Gas leakage detection and safety control system and method based on internet of things

Abstract

The application provides a gas leakage detection and safety control system and method based on the Internet of Things, comprising: a data acquisition module, which is used for network deployment of pre-deployed integrated sensors in an application scene based on the Internet of Things, and controls the integrated sensors to collect gas concentration data and environmental data in respective monitoring areas based on the network deployment result; a detection module, which is used for correlation analysis of the gas concentration data and the environmental data in the respective monitoring areas, prediction of the change trend of the gas concentration, and real-time dynamic monitoring of gas leakage based on the change trend; and a safety control module, which is used for, when it is determined that there is gas leakage based on the real-time dynamic monitoring result, synchronously starting safety emergency equipment to perform safety response based on the Internet of Things, and synchronously sending the safety response result to a remote monitoring end to perform early warning notification. The timeliness and accuracy of gas leakage are improved, and the effect of gas leakage detection and safety control is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas detection, in particular to a gas leakage detection and safety control system and method based on Internet of Things. BACKGROUND

[0002] At present, gas is widely used in modern life and industrial production, but gas leakage may cause serious safety accidents such as explosion, fire and poisoning, so it is particularly important to detect and control gas leakage;

[0003] However, the traditional gas detection device is often single-functioned, can only perform local alarm, and cannot timely transmit information to relevant personnel or perform remote control, and when detecting gas leakage, only a single sensor is often used to monitor the gas concentration with a fixed strategy, without considering the influence of the environment on the gas concentration, thereby causing misjudgment and reducing the accuracy of gas leakage detection and safety control;

[0004] Therefore, in order to overcome the above defects, the present application provides a gas leakage detection and safety control system and method based on Internet of Things. SUMMARY

[0005] The present application provides a gas leakage detection and safety control system and method based on Internet of Things, which is used to perform network deployment on the integrated sensors pre-deployed in the application scene, so as to facilitate effective control of the integrated sensors and reception of the data collected by the integrated sensors, and then collect the gas concentration data and environmental data in the respective monitoring areas through the network-deployed integrated sensors, ensuring the reliability and comprehensiveness of the collected gas concentration data and environmental data, secondly, correlating and analyzing the obtained gas concentration data and environmental data, and dynamically monitoring the gas leakage in real time according to the analysis results, so as to facilitate timely discovery of gas leakage and improve the timeliness and accuracy of gas leakage, finally, when determining that there is gas leakage, timely starting the safety emergency equipment for safety response, and simultaneously performing early warning notification, so as to facilitate relevant personnel to timely discover the abnormality and facilitate timely taking of corresponding emergency measures, thereby ensuring the effect of gas leakage detection and safety control.

[0006] The present application provides a gas leakage detection and safety control system based on Internet of Things, comprising:

[0007] A data acquisition module is used to perform network deployment on the integrated sensors pre-deployed in the application scene based on Internet of Things, and control the integrated sensors to collect the gas concentration data and environmental data in the respective monitoring areas based on the network deployment results;

[0008] The detection module is configured to perform correlation analysis on the gas concentration data and the environmental data in each monitoring area, predict the change trend of the gas concentration, and perform real-time dynamic monitoring on the gas leakage based on the change trend.

[0009] The safety control module is configured to determine, based on the real-time dynamic monitoring result, that there is a gas leakage, start the safety emergency equipment for safety response based on the Internet of Things, and synchronously send the safety response result to the remote monitoring end for early warning notification.

[0010] Preferably, a gas leakage detection and safety control system based on the Internet of Things comprises a data acquisition module comprising:

[0011] The scene analysis unit is configured to obtain a regional distribution map of the application scene, and determine the spatial layout and functional attributes of different regions in the application scene based on the regional distribution map.

[0012] The sensor position and quantity determination unit is configured to determine the gas detection preference degree of different regions based on the functional attributes, and perform structural analysis on the spatial layout of the corresponding region based on the gas detection preference degree to determine the gas detection key point of the corresponding region.

[0013] The sensor deployment guidance unit is configured to count the number and position of the integrated sensor of each region based on the gas detection key point, and guide the deployment of the integrated sensor based on the counting result.

[0014] Preferably, a gas leakage detection and safety control system based on the Internet of Things comprises a data acquisition module comprising:

[0015] The networking unit is configured to:

[0016] Determine the available local area network in the application scene based on the Internet of Things, and perform port adaptation on the local area network based on the pre-deployed integrated sensor in the application scene.

[0017] Based on the port adaptation result, assign a routing port to each pre-deployed integrated sensor in the local area network, and perform networking and debugging on each pre-deployed integrated sensor based on the routing port.

[0018] The sensor configuration unit is configured to:

[0019] Based on the networking and debugging result, perform device initialization on each integrated sensor, and perform network parameter configuration on each integrated sensor based on the device initialization.

[0020] Determine the multi-dimensional parameter quantization index based on the gas detection requirement, and perform working parameter configuration on each integrated sensor after network parameter configuration based on the multi-dimensional parameter quantization index, to complete the network deployment of the pre-deployed integrated sensor.

[0021] Preferably, a gas leakage detection and safety control system based on Internet of Things, a data acquisition module comprises:

[0022] A sensor control unit is configured to acquire a periodic start time node for the integrated sensor based on the management terminal and periodically trigger the integrated sensor based on the periodic start time node.

[0023] A data acquisition unit is configured to control the integrated sensor to acquire gas concentration data and environmental data in the respective monitoring area based on the periodic trigger result, extract the terminal identity of each integrated sensor, and mark the object ownership of the gas concentration data and the environmental data in the respective monitoring area based on the terminal identity.

[0024] Preferably, a gas leakage detection and safety control system based on Internet of Things, a data acquisition unit comprises:

[0025] A data acquisition subunit is configured to acquire the gas concentration data and the environmental data marked with the object ownership and determine the number of objects based on the object ownership marking result.

[0026] A storage space division subunit is configured to:

[0027] uniformly divide the to-be-stored area based on the number of objects to obtain a first storage space set, determine a first byte amount of each object ownership marked gas concentration data and environmental data, generate a guide instruction for each object based on the object ownership marking, and determine a second byte amount of the guide instruction.

[0028] split each first storage space in the first storage space set into a second storage space and a third storage space based on the second byte amount, and adaptively split the third storage space into a fourth storage space and a fifth storage space based on the first byte amount.

[0029] A storage subunit is configured to store the guide instruction for each object in the corresponding second storage space, and store the object ownership marked gas concentration data and environmental data of each object in the corresponding fourth storage space and fifth storage space, respectively.

[0030] Preferably, a gas leakage detection and safety control system based on Internet of Things, a detection module comprises:

[0031] An association analysis unit is configured to:

[0032] acquire the gas concentration data and the environmental data in the respective monitoring area, and call a gas concentration knowledge system from a server.

[0033] Based on the gas concentration knowledge extraction, determine the strong correlation data category in the environmental data which has influence on the gas concentration data, and based on the strong correlation data category, perform category screening on the environmental data to obtain key environmental data;

[0034] Perform data cleaning and standardization processing on the key environmental data and the gas concentration data, and based on the data cleaning and standardization processing results, perform analogy display on the key environmental data and the gas concentration data under different monitoring areas;

[0035] Based on the analogy display results, determine the gas concentration range corresponding to the value of different key environmental data, and construct a decision tree model, and input the value of different key environmental data as an input variable and the gas concentration range as a target variable into the decision tree model for analysis to obtain the distribution rule of the gas concentration under different key environmental data;

[0036] The change trend prediction unit is configured to:

[0037] Obtain the gas concentration data and environmental data under different monitoring areas at the current time, and based on the distribution rule, analyze the gas concentration data and environmental data under different monitoring areas at the current time, and based on the analysis results, correct the gas concentration data at the current time to obtain a reference gas concentration;

[0038] Sequentially associate the reference gas concentration at each time based on the time development sequence, and predict the gas concentration change trend at the next time based on the sequential association results;

[0039] The real-time dynamic monitoring unit is configured to:

[0040] Determine a safe gas concentration threshold based on a gas leakage safety detection protocol, and dynamically compare the gas concentration change trend with the safe gas concentration threshold;

[0041] If the difference between the reference gas concentration at the current time and the safe gas concentration threshold meets the early warning preparation condition, and the gas concentration change trend at the next time is an upward trend, it is determined that there is gas leakage.

[0042] Preferably, a gas leakage detection and safety control system based on the Internet of Things, the safety control module comprises:

[0043] The verification unit is configured to:

[0044] Determine a target integrated sensor corresponding to an abnormal gas concentration based on the real-time dynamic monitoring results, and perform self-state verification on the target integrated sensor;

[0045] After the self-state verification is passed, control the target integrated sensor to actively collect secondary data in the corresponding monitoring area, and analyze the active secondary data collection results;

[0046] When the analysis result meets the gas leakage judgment condition, the target integrated sensor is traced back to the location to obtain the gas leakage position;

[0047] The safety response unit is used for:

[0048] Based on the gas leakage position, the safety emergency equipment corresponding to the position is determined, and the safety emergency equipment is synchronously started based on the Internet of Things to perform safety response.

[0049] Preferably, a gas leakage detection and safety control system based on the Internet of Things, the safety control module comprises:

[0050] The early warning report generation unit is used for generating an early warning description based on the safety response result, and generating a corresponding early warning report based on the early warning description;

[0051] The early warning notification unit is used for:

[0052] Based on the safety response result, offline early warning notification is performed in the gas leakage area, and based on the Internet of Things, the corresponding remote monitoring end is determined;

[0053] Based on the Internet of Things, the early warning report is sent to the remote monitoring end for online early warning notification.

[0054] The present application provides a kind of gas leakage detection and safety control method based on the Internet of Things, comprising:

[0055] Step 1: based on the Internet of Things, the integrated sensor pre-deployed in application scene is networked, and based on the network deployment result, the integrated sensor collects the gas concentration data and environmental data in respective monitoring area;

[0056] Step 2: the gas concentration data and environmental data in respective monitoring area are associated and analyzed, the change trend of gas concentration is predicted, and based on the change trend, the gas leakage is dynamically monitored in real time;

[0057] Step 3: based on the real-time dynamic monitoring result, when there is gas leakage, the safety emergency equipment is synchronously started based on the Internet of Things to perform safety response, and the safety response result is synchronously sent to the remote monitoring end for early warning notification.

[0058] Preferably, a gas leakage detection and safety control method based on the Internet of Things, in step 1, based on the Internet of Things, the integrated sensor pre-deployed in application scene is networked, comprising:

[0059] Obtain the area distribution diagram of application scene, and determine the spatial layout and functional attribute of different areas in application scene based on the area distribution diagram;

[0060] The degree of preference of gas detection for different regions is determined based on the functional attributes, and the spatial layout of the corresponding region is structurally analyzed based on the degree of preference of gas detection, to determine the gas detection key point of the corresponding region;

[0061] The number and position of the integrated sensor of each region are counted based on the gas detection key point, and the integrated sensor is deployed based on the counting result.

[0062] Compared with the prior art, the beneficial effects of the present application are as follows:

[0063] Through the network deployment of the pre-deployed integrated sensor in the application scene, the integrated sensors can be effectively controlled, and the data collected by the integrated sensors can be received, and then the gas concentration data and environmental data in the monitoring area of each integrated sensor are collected through the network deployment of the integrated sensor, ensuring the reliability and comprehensiveness of the collected gas concentration data and environmental data, and then the obtained gas concentration data and environmental data are analyzed, and the gas leakage is dynamically monitored in real time according to the analysis result, so that the gas leakage can be found in time, and the timeliness and accuracy of the gas leakage are improved, and finally when the gas leakage is determined, the safety emergency equipment is started in time to respond to safety, and the warning notification is synchronized, so that the related personnel can find the abnormality in time, and the corresponding emergency measures can be taken in time, and the effect of gas leakage detection and safety control is ensured.

[0064] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structure specifically pointed out in the present application document.

[0065] The technical solutions of the present application will be further described in detail below with the help of the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0066] The drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0067] Figure 1 is a structure diagram of a gas leakage detection and safety control system based on Internet of Things in an embodiment of the present application;

[0068] Figure 2 is a structure diagram of a data acquisition module in a gas leakage detection and safety control system based on Internet of Things in embodiment 4 of the present application;

[0069] Figure 3A flow chart of a gas leakage detection and safety control method based on an Internet of Things in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

[0071] Embodiment 1

[0072] The present embodiment provides a gas leakage detection and safety control system based on an Internet of Things, as shown in FIG. 1, which comprises: Figure 1

[0073] A data collection module is configured to perform network deployment on the pre-deployed integrated sensors in the application scenario based on the Internet of Things, and control the integrated sensors to collect gas concentration data and environmental data in their respective monitoring areas based on the network deployment results.

[0074] A detection module is configured to perform correlation analysis on the gas concentration data and environmental data in the respective monitoring areas, predict the change trend of the gas concentration, and perform real-time dynamic monitoring on the gas leakage based on the change trend.

[0075] A safety control module is configured to, based on the real-time dynamic monitoring results, determine that there is a gas leakage, synchronously start the safety emergency equipment to perform safety response based on the Internet of Things, and synchronously send the safety response results to the remote monitoring end to perform early warning notification.

[0076] In the present embodiment, the integrated sensors comprise gas concentration detection sensors and environmental detection sensors, wherein the environmental detection sensors comprise temperature sensors, humidity sensors, pressure sensors, and the like.

[0077] In the present embodiment, the network deployment refers to routing allocation and parameter adaptation on the pre-deployed integrated sensors, so as to ensure that the integrated sensors can be effectively controlled.

[0078] In the present embodiment, the environmental data comprises temperature data, humidity data, pressure data, and the like.

[0079] In the present embodiment, the correlation analysis refers to comprehensive analysis on the gas concentration data and environmental data, aiming to determine the influence of the environmental data on the gas concentration data, so as to correct the gas concentration at different time points, and ensure the reliability of the final gas concentration.

[0080] In the present embodiment, the safety emergency equipment is set in advance, and different detection areas are provided with safety emergency equipment, such as valves or fans.

[0081] ​In this embodiment, the remote monitoring terminal can be a user's mobile phone terminal or the like.

[0082] The working principle and beneficial effects of the above technical solution are: by deploying the integrated sensors pre-deployed in the application scene in the network, the integrated sensors can be effectively controlled, and the data collected by the integrated sensors can be received, and then the integrated sensors deployed in the network collect the gas concentration data and environmental data in their respective monitoring areas, ensuring the reliability and comprehensiveness of the collected gas concentration data and environmental data. Secondly, the obtained gas concentration data and environmental data are analyzed, and the gas leakage is dynamically monitored in real time according to the analysis result, which facilitates timely discovery of gas leakage and improves the timeliness and accuracy of gas leakage. Finally, when it is determined that there is gas leakage, the safety emergency equipment is started in time to respond to safety, and a warning notification is simultaneously performed, which facilitates relevant personnel to discover abnormalities in time and facilitates timely adoption of corresponding emergency measures, thereby ensuring the effect of gas leakage detection and safety control.

[0083] Embodiment 2

[0084] Based on the embodiment 1, the embodiment provides a gas leakage detection and safety control system based on the Internet of Things, and a data acquisition module, comprising:

[0085] A scene analysis unit is configured to acquire a regional distribution map of the application scene, and determine the spatial layout and functional attribute of different regions in the application scene based on the regional distribution map.

[0086] A sensor position and quantity determination unit is configured to determine the gas detection preference degree of different regions based on the functional attribute, and perform structural analysis on the spatial layout of the corresponding region based on the gas detection preference degree, and determine the gas detection key point of the corresponding region.

[0087] A sensor deployment guidance unit is configured to count the number and position of the integrated sensors of each region based on the gas detection key point, and guide the deployment of the integrated sensors based on the statistical result.

[0088] In this embodiment, the functional attribute refers to the type of different regions, for example, the function of the kitchen can be to provide space for cooking, and the functional attribute of the bedroom is to provide space for rest.

[0089] In this embodiment, the gas detection preference degree refers to the strictness of detecting gas in different regions.

[0090] In this embodiment, the gas detection key point refers to the position that needs to be focused on for gas detection.

[0091] The working principle and beneficial effects of the above technical solution are: by determining the spatial layout and functional attributes of different areas in the application scenario, the degree of gas detection of different areas is locked according to the functional attributes, and at the same time, the gas detection key points of the corresponding area are determined according to the spatial layout. Finally, the number and position of the integrated sensor of each area are counted according to the determined gas detection key points, realizing effective deployment guidance of the integrated sensor, providing convenience and guarantee for collecting gas concentration data and environmental data, and providing reliable guarantee for gas leakage detection and safety control.

[0092] Embodiment 3:

[0093] Based on the embodiment 1, the embodiment provides a gas leakage detection and safety control system based on Internet of Things, a data acquisition module, comprising:

[0094] A networking unit, configured to:

[0095] Determine the available local area network in the application scenario based on Internet of Things, and perform port adaptation on the local area network based on the pre-deployed integrated sensor in the application scenario;

[0096] Based on the port adaptation result, assign a routing port to each pre-deployed integrated sensor in the local area network, and network and debug each pre-deployed integrated sensor based on the routing port;

[0097] A sensor configuration unit, configured to:

[0098] Based on the networking and debugging results, initialize the devices of each integrated sensor, and configure the network parameters of each integrated sensor based on the device initialization;

[0099] Determine multi-dimensional parameter quantization indicators based on the gas detection requirements, and configure the working parameters of each integrated sensor after network parameter configuration based on the multi-dimensional parameter quantization indicators, to complete the network deployment of the pre-deployed integrated sensor.

[0100] In this embodiment, port adaptation is to assign a corresponding port to each integrated sensor in the local area network, so as to ensure that corresponding data acquisition and transmission can be performed.

[0101] In this embodiment, device initialization refers to resetting the parameters of each integrated sensor, so as to facilitate corresponding configuration according to requirements.

[0102] In this embodiment, the multi-dimensional parameter quantization indicator refers to the basis for measuring whether the gas leaks during gas detection, for example, the numerical value of the gas concentration.

[0103] The working principle and beneficial effects of the above technical solutions are: ensuring the reliability of the network deployment of the pre-deployed integrated sensor, and providing convenience and protection for data collection and transmission of the pre-deployed integrated sensor.

[0104] Embodiment 4:

[0105] Based on the embodiment 1, the embodiment provides a gas leakage detection and safety control system based on Internet of Things, as shown in Figure 2 The data acquisition module comprises:

[0106] The sensor control unit is configured to obtain a periodic start time node of the integrated sensor based on the management terminal, and periodically trigger the integrated sensor based on the periodic start time node.

[0107] The data acquisition unit is configured to control the integrated sensor to collect gas concentration data and environmental data in the respective monitoring area based on the periodic trigger result, and extract a terminal identity of each integrated sensor and mark the gas concentration data and the environmental data in the respective monitoring area based on the terminal identity.

[0108] In this embodiment, the periodic start time node refers to the time node for triggering the integrated sensor, and the time node is periodic.

[0109] In this embodiment, the object attribution marking refers to marking the collected corresponding gas concentration data and environmental data according to the terminal identity of the integrated sensor, so as to facilitate determination of the spatial area corresponding to different gas concentration data and environmental data.

[0110] The working principle and beneficial effects of the above technical solutions are: ensuring the reliability of the network deployment of the pre-deployed integrated sensor, and providing convenience and protection for data collection and transmission of the pre-deployed integrated sensor.

[0111] Embodiment 5:

[0112] Based on the embodiment 4, the embodiment provides a gas leakage detection and safety control system based on Internet of Things, and the data acquisition unit comprises:

[0113] The data acquisition subunit is configured to acquire the gas concentration data and the environmental data after the object attribution marking, and determine the number of objects based on the object attribution marking result.

[0114] The storage space division subunit is configured to:

[0115] The object number is used to uniformly divide the storage area, to obtain a first storage space set, and to determine a first byte amount of the marked gas concentration data and environment data of each object, and meanwhile, a guide instruction of each object is generated based on the object mark, and a second byte amount of the guide instruction is determined;

[0116] Each first storage space in the first storage space set is split into a second storage space and a third storage space based on the second byte amount, and the third storage space is adaptively split into a fourth storage space and a fifth storage space based on the first byte amount.

[0117] The storage subunit is configured to store the guide instruction of each object in the corresponding second storage space, and to store the marked gas concentration data and environment data of each object in the corresponding fourth storage space and fifth storage space, respectively.

[0118] In this embodiment, the object number refers to the data collected by different integrated sensors currently existing, and one integrated sensor corresponds to one object number.

[0119] In this embodiment, the first byte amount refers to the data amount of the gas concentration data and the environment data, respectively.

[0120] In this embodiment, the guide instruction refers to an instruction generated according to the object mark, and used to represent the corresponding relationship between each object and the gas concentration data and the environment data.

[0121] In this embodiment, the second byte amount refers to the data amount of the guide instruction.

[0122] In this embodiment, the second storage space and the third storage space refer to two regions obtained by splitting the first storage space, one region is used to store the guide instruction, and the other region is used to store the gas concentration data and the environment data.

[0123] In this embodiment, the fourth storage space and the fifth storage space refer to two spaces adaptively split from the third storage space according to the first byte amount, that is, the third storage space is divided according to the data amount of the gas concentration data and the environment data, and the gas concentration data and the environment data are stored, respectively.

[0124] The working principle and beneficial effects of the above technical solution are as follows: the generated guide instruction, gas concentration data and environment data are stored in different regions, which ensures the orderliness and reliability of the storage of different types of data, and provides convenience and guarantee for data retrieval.

[0125] Embodiment 6:

[0126] The embodiment is based on the embodiment 1, and provides a gas leakage detection and safety control system based on Internet of Things, a detection module comprising:

[0127] An association analysis unit is configured to:

[0128] acquire gas concentration data and environmental data in each monitoring area, and call a gas concentration knowledge system from a server;

[0129] determine a strongly associated data category in the environmental data that has an impact on the gas concentration data based on the gas concentration knowledge extraction, and perform category filtering on the environmental data based on the strongly associated data category to obtain key environmental data;

[0130] perform data cleaning and standardization processing on the key environmental data and the gas concentration data, and perform analogy display on the key environmental data and the gas concentration data under different monitoring areas based on the data cleaning and standardization processing results;

[0131] determine a gas concentration range corresponding to a value of different key environmental data based on the analogy display results, simultaneously construct a decision tree model, and input the value of different key environmental data as an input variable and the gas concentration range as a target variable into the decision tree model for analysis to obtain a distribution rule of the gas concentration under different key environmental data;

[0132] A change trend prediction unit is configured to:

[0133] acquire gas concentration data and environmental data under different monitoring areas at a current time, analyze the gas concentration data and the environmental data under different monitoring areas at the current time based on the distribution rule, and correct the gas concentration data at the current time based on the analysis results to obtain a reference gas concentration;

[0134] sequentially associate the reference gas concentrations at each time based on a time development sequence, and predict a gas concentration change trend at a next time based on the sequential association results;

[0135] A real-time dynamic monitoring unit is configured to:

[0136] determine a safe gas concentration threshold based on a gas leakage safety detection protocol, and dynamically compare the gas concentration change trend with the safe gas concentration threshold;

[0137] if a difference between the reference gas concentration at the current time and the safe gas concentration threshold satisfies an early warning preparation condition, and the gas concentration change trend at the next time is an upward trend, it is determined that there is a gas leakage.

[0138] In the embodiment, the gas concentration knowledge system is acquired from the server and is used to record impact factors in the environment that have an impact on the gas concentration.

[0139] In this embodiment, the strong correlation data category is the category of environmental data that affects the gas concentration determined according to the gas concentration knowledge system.

[0140] In this embodiment, the key environmental data refers to the result obtained by classifying the environmental data according to the strong correlation data category, that is, the specific environmental data corresponding to the strong correlation data category in the environmental data.

[0141] In this embodiment, the analogy display refers to comparing and displaying the key environmental data and the gas concentration data in different monitoring areas, and the purpose is to determine the gas concentration range corresponding to the value of different key environmental data, so as to provide a basis for detecting gas leakage.

[0142] In this embodiment, the reference gas concentration refers to the influence degree of environmental data on gas concentration determined by analyzing the gas concentration data and environmental data in different monitoring areas at the current time according to the distribution rule, and the final result obtained by correcting the gas concentration data according to the influence degree.

[0143] In this embodiment, the gas leakage safety detection protocol is set in advance and is used to represent the safe value of gas concentration allowed to appear in different spatial areas.

[0144] In this embodiment, the early warning preparation condition is set in advance and is used as a basis for measuring whether to alarm for gas leakage, and can be adjusted.

[0145] The working principle and beneficial effects of the above technical solution are: to ensure the accuracy and reliability of detecting whether the gas leaks, and to facilitate timely taking appropriate emergency response measures when gas leakage is found, thereby improving the reliability and effect of gas leakage detection.

[0146] Embodiment 7:

[0147] Based on embodiment 1, the embodiment provides a gas leakage detection and safety control system based on the Internet of Things, and the safety control module comprises:

[0148] The verification unit is configured to:

[0149] Determine the target integrated sensor corresponding to the abnormal gas concentration based on the real-time dynamic monitoring result, and perform self-state verification on the target integrated sensor;

[0150] After the self-state verification is passed, the target integrated sensor is controlled to perform active secondary data acquisition on the corresponding monitoring area, and the active secondary data acquisition result is analyzed;

[0151] When the analysis result meets the gas leakage judgment condition, the target integrated sensor is subjected to position tracing to obtain the gas leakage position.

[0152] a safety response unit, configured to:

[0153] determine a safety emergency device corresponding to the position based on the gas leakage position, and synchronously start the safety emergency device to perform safety response based on the Internet of Things.

[0154] In this embodiment, the target integrated sensor refers to an integrated sensor corresponding to an abnormal gas concentration.

[0155] In this embodiment, the active secondary data acquisition refers to re-acquiring the gas concentration data of the corresponding monitoring area after the target integrated sensor passes the self-state verification, i.e., re-inspecting the gas concentration data.

[0156] In this embodiment, the position tracing refers to determining the position of the target integrated sensor in the application scenario.

[0157] In this embodiment, the safety emergency device is deployed in advance in the application scenario, so as to timely perform corresponding safety response when gas leakage occurs, for example, it can be a gas switch valve.

[0158] The working principle and beneficial effects of the above technical solution are: the target integrated sensor corresponding to the abnormal gas concentration is controlled to perform self-state verification and active secondary data acquisition, thereby facilitating accurate verification of gas leakage, and ultimately starting the safety emergency device to perform safety response when determining gas leakage, thereby improving the safety factor.

[0159] Embodiment 8:

[0160] On the basis of embodiment 1, this embodiment provides a gas leakage detection and safety control system based on the Internet of Things, and a safety control module, comprising:

[0161] a warning report generation unit, configured to generate a warning description based on the safety response result, and generate a corresponding warning report based on the warning description;

[0162] a warning notification unit, configured to:

[0163] perform offline warning notification in the gas leakage area based on the safety response result, and simultaneously determine a remote monitoring end based on the Internet of Things;

[0164] send the warning report to the remote monitoring end for online warning notification based on the Internet of Things.

[0165] In this embodiment, the warning description refers to text information describing the safety response result.

[0166] In this embodiment, the offline warning notification can be a ringing alarm.

[0167] In this embodiment, the online early warning notification can be transmitting the alarm information to the corresponding remote monitoring end for alarm notification.

[0168] The working principle and beneficial effects of the above technical solution are: the offline early warning notification and the online early warning notification are used for early warning notification, so that different user groups can timely find abnormal conditions, and the safety response effect is improved.

[0169] Embodiment 9:

[0170] The embodiment provides a gas leakage detection and safety control method based on an Internet of Things, as shown in the following figure, which comprises the following steps: Figure 3

[0171] Step 1: based on the Internet of Things, network deployment is performed on the pre-deployed integrated sensors in the application scenario, and based on the network deployment result, the integrated sensors collect gas concentration data and environmental data in their respective monitoring areas;

[0172] Step 2: correlation analysis is performed on the gas concentration data and environmental data in the respective monitoring areas, the change trend of the gas concentration is predicted, and real-time dynamic monitoring of the gas leakage is performed based on the change trend;

[0173] Step 3: based on the real-time dynamic monitoring result, when it is determined that there is gas leakage, the safety emergency equipment is synchronously started based on the Internet of Things for safety response, and the safety response result is synchronously sent to the remote monitoring end for early warning notification.

[0174] The working principle and beneficial effects of the above technical solution are: through network deployment on the pre-deployed integrated sensors in the application scenario, the integrated sensors can be effectively controlled, and the data collected by the integrated sensors can be received, and then the integrated sensors deployed by the network collect the gas concentration data and environmental data in their respective monitoring areas, ensuring the reliability and comprehensiveness of the collected gas concentration data and environmental data. Secondly, the obtained gas concentration data and environmental data are correlated and analyzed, and real-time dynamic monitoring of the gas leakage is performed according to the analysis result, so that the gas leakage can be found in time, and the timeliness and accuracy of the gas leakage are improved. Finally, when it is determined that there is gas leakage, the safety emergency equipment is started in time for safety response, and the early warning notification is synchronously performed, so that the related personnel can find the abnormality in time, and the corresponding emergency measures can be taken in time, and the effect of the gas leakage detection and safety control is ensured.

[0175] Embodiment 10:

[0176] ​Based on embodiment 9, the present embodiment provides a gas leakage detection and safety control method based on Internet of Things, in step 1, the integrated sensors pre-deployed in the application scene are networked based on Internet of Things, including:

[0177] The regional distribution map of the application scene is obtained, and the spatial layout and functional attributes of different regions in the application scene are determined based on the regional distribution map;

[0178] The gas detection preference degree of different regions is determined based on the functional attributes, and the spatial layout of the corresponding region is structurally analyzed based on the gas detection preference degree to determine the gas detection key point of the corresponding region;

[0179] The number and position of the integrated sensors of each region are counted based on the gas detection key point, and the integrated sensors are deployed based on the statistical results.

[0180] The working principle and beneficial effects of the above technical scheme are: by determining the spatial layout and functional attributes of different regions in the application scene, the gas detection degree of different regions is locked according to the functional attributes, at the same time, the gas detection key point of the corresponding region is determined according to the spatial layout, finally, the number and position of the integrated sensors of each region are counted according to the determined gas detection key point, the integrated sensors are effectively deployed, which provides convenience and guarantee for collecting gas concentration data and environmental data, and also provides reliable guarantee for gas leakage detection and safety control.

[0181] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. An Internet of Things based gas leakage detection and safety control system, characterized in that, include: The data acquisition module is used to deploy pre-deployed integrated sensors in the application scenario based on the Internet of Things, and to control the integrated sensors to collect gas concentration data and environmental data in their respective monitoring areas based on the network deployment results. The detection module is used to perform correlation analysis on gas concentration data and environmental data in their respective monitoring areas, predict the changing trend of gas concentration, and perform real-time dynamic monitoring of gas leaks based on the changing trend. The safety control module is used to activate the safety emergency equipment based on the Internet of Things when a gas leak is detected based on real-time dynamic monitoring results, and to send the safety response results to the remote monitoring terminal for early warning notification. The detection module includes: The correlation analysis unit is used for: Acquire gas concentration data and environmental data within their respective monitoring areas, and retrieve gas concentration knowledge system from the server; Based on knowledge of gas concentration, the strongly correlated data categories that affect gas concentration data in environmental data are identified, and the environmental data are then filtered based on these strongly correlated data categories to obtain key environmental data. Key environmental data and gas concentration data are cleaned and standardized, and the key environmental data and gas concentration data in different monitoring areas are compared and displayed based on the results of the data cleaning and standardization. Based on the analogy results, the range of gas concentration corresponding to different key environmental data values ​​is determined. At the same time, a decision tree model is constructed, and the different key environmental data values ​​are used as input variables, while the gas concentration range is used as the target variable. The analysis is performed on the decision tree model to obtain the distribution pattern of gas concentration under different key environmental data. Trend prediction unit, used for: The gas concentration data and environmental data of different monitoring areas at the current time are obtained, and the gas concentration data and environmental data of different monitoring areas at the current time are analyzed based on the distribution pattern. Based on the analysis results, the gas concentration data at the current time is corrected to obtain the baseline gas concentration. Based on the time development sequence, the baseline gas concentration at each moment is sequentially correlated, and the gas concentration change trend at the next moment is predicted based on the sequential correlation results. The real-time dynamic monitoring unit is used for: The safe gas concentration threshold is determined based on the gas leak safety detection protocol, and the gas concentration change trend is dynamically compared with the safe gas concentration threshold. If the difference between the current baseline gas concentration and the safe gas concentration threshold meets the warning preparation conditions, and the gas concentration trend at the next moment shows an upward trend, it is determined that there is a gas leak. The data acquisition module includes: The sensor control unit is used to obtain the periodic start-up time node of the integrated sensor based on the management terminal, and to periodically trigger the integrated sensor based on the periodic start-up time node; The data acquisition unit is used to control the integrated sensors to collect gas concentration data and environmental data in their respective monitoring areas based on the periodic triggering results. At the same time, it extracts the terminal identity of each integrated sensor and marks the gas concentration data and environmental data in their respective monitoring areas based on the terminal identity. The data acquisition subunit is used to acquire gas concentration data and environmental data after object attribution marking, and to determine the number of objects based on the object attribution marking results; The storage space is divided into sub-units for: The storage area to be stored is evenly divided based on the number of objects to obtain the first set of storage spaces. The gas concentration data and environmental data after the object's ownership mark are determined by the first byte. At the same time, a guide description for each object is generated based on the object's ownership mark, and the guide description is determined by the second byte. Based on the second byte amount, each first storage space in the first storage space set is split into a second storage space and a third storage space, and based on the first byte amount, the third storage space is adaptively split into a fourth storage space and a fifth storage space; The storage subunit is used to store the guidance description of each object in the corresponding second storage space, and at the same time, store the gas concentration data and environmental data after each object is assigned affixed in the corresponding fourth and fifth storage spaces, respectively.

2. The gas leakage detection and safety control system based on the Internet of Things according to claim 1, characterized in that, The data acquisition module includes: The scene analysis unit is used to obtain the regional distribution map of the application scene and determine the spatial layout and functional attributes of different areas in the application scene based on the regional distribution map. The sensor location and quantity determination unit is used to determine the degree of gas detection preference for different areas based on functional attributes, and to perform structural analysis of the spatial layout of the corresponding areas based on the degree of gas detection preference, thereby determining the key points for gas detection in the corresponding areas. The sensor deployment guidance unit is used to count the number and location of integrated sensors in each area based on key gas detection points, and to provide deployment guidance for the integrated sensors based on the statistical results.

3. The gas leakage detection and safety control system based on the Internet of Things according to claim 1, characterized in that, The data acquisition module includes: Networking unit, used for: Based on the Internet of Things, the available local area networks in the application scenario are determined, and the ports of the local area networks are adapted based on the pre-deployed integrated sensors in the application scenario. Based on the port adaptation results, a routing port is assigned to each pre-deployed integrated sensor in the local area network, and the pre-deployed integrated sensors are networked and debugged based on the routing ports. Sensor configuration unit, used for: Based on the networking and debugging results, the devices of each integrated sensor are initialized, and the network parameters of each integrated sensor are configured based on the device initialization. Based on the requirements for gas detection, multi-dimensional parameter quantification indicators are determined, and based on these indicators, the working parameters of each integrated sensor after network parameter configuration are configured, thus completing the network deployment of the pre-deployed integrated sensors.

4. The gas leakage detection and safety control system based on the Internet of Things according to claim 1, characterized in that, The security control module includes: Verification unit, used for: Based on real-time dynamic monitoring results, the target integrated sensor corresponding to the abnormal gas concentration is determined, and the self-state verification of the target integrated sensor is performed. After its own status verification is passed, the integrated sensor of the control target actively collects secondary data in the corresponding monitoring area and analyzes the results of the active secondary data collection. When the analysis results meet the conditions for determining a gas leak, the location of the gas leak is obtained by tracing the location of the target integrated sensor. The security response unit is used for: Based on the location of the gas leak, the corresponding safety emergency equipment is determined, and the safety emergency equipment is activated synchronously based on the Internet of Things to carry out a safety response.

5. The gas leakage detection and safety control system based on the Internet of Things according to claim 1, characterized in that, The security control module includes: The early warning report generation unit is used to generate an early warning description based on the security response results, and to generate a corresponding early warning report based on the early warning description; The early warning notification unit is used for: Based on the safety response results, offline early warning notifications are issued in the gas leak area, and at the same time, the corresponding remote monitoring terminal is determined based on the Internet of Things; The Internet of Things (IoT) enables the sending of early warning reports to remote monitoring terminals for online early warning notifications.

6. A gas leakage detection and safety control method based on Internet of Things, characterized in that, include: Step 1: Deploy the pre-deployed integrated sensors in the application scenario based on the Internet of Things, and control the integrated sensors to collect gas concentration data and environmental data in their respective monitoring areas based on the network deployment results; Step 2: Perform correlation analysis on the gas concentration data and environmental data in their respective monitoring areas, predict the changing trend of gas concentration, and conduct real-time dynamic monitoring of gas leaks based on the changing trend. Step 3: When a gas leak is confirmed based on real-time dynamic monitoring results, the safety emergency equipment is activated synchronously via the Internet of Things to conduct a safety response, and the safety response results are simultaneously sent to the remote monitoring terminal for early warning notification; Step 2 includes: Acquire gas concentration data and environmental data within their respective monitoring areas, and retrieve gas concentration knowledge system from the server; Based on knowledge of gas concentration, the strongly correlated data categories that affect gas concentration data in environmental data are identified, and the environmental data are then filtered based on these strongly correlated data categories to obtain key environmental data. Key environmental data and gas concentration data are cleaned and standardized, and the key environmental data and gas concentration data in different monitoring areas are compared and displayed based on the results of the data cleaning and standardization. Based on the analogy results, the range of gas concentration corresponding to different key environmental data values ​​is determined. At the same time, a decision tree model is constructed, and the different key environmental data values ​​are used as input variables, while the gas concentration range is used as the target variable. The analysis is performed on the decision tree model to obtain the distribution pattern of gas concentration under different key environmental data. The gas concentration data and environmental data of different monitoring areas at the current time are obtained, and the gas concentration data and environmental data of different monitoring areas at the current time are analyzed based on the distribution pattern. Based on the analysis results, the gas concentration data at the current time is corrected to obtain the baseline gas concentration. Based on the time development sequence, the baseline gas concentration at each moment is sequentially correlated, and the gas concentration change trend at the next moment is predicted based on the sequential correlation results. The safe gas concentration threshold is determined based on the gas leak safety detection protocol, and the gas concentration change trend is dynamically compared with the safe gas concentration threshold. If the difference between the current baseline gas concentration and the safe gas concentration threshold meets the warning preparation conditions, and the gas concentration trend at the next moment shows an upward trend, it is determined that there is a gas leak. Step 1 includes: The integrated sensor is periodically triggered based on the periodic start time node obtained from the management terminal. Based on the periodic trigger result control, the integrated sensors collect gas concentration data and environmental data in their respective monitoring areas. At the same time, the terminal identity of each integrated sensor is extracted, and the gas concentration data and environmental data in their respective monitoring areas are marked with object affiliation based on the terminal identity. Obtain gas concentration data and environmental data after object attribution marking, and determine the number of objects based on the object attribution marking results; The storage area to be stored is evenly divided based on the number of objects to obtain the first set of storage spaces. The gas concentration data and environmental data after the object's ownership mark are determined by the first byte. At the same time, a guide description for each object is generated based on the object's ownership mark, and the guide description is determined by the second byte. Based on the second byte amount, each first storage space in the first storage space set is split into a second storage space and a third storage space, and based on the first byte amount, the third storage space is adaptively split into a fourth storage space and a fifth storage space; The guidance description for each object is stored in the corresponding second storage space. At the same time, the gas concentration data and environmental data after each object is assigned a label are stored in the corresponding fourth and fifth storage spaces, respectively.

7. The gas leakage detection and safety control method based on the Internet of Things according to claim 6, characterized in that, In step 1, the network deployment of pre-deployed integrated sensors in the application scenario is carried out based on the Internet of Things, including: Obtain the regional distribution map of the application scenario, and determine the spatial layout and functional attributes of different areas in the application scenario based on the regional distribution map; Based on functional attributes, the degree of preference for gas detection in different areas is determined, and based on the degree of preference for gas detection, the spatial layout of the corresponding areas is structurally analyzed to determine the key points for gas detection in the corresponding areas. Based on the key points of gas detection, the number and location of integrated sensors in each area are statistically analyzed, and deployment guidelines for integrated sensors are provided based on the statistical results.

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