gas concentration of the gas meter in the current environment collected by the gas detection module, wherein the gas detection module is pre-installed on the gas meter; The average gas usage, maximum gas usage and minimum gas usage of the user are obtained, and the gas concentration is predicted within a preset time period according to the average gas usage, the maximum gas usage and the minimum gas usage to obtain a predicted concentration.

3. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: The method of obtaining the current ambient gas concentration specifically includes any of the following methods: Acquiring the current ambient gas concentration at every preset time interval; In response to the user's query operation on the gas concentration, the current ambient gas concentration is acquired.

4. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: The step of determining whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold, further includes: If the current ambient gas concentration is greater than or equal to the danger threshold, an emergency evacuation message is sent to a preset speaker to notify the user to evacuate, and the emergency evacuation message includes prompting information to avoid using electrical appliances and switches.

5. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: If the difference is greater than the normal threshold and less than the dangerous threshold, the gas usage curve and the working state parameters of the gas meter within a preset time period are obtained according to the current ambient gas concentration, and then the following is further included: Get the gas concentration rising speed; Inputting the gas concentration rising speed and the current gas concentration into a preset regression model to obtain a relationship curve between gas concentration and time; Obtaining the time point at which the current ambient gas concentration reaches a dangerous threshold according to the relationship curve; Calculate according to the current ambient gas concentration and the time point to obtain a predicted gas leakage processing time; The predicted gas leak processing time is used to remind the user of the time period when the current ambient gas concentration reaches a dangerous threshold, so that the user can evacuate in time.

6. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: The calculating, according to the gas usage curve and the working state parameter, the abnormal index of the current ambient gas concentration specifically includes: Obtaining the smoothness and fluctuation amplitude of the gas consumption curve; An abnormality index of the gas concentration is calculated according to the smoothness and the fluctuation amplitude.

7. The method for monitoring gas anomalies on the Internet of Things cloud platform according to claim 1, characterized in that: The method further comprises: calculating an abnormal index of the current ambient gas concentration according to the gas usage curve and the working state parameter, and when the abnormal index exceeds a preset index, determining that the current ambient gas concentration is abnormal and sending an alarm prompt to the user, and then further comprising: Constructing a corresponding relationship between the current ambient gas concentration and the current time; Storing the current ambient gas concentration, the current time and the corresponding relationship in a preset gas leakage database to construct and update the preset gas leakage database; In response to the user's query operation regarding gas leakage, obtaining a query time input by the user; Searching the preset gas leakage database for the gas concentration corresponding to the query time; The gas concentration corresponding to the query time is displayed to the user.

8. A gas anomaly monitoring system for an Internet of Things cloud platform, characterized in that: The gas anomaly monitoring system of the Internet of Things cloud platform includes: A gas concentration prediction module is used to obtain the current ambient gas concentration and the user's historical gas usage data, and to predict the gas concentration within a preset time period based on the historical gas usage data to obtain a predicted concentration; A gas concentration determination module, used to determine whether the difference between the current ambient gas concentration and the predicted concentration is greater than a normal threshold and less than a dangerous threshold; A gas meter data acquisition module, configured to acquire a gas usage curve of the gas meter and working status parameters of the gas meter within a preset time period according to the current ambient gas concentration if the difference is greater than the normal threshold and less than the dangerous threshold; The abnormal warning module is used to calculate the abnormal index of the current ambient gas concentration according to the gas consumption curve and the working state parameter. When the abnormal index exceeds the preset index, it is determined that the current ambient gas concentration is abnormal and an alarm prompt is sent to the user.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a gas anomaly monitoring program of the Internet of Things cloud platform stored in the memory and executable on the processor. When the gas anomaly monitoring program of the Internet of Things cloud platform is executed by the processor, the steps of the gas anomaly monitoring method of the Internet of Things cloud platform as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a gas anomaly monitoring program for the Internet of Things cloud platform, and when the gas anomaly monitoring program for the Internet of Things cloud platform is executed by a processor, the steps of the gas anomaly monitoring method for the Internet of Things cloud platform as described in any one of claims 1-7 are implemented.

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