Data acquisition optimization method and system for NB-iot gas device, device, and medium

Abstract

Disclosed are a data acquisition optimization method and system for an NB-Internet of Things (IoT) gas device, a device, and a medium. The method comprises: acquiring a service registration packet of a target NB-IoT gas device, and parsing the service registration packet to obtain first service parsing data; performing decryption and enhancement processing on the first service parsing data to obtain first target data, and returning a registration success notification on the basis of the first target data and a corresponding device linkage rule; acquiring an actual service packet of the target NB-IoT gas device, and parsing the actual service packet to obtain second service parsing data; and performing decryption and enhancement processing on the second service parsing data to obtain second target data, returning a receiving success notification on the basis of the second target data and a corresponding device linkage rule, and forwarding the second target data to an IoT SaaS application platform. The present invention improves the acquisition success rate and the acquisition efficiency of data acquisition of NB-IoT gas devices, and can be applied to the technical field of IoT.

Description

NB-IoT gas equipment data collection optimization method and system, equipment and medium Technical Field

[0001] The present invention relates to the field of Internet of Things technology, and in particular to an NB-IoT gas equipment data acquisition optimization method and system, equipment, and medium. Background Art

[0002] The gas industry is a crucial issue for people's well-being. With the development of urbanization and the advancement of the digital transformation of gas, smart NB-IoT gas equipment is becoming increasingly prevalent. To ensure data security and the success rate of data reporting and collection, most smart NB-IoT gas equipment currently uses an encrypted responsive reporting method. This means that throughout the data collection process, smart NB-IoT gas equipment transmits data with encryption parameters. The IoT PaaS cloud platform pushes the device-reported data to the SaaS application. After receiving the message and verifying the data, the SaaS application sends a reply with a command containing the encryption parameters. The device will only proceed to the next step of data reporting after receiving the confirmation command. If the device does not receive the confirmation command, the data report is deemed to have failed and the device will enter the failure retransmission mechanism, waiting to send the data again.

[0003] As the number of smart NB-IoT gas devices has surged in recent years along with the number of residential users, data collection for large-scale smart gas devices currently faces the following challenges:

[0004] 1) Large-scale devices report simultaneously, resulting in a large amount of concurrent data being reported and a sharp increase in the amount of subscription and push data. This increases the pressure on the SaaS application server to receive and process data, causing data processing congestion on the application server, leading to data loss, and again causing the device to retransmit subsequent data. The cycle worsens, forming a southbound data storm, resulting in a large number of data collection failures.

[0005] 2) In the encrypted response reporting mode adopted by smart gas equipment, the concentrated reporting of a large number of devices triggers a large number of command issuance API interface calls, increasing northbound TPS, triggering flow control restrictions at all levels, causing command response downlink failures, and message confirmation commands cannot be sent to the device side, resulting in device retransmission, exacerbating congestion problems, and reducing the success rate and efficiency of device data collection.

[0006] To address the above issues, the current common solutions are to expand the discrete interval for reporting data from smart NB-IoT gas devices or to increase the concurrent data processing performance of the server. However, the above solutions are costly and, as the number of smart gas meters increases, they cannot fundamentally solve the problems of reduced success rate and efficiency in data collection for large-scale gas devices.

[0007] Summary of the Invention

[0008] The purpose of the present invention is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0009] To this end, an object of an embodiment of the present invention is to provide an NB-IoT gas equipment data collection optimization method, which improves the collection success rate and collection efficiency of NB-IoT gas equipment data collection.

[0010] Another object of an embodiment of the present invention is to provide an NB-IoT gas equipment data acquisition and optimization system.

[0011] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present invention include:

[0012] In one aspect, an embodiment of the present invention provides an NB-IoT gas equipment data collection optimization method, comprising the following steps:

[0013] Obtaining a service registration message of a target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parsing the service registration message to obtain first service parsing data;

[0014] Decrypting and enhancing the first service parsed data to obtain first target data, and returning a registration success notification to the target NB-IoT gas device based on the first target data and the corresponding device linkage rule;

[0015] Obtaining an actual business message of the target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parsing the actual business message to obtain second business parsing data;

[0016] The second business parsed data is decrypted and enhanced to obtain the second target data, and a successful reception notification is returned to the target NB-IoT gas device according to the second target data and the corresponding device linkage rules, and then the second target data is forwarded to the Internet of Things SaaS application platform.

[0017] Furthermore, in one embodiment of the present invention, the NB-IoT gas device data collection optimization method further includes a step of activating and logging in to the target NB-IoT gas device, which specifically includes:

[0018] Establishing a thing model on the IoT PaaS cloud platform and configuring a rule base, wherein the rule base includes data decryption processing rules and device linkage rules;

[0019] Sending a device login message to the Internet of Things PaaS cloud platform through the target NB-IoT gas device, wherein the device login message includes a registration lifetime field and a device unique identification number;

[0020] The target NB-IoT gas device is activated and logged in authenticated through the IoT PaaS cloud platform according to the registration lifetime field and the device unique identification number. When the authentication is successful, the registration lifetime timer is set and started according to the registration lifetime field, the session information of the target NB-IoT gas device is saved, and an activation login success notification is returned to the target NB-IoT gas device.

[0021] Furthermore, in one embodiment of the present invention, the step of obtaining the service registration message of the target NB-IoT gas device through the IoT PaaS cloud platform specifically includes:

[0022] When the Internet of Things PaaS cloud platform detects that the target NB-IoT gas device is connected, the online status of the target NB-IoT gas device is determined according to the registration lifetime timer;

[0023] When it is determined that the target NB-IoT gas device is online, the registration lifetime timer is reset, and the service registration message sent by the target NB-IoT gas device is received through the Internet of Things PaaS cloud platform;

[0024] When it is determined that the target NB-IoT gas device is offline, the historical session information of the target NB-IoT gas device is obtained according to the unique identification number of the device, and whether the target NB-IoT gas device has been activated and logged in is determined according to the historical session information. If so, the registration lifetime timer is reset, and the service registration message sent by the target NB-IoT gas device is received through the Internet of Things PaaS cloud platform.

[0025] Furthermore, in one embodiment of the present invention, the step of parsing the service registration message to obtain the first service parsing data specifically includes:

[0026] Querying the attribute field, parameter field, and service field of the object model, and determining the corresponding relationship between the attribute field and the service field;

[0027] Parsing the service registration message according to the attribute field, the parameter field, the service field, and the corresponding relationship to obtain the first service parsing data;

[0028] The first business parsing data is stored in the message queue module of the Internet of Things PaaS cloud platform.

[0029] Furthermore, in one embodiment of the present invention, the step of decrypting and enhancing the first service parsed data to obtain first target data, and returning a registration success notification to the target NB-IoT gas device according to the first target data and the corresponding device linkage rule, specifically includes:

[0030] Obtain the data decryption processing rule and the device linkage rule corresponding to the target NB-IoT gas device in the rule base;

[0031] Decrypting and enhancing the first business parsing data in the message queue module according to the data decryption processing rule to obtain the first target data;

[0032] The registration success notification is generated according to the first target data and the device linkage rule, and the registration success notification is sent to the target NB-IoT gas device through an instruction sending module.

[0033] Furthermore, in one embodiment of the present invention, the step of returning a successful reception notification to the target NB-IoT gas device according to the second target data and the corresponding device linkage rule, and then forwarding the second target data to the Internet of Things SaaS application platform, specifically includes:

[0034] Generate the successful reception notification and the service control instruction according to the second target data and the device linkage rule, and send the successful reception notification and the service control instruction to the target NB-IoT gas device through the instruction sending module;

[0035] A SaaS application subscription address is determined according to the device linkage rule, and the second target data is forwarded to the Internet of Things SaaS application platform according to the SaaS application subscription address.

[0036] Furthermore, in one embodiment of the present invention, the NB-IoT gas equipment data collection optimization method further includes the following steps:

[0037] When the IoT PaaS cloud platform does not receive a data reception response returned by the IoT SaaS application platform within a preset first time threshold, the IoT PaaS cloud platform re-forwards the second target data to the IoT SaaS application platform according to a preset re-push rule until the IoT PaaS cloud platform receives a data reception response returned by the IoT SaaS application platform;

[0038] When the Internet of Things PaaS cloud platform does not receive the data reception response returned by the Internet of Things SaaS application platform within a preset second time threshold, a data push failure record is generated and stored by the Internet of Things PaaS cloud platform.

[0039] On the other hand, an embodiment of the present invention provides an NB-IoT gas equipment data acquisition and optimization system, including:

[0040] A service registration message parsing module is used to obtain a service registration message of a target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the service registration message to obtain first service parsing data;

[0041] A registration success notification return module, configured to decrypt and enhance the first service parsing data to obtain first target data, and return a registration success notification to the target NB-IoT gas device based on the first target data and the corresponding device linkage rule;

[0042] an actual business message parsing module, configured to obtain the actual business message of the target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the actual business message to obtain second business parsing data;

[0043] The target data push module is used to decrypt and enhance the second business parsing data to obtain the second target data, and return a successful reception notification to the target NB-IoT gas device based on the second target data and the corresponding device linkage rules, and then forward the second target data to the Internet of Things SaaS application platform.

[0044] On the other hand, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, the NB-IoT gas equipment data collection optimization method as described above is implemented.

[0045] On the other hand, an embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the NB-IoT gas equipment data collection optimization method as described above.

[0046] The advantages and benefits of the present invention will be described in part in the following description and will become apparent from the following description or learned through practice of the present invention:

[0047] This embodiment of the present invention obtains a service registration message from a target NB-IoT gas device through an IoT PaaS cloud platform, parses the service registration message to obtain first service resolution data, decrypts and enhances the first service resolution data to obtain first target data, and returns a registration success notification to the target NB-IoT gas device based on the first target data and the corresponding device linkage rules. The IoT PaaS cloud platform then obtains the target NB-IoT gas device's actual service message, parses the actual service message to obtain second service resolution data, decrypts and enhances the second service resolution data to obtain second target data, and returns a receipt success notification to the target NB-IoT gas device based on the second target data and the corresponding device linkage rules. The second target data is then forwarded to the IoT SaaS application platform. This embodiment of the present invention uses cloud-edge collaboration to enable uplink and downlink interaction between the IoT PaaS cloud platform and the target NB-IoT gas device, achieving automatic response to data collection and reception without requiring application-side parsing and operations. This avoids high-concurrency data push and frequent API calls, thereby improving the success rate and efficiency of NB-IoT gas device data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following introduction is made to the drawings required for use in the embodiments of the present invention. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative work.

[0049] FIG1 is a flow chart of a method for optimizing data collection of NB-IoT gas equipment provided by an embodiment of the present invention;

[0050] FIG2 is a flowchart of activating and logging in to a target NB-IoT gas device according to an embodiment of the present invention;

[0051] FIG3 is a flow chart of step S101 provided in an embodiment of the present invention;

[0052] FIG4 is another flow chart of step S101 provided in an embodiment of the present invention;

[0053] FIG5 is a flow chart of step S102 provided in an embodiment of the present invention;

[0054] FIG6 is a flow chart of step S104 provided in an embodiment of the present invention;

[0055] FIG7 is another flowchart of the NB-IoT gas equipment data collection optimization method provided by an embodiment of the present invention;

[0056] FIG8 is a timing diagram of a specific implementation of the NB-IoT gas equipment data collection optimization method provided by an embodiment of the present invention;

[0057] FIG9 is a schematic diagram of the structure of an NB-IoT gas equipment data acquisition and optimization system provided by an embodiment of the present invention;

[0058] FIG10 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and are not to be construed as limitations on the present application. It should be noted that, although the functional modules are divided in the system schematic and the logical order is shown in the flow chart, in some cases, the steps shown or described may be performed in a different order than the module division in the system schematic or the flow chart. For the step numbers in the following embodiments, they are only provided for the convenience of explanation and description, and no limitation is placed on the order between the steps. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0060] In the description of the present invention, the meaning of "a plurality" is two or more. If there is a description of "first" or "second", it is only used to distinguish technical features and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used in this document are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0061] The NB-IoT gas equipment data collection optimization method provided in the embodiments of the present application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet computer, laptop computer, desktop computer, set-top box, etc.; the server can be configured as an independent physical server, or as a server cluster or distributed system consisting of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the NB-IoT gas equipment data collection optimization method, etc., but is not limited to the above forms.

[0062] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0063] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with the relevant laws, regulations, and standards of the relevant countries and regions. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0064] The purpose of the embodiments of the present invention is to provide an optimization method for large-scale NB-IoT gas equipment data collection. Based on the cloud-edge collaboration solution, it optimizes the reporting and collection mechanism of intelligent NB-IoT gas equipment, improves the data collection success rate in large-scale gas equipment data collection scenarios, reduces optimization costs, and ensures high reliability and high security collection of IoT smart gas equipment data.

[0065] FIG1 is a flowchart of a method for optimizing data collection of NB-IoT gas equipment according to an embodiment of the present invention. Referring to FIG1 , an embodiment of the present invention provides a method for optimizing data collection of NB-IoT gas equipment, specifically comprising the following steps:

[0066] S101. Obtain a service registration message of a target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the service registration message to obtain first service parsing data.

[0067] Specifically, when the IoT PaaS cloud platform detects that a target device has been connected, it checks and obtains the business registration message reported by the target device to the IoT PaaS cloud platform as the first business message of the target device. The IoT PaaS cloud platform refreshes the lifetime counter of the device and restarts the timing; it uses the pre-established object model to parse the first business message, obtains the first business parsing data, and stores the parsed data in the IoT PaaS cloud platform message queue module.

[0068] FIG2 is a flowchart of activating and logging in a target NB-IoT gas device according to an embodiment of the present invention. Referring to FIG2 , as an optional embodiment, the NB-IoT gas device data collection optimization method further includes step S100 of activating and logging in a target NB-IoT gas device, which specifically includes:

[0069] S1001. Establish a thing model on the IoT PaaS cloud platform and configure a rule base, which includes data decryption processing rules and device linkage rules.

[0070] S1002. Send a device login message to the IoT PaaS cloud platform through the target NB-IoT gas device. The device login message includes a registration lifetime field and a device unique identification number.

[0071] S1003. Activate and log in the target NB-IoT gas device through the Internet of Things PaaS cloud platform according to the registration lifetime field and the device unique identification number. When the authentication is successful, set and start the registration lifetime timer according to the registration lifetime field, save the session information of the target NB-IoT gas device, and then return the activation login success notification to the target NB-IoT gas device.

[0072] Specifically, a physical model and heartbeat-free products are established on the IoT PaaS cloud platform, the physical model attributes, parameters and services are defined, and a rule base is configured; in the heartbeat-free mode, the device completes the activation login on the IoT PaaS cloud platform, and the IoT PaaS cloud platform obtains the lifetime field and unique identification number. After the authentication is passed, the target device platform login activation is determined, the session information is saved, and the lifetime timer is started for the target device; after the login is successful, the device reports the service registration message carrying the encryption parameters.

[0073] FIG3 is a flowchart of step S101 according to an embodiment of the present invention. Referring to FIG3 , as an optional embodiment, the step of obtaining a service registration message of a target NB-IoT gas device through the IoT PaaS cloud platform specifically includes:

[0074] S1011. When the IoT PaaS cloud platform detects that the target NB-IoT gas device is connected, the online status of the target NB-IoT gas device is determined based on the registration lifetime timer.

[0075] S1012. When it is determined that the target NB-IoT gas device is online, the registration lifetime timer is reset, and a service registration message sent by the target NB-IoT gas device is received through the IoT PaaS cloud platform;

[0076] S1013. When it is determined that the target NB-IoT gas device is offline, the historical session information of the target NB-IoT gas device is obtained according to the device's unique identification number, and whether the target NB-IoT gas device has been activated and logged in is determined according to the historical session information. If so, the registration lifetime timer is reset, and the service registration message sent by the target NB-IoT gas device is received through the IoT PaaS cloud platform.

[0077] Specifically, after the target device successfully activates and logs in to the IoT PaaS cloud platform for the first time, no matter whether it is online or offline, there is no need to log in again when reporting business data at any time. The IoT PaaS cloud platform obtains the historical session information of the target device through the globally unique identification number. The specific process is as follows:

[0078] 1) If the device is online within the lifetime timer period, refresh the lifetime timer and obtain the service reporting data;

[0079] 2) If it is not within the lifetime timer period, the device is determined to be offline, and the historical session information is read from the platform based on the device's unique identification number. The device status is updated to online, the lifetime timer is refreshed, and the service reporting data is obtained.

[0080] FIG4 is another flow chart of step S101 according to an embodiment of the present invention. Referring to FIG4 , as an optional implementation, the step of parsing the service registration message to obtain the first service parsing data specifically includes:

[0081] S1014. Query the attribute fields, parameter fields, and service fields of the object model, and determine the corresponding relationship between the attribute fields and the service fields;

[0082] S1015. Parse the service registration message according to the attribute field, parameter field, service field, and corresponding relationship to obtain first service parsing data.

[0083] S1016: Storing the first business parsed data in a message queue module of the Internet of Things PaaS cloud platform.

[0084] Specifically, the embodiment of the present invention uses the pre-established object model to parse device service data as follows:

[0085] 1) Query the attributes, parameters, service fields of the object model, and the correspondence between services and attributes;

[0086] 2) Parse the business data message obtained by the cloud platform according to the above fields to obtain the parsed data.

[0087] S102: Decrypt and enhance the first service parsed data to obtain first target data, and return a registration success notification to the target NB-IoT gas device based on the first target data and the corresponding device linkage rule.

[0088] Specifically, based on the first business parsing data in the consumer message queue module, the data decryption processing rules and device linkage rules corresponding to the device in the cloud platform rule library are read, and the data processing rules are used to decrypt and enhance the parsed data to obtain the first target data. Based on the linkage rules and the first target data, the cloud platform automatically triggers the linkage action, that is, it automatically notifies the instruction issuing module to generate an instruction issuing task carrying the first target data, and assigns the task to the corresponding device to complete the business registration success confirmation notification.

[0089] FIG5 is a flowchart of step S102 according to an embodiment of the present invention. Referring to FIG5 , as an optional implementation, decrypting and enhancing the first service parsed data to obtain first target data, and returning a registration success notification to the target NB-IoT gas device according to the first target data and the corresponding device linkage rule, specifically includes:

[0090] S1021. Obtain data decryption processing rules and device linkage rules corresponding to the target NB-IoT gas device in the rule library;

[0091] S1022: Decrypt and enhance the first business parsed data in the message queue module according to the data decryption processing rule to obtain first target data;

[0092] S1023. Generate a registration success notification according to the first target data and the device linkage rule, and send the registration success notification to the target NB-IoT gas device through the instruction sending module.

[0093] Specifically, the data processing rules and device linkage rules corresponding to the device in the cloud platform rule library are read, and the corresponding processing operations are performed as follows:

[0094] 1) Read the rules corresponding to the product to which the device belongs in the cache rule library, including rule ID, rule SQL statement, message flow rules, and linkage rules

[0095] 2) If linkage is triggered, the linkage rule status takes effect, and the interface defined in the rule is automatically called to generate a registration success notification, and the registration success notification is sent to the target NB-IoT gas device through the instruction sending module.

[0096] S103: Acquire actual business messages of the target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the actual business messages to obtain second business parsing data.

[0097] Specifically, after the device receives the business registration confirmation notification message issued by the cloud platform, it sends the encrypted actual business message; the IoT PaaS cloud platform waits for and obtains the actual business message of the target device as the second business message of the target device, saves the session information, and resets the lifetime timer; uses the pre-established object model to parse the device business data, obtains the second business parsing data, and stores the second business parsing data in the IoT PaaS cloud platform message queue module.

[0098] S104. Decrypt and enhance the second business parsed data to obtain second target data, and return a successful reception notification to the target NB-IoT gas device based on the second target data and the corresponding device linkage rule, and then forward the second target data to the Internet of Things SaaS application platform.

[0099] Specifically, the second business analysis data in the consumer message queue module is read, the data processing rules and device linkage rules corresponding to the device in the cloud platform rule library are read, the business analysis data is processed using the data processing rules to obtain the second target data, and the second target data is stored in the message queue module; based on the linkage rules and the second target data, the cloud platform asynchronously triggers and completes the linkage action of message forwarding and instruction issuance.

[0100] FIG6 is a flowchart of step S104 according to an embodiment of the present invention. Referring to FIG6 , as an optional implementation, returning a successful reception notification to the target NB-IoT gas device according to the second target data and the corresponding device linkage rule, and then forwarding the second target data to the IoT SaaS application platform, specifically includes:

[0101] S1041. Generate a successful reception notification and a service control instruction based on the second target data and the device linkage rule, and send the successful reception notification and the service control instruction to the target NB-IoT gas device through the instruction sending module;

[0102] S1042: Determine the SaaS application subscription address according to the device linkage rule, and forward the second target data to the Internet of Things SaaS application platform according to the SaaS application subscription address.

[0103] Specifically, the second target data in the message queue module is consumed, and the message is forwarded and pushed to the SaaS application; the notification instruction issuance module generates an instruction issuance task carrying the second target data, and assigns the task to the corresponding device to complete the actual business message success confirmation notification or business instruction control such as switching valves, and pushes the instruction issuance status; after the SaaS application receives the target data pushed by the IoT PaaS cloud platform, it returns a response to the cloud platform.

[0104] FIG7 is another flowchart of the NB-IoT gas equipment data collection optimization method provided by an embodiment of the present invention. Referring to FIG7 , as an optional embodiment, the NB-IoT gas equipment data collection optimization method further includes the following steps:

[0105] S105. When the IoT PaaS cloud platform does not receive a data reception response returned by the IoT SaaS application platform within a preset first time threshold, the IoT PaaS cloud platform re-forwards the second target data to the IoT SaaS application platform according to a preset re-push rule until the IoT PaaS cloud platform receives a data reception response returned by the IoT SaaS application platform.

[0106] S106: When the IoT PaaS cloud platform does not receive a data reception response returned by the IoT SaaS application platform within a preset second time threshold, a data push failure record is generated and stored through the IoT PaaS cloud platform.

[0107] Specifically, after the SaaS application receives the data pushed by the IoT PaaS cloud platform, it must return a response to the cloud platform within 5 seconds to confirm receipt of the corresponding information; if the SaaS application does not return a response to the cloud platform within 5 seconds, the IoT PaaS cloud platform will implement multi-level re-push within the device's lifetime cycle, such as 15 minutes, 1 hour, 4 hours, and 12 hours, until the SaaS application returns a response; if the SaaS application does not return a response within 12 hours, the IoT PaaS cloud platform will record the push failure record.

[0108] FIG8 is a timing diagram showing a specific implementation of the NB-IoT gas equipment data collection optimization method provided by an embodiment of the present invention. The implementation process of a specific embodiment of the present invention is described below based on FIG8 :

[0109] 1. Establish object models and heartbeat-free products on the IoT PaaS cloud platform, define object model attributes, parameters and services; and configure the rule base;

[0110] 2. In the heartbeat-free mode, the device completes activation and login on the IoT PaaS cloud platform. The device logs in to the IoT PaaS cloud and sends a login message carrying a unique identification number and lifetime parameters.

[0111] 3. The IoT PaaS cloud platform detects device access, verifies the login message format, obtains the lifetime field and unique identification number, and determines that the target device platform login is activated after authentication is successful. The target device becomes online. The IoT PaaS cloud platform can then determine the life cycle of the target device based on the lifetime field, start a lifetime timer for the target device, and store session information.

[0112] 4. The target device reports a service registration message, which carries encryption parameters.

[0113] 5. When the IoT PaaS cloud platform detects that a target device has connected, it obtains the lifetime timer status of the terminal: if it is within the lifetime timer period, it obtains the service registration message reported by the target device to the IoT PaaS cloud platform as the first service message of the target device, saves the session information, and restarts the lifetime timer; if it has exceeded the lifetime timer period, the IoT PaaS cloud platform determines that the target device is offline, reads the historical session information of the terminal recorded by the cloud platform based on the unique identification number, refreshes the device status, obtains the service registration message as the first service message of the target device, and restarts the lifetime timer;

[0114] 6. The cloud platform reads the attributes, parameters, service fields, and the correspondence between services and attributes of the object model associated with the terminal, parses the first business message obtained by the cloud platform based on the above object model fields, obtains first business parsed data, and stores the parsed data in the message queue module of the IoT PaaS cloud platform;

[0115] 7. The parsed data in the consumer message queue module is read from the cloud platform rule library, and the rule ID, rule SQL statement, and linkage instruction rule corresponding to the device are read. The rule SQL statement is used to enhance the parsed data to obtain the first target data. Based on the linkage instruction rule, the cloud platform automatically triggers the linkage action, that is, automatically calls the instruction issuing module to generate an instruction issuing task carrying the first target data, and assigns the task to the corresponding device as a confirmation notification of successful service registration;

[0116] 8. After receiving the service registration confirmation notification message from the cloud platform, the device sends the encrypted actual service message;

[0117] 9. The IoT PaaS cloud platform waits for and obtains the actual business message of the target device as the second business message of the target device, saves the session information, and resets the lifetime timer;

[0118] 10. Parse the device business data according to the object model fields that have been read to obtain second business parsing data, and store the second business parsing data in the message queue module of the IoT PaaS cloud platform;

[0119] 11. The second business parsing data in the consumption message queue module is read from the cloud platform rule library, which corresponds to the rule ID, rule SQL statement, message flow rule, and linkage rule associated with the device. The rule SQL statement is used to process the business parsing data to obtain the second target data, and the second target data is stored in the message queue module. Based on the message flow rule, linkage instruction rule, and the second target data, the cloud platform asynchronously triggers and completes message forwarding and instruction issuance, namely:

[0120] 1) The second target data in the consumption message queue module is pushed to the SaaS application subscription address according to the message flow rule, and the process proceeds to step 13;

[0121] 2) Call the instruction issuing module interface to generate an instruction issuing task carrying the second target data, assign the task to the corresponding device to make a successful confirmation notification of the actual business message or control of business instructions such as switching valves, and then enter step 12, and push the instruction issuing status to the subscription address associated with the terminal and then enter step 13.

[0122] 12. After receiving the command, the device returns a command response. The IoT PaaS cloud platform updates the command status to Completed. The device goes into hibernation, waiting for the next reporting cycle, and then re-enters step 4.

[0123] 13. After receiving data pushed from the IoT PaaS cloud platform, the SaaS application must respond to the cloud platform within 5 seconds, confirming receipt of the information. If the SaaS application does not respond to the cloud platform within 5 seconds, the IoT PaaS cloud platform will implement multiple pushes within the device's lifetime, such as 15 minutes, 1 hour, 4 hours, and 12 hours, until the SaaS application responds. If the SaaS application does not respond within 12 hours, the IoT PaaS cloud platform will record a push failure.

[0124] The above describes the method steps of the embodiment of the present invention. It is understandable that in the traditional gas equipment data collection mode, the equipment needs to frequently report to keep the equipment alive and respond to information confirmation, and needs to frequently interact with the SaaS application in the uplink and downlink to complete the synchronization of bilateral information. Starting from the service registration message, it takes at least 10 interactions to complete a collection. If the application responds slowly or the network fluctuation triggers the device retransmission mechanism, the number of interactions may increase to more than 16 times. In the scenario of large-scale gas data collection, the data concurrency is large, and the high frequency interaction in this mode doubles the data concurrency. Compared with the traditional gas equipment data collection mode, the embodiment of the present invention realizes automatic response through the rule library of the Internet of Things PaaS cloud platform and the uplink and downlink interaction with the device side. There is no need for corresponding analysis and operation on the application side, reducing the high concurrency push of data and the high TPS problem of API interface calls, and completing a collection can be reduced to 5 interactions. In addition, in the embodiment of the present invention, the simple business logic of terminal data collection and valve switching only needs to interact with the Internet of Things PaaS cloud platform, without the need for redundant interaction steps such as pushing SaaS applications, SaaS application calculations, calling cloud interfaces to return messages, etc., which greatly reduces the terminal uplink and downlink delays, improves the success rate of large-scale NB-IoT device data collection, and reduces the performance requirements of the application server.

[0125] It should be recognized that the embodiment of the present invention realizes the uplink and downlink interaction between the Internet of Things PaaS cloud platform and the target NB-IoT gas equipment based on cloud-edge collaboration, realizes automatic response of data collection and reception, does not require analysis and operation on the application side, avoids high-concurrency data push and high-frequency API interface calls, and improves the collection success rate and collection efficiency of NB-IoT gas equipment data.

[0126] FIG9 is a schematic diagram of the structure of an NB-IoT gas equipment data acquisition and optimization system provided by an embodiment of the present invention. Referring to FIG9 , an embodiment of the present invention provides an NB-IoT gas equipment data acquisition and optimization system, including:

[0127] A service registration message parsing module is used to obtain a service registration message of a target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the service registration message to obtain first service parsing data;

[0128] A registration success notification return module is used to decrypt and enhance the first service parsed data to obtain the first target data, and return a registration success notification to the target NB-IoT gas device based on the first target data and the corresponding device linkage rule;

[0129] The actual business message parsing module is used to obtain the actual business message of the target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the actual business message to obtain the second business parsing data;

[0130] The target data push module is used to decrypt and enhance the second business parsed data to obtain the second target data, and return a successful reception notification to the target NB-IoT gas device based on the second target data and the corresponding device linkage rules, and then forward the second target data to the Internet of Things SaaS application platform.

[0131] The contents of the above method embodiments are all applicable to the present system embodiments. The functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0132] An embodiment of the present invention further provides an electronic device comprising: a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory. When the program is executed by the processor, the aforementioned NB-IoT gas device data collection optimization method is implemented. The electronic device can be any smart terminal, including a tablet computer and an in-vehicle computer.

[0133] FIG10 is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. Referring to FIG10 , an embodiment of the present invention provides an electronic device, including:

[0134] The processor 1001 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided by the embodiments of the present invention.

[0135] The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called by the processor 1001 to execute the NB-IoT gas equipment data collection optimization method of the embodiment of the present invention;

[0136] Input / output interface 1003, used to implement information input and output;

[0137] Communication interface 1004, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0138] Bus 1005 , which transmits information between various components of the device (e.g., processor 1001 , memory 1002 , input / output interface 1003 , and communication interface 1004 );

[0139] The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

[0140] An embodiment of the present invention also provides a storage medium, which is a computer-readable storage medium used for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the above-mentioned NB-IoT gas equipment data collection optimization method.

[0141] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0142] Embodiments of the present invention further disclose a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the method shown in FIG1 .

[0143] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the above-mentioned boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0144] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the above-mentioned functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the routine skills of an engineer. Therefore, a person skilled in the art can implement the present invention set forth in the claims using ordinary skills without undue experimentation. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0145] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the above methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0146] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0147] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable media on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0148] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0149] In the above description of this specification, reference to the terms "one embodiment / example," "another embodiment / example," or "certain embodiments / examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0150] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0151] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A NB-IoT gas equipment data collection optimization method, characterized in that: The following steps are involved: Obtaining a service registration message of a target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parsing the service registration message to obtain first service parsing data; Decrypting and enhancing the first service parsed data to obtain first target data, and returning a registration success notification to the target NB-IoT gas device according to the first target data and the corresponding device linkage rule; Acquire the actual business message of the target NB-IoT gas device through the Internet of Things PaaS cloud platform, and parse the actual business message to obtain second business parsing data; The second business parsed data is decrypted and enhanced to obtain the second target data, and a successful reception notification is returned to the target NB-IoT gas device according to the second target data and the corresponding device linkage rule, and then the second target data is forwarded to the Internet of Things SaaS application platform.

2. According to claim 1, a NB-IoT gas equipment data collection optimization method is characterized in that: The NB-IoT gas equipment data collection optimization method further includes a step of activating and logging in to the target NB-IoT gas equipment, which specifically includes: Establishing a physical model on the Internet of Things PaaS cloud platform and configuring a rule base, wherein the rule base includes data decryption processing rules and device linkage rules; Sending a device login message to the Internet of Things PaaS cloud platform through the target NB-IoT gas device, wherein the device login message includes a registration lifetime field and a device unique identification number; The target NB-IoT gas device is activated and logged in for authentication through the IoT PaaS cloud platform according to the registration lifetime field and the device unique identification number. When the authentication is successful, the registration lifetime timer is set and started according to the registration lifetime field, the session information of the target NB-IoT gas device is saved, and then an activation login success notification is returned to the target NB-IoT gas device.

3. According to claim 2, a NB-IoT gas equipment data collection optimization method is characterized in that: The step of obtaining the service registration message of the target NB-IoT gas device through the IoT PaaS cloud platform specifically includes: When the Internet of Things PaaS cloud platform detects that the target NB-IoT gas device is connected, the online status of the target NB-IoT gas device is determined according to the registration lifetime timer; When it is determined that the target NB-IoT gas device is online, the registration lifetime timer is reset, and the service registration message sent by the target NB-IoT gas device is received through the Internet of Things PaaS cloud platform; When it is determined that the target NB-IoT gas device is offline, the historical session information of the target NB-IoT gas device is obtained according to the unique identification number of the device, and whether the target NB-IoT gas device is activated is determined according to the historical session information. Active login, if yes, reset the registration lifetime timer, and receive the service registration message sent by the target NB-IoT gas device through the Internet of Things PaaS cloud platform.

4. According to claim 2, a NB-IoT gas equipment data collection optimization method is characterized in that: The step of parsing the service registration message to obtain first service parsing data specifically includes: Querying the attribute field, parameter field and service field of the object model, and determining the corresponding relationship between the attribute field and the service field; Parsing the service registration message according to the attribute field, the parameter field, the service field and the corresponding relationship to obtain the first service parsing data; The first business parsing data is stored in the message queue module of the Internet of Things PaaS cloud platform.

5. According to claim 4, a NB-IoT gas equipment data collection optimization method is characterized in that: The step of decrypting and enhancing the first service parsed data to obtain the first target data, and returning a registration success notification to the target NB-IoT gas device according to the first target data and the corresponding device linkage rule specifically includes: Obtain the data decryption processing rule and the device linkage rule corresponding to the target NB-IoT gas device in the rule base; Decrypt and enhance the first business parsing data in the message queue module according to the data decryption processing rule to obtain the first target data; The registration success notification is generated according to the first target data and the device linkage rule, and the registration success notification is sent to the target NB-IoT gas device through an instruction sending module.

6. A NB-IoT gas equipment data collection optimization method according to claim 5, characterized in that: The step of returning a successful reception notification to the target NB-IoT gas device according to the second target data and the corresponding device linkage rule, and then forwarding the second target data to the Internet of Things SaaS application platform specifically includes: Generate the successful reception notification and the service control instruction according to the second target data and the device linkage rule, and send the successful reception notification and the service control instruction to the target NB-IoT gas device through the instruction sending module; The SaaS application subscription address is determined according to the device linkage rule, and the second target data is forwarded to the Internet of Things SaaS application platform according to the SaaS application subscription address.

7. A NB-IoT gas equipment data collection optimization method according to any one of claims 1 to 6, characterized in that: The NB-IoT gas equipment data collection optimization method further includes the following steps: When the Internet of Things PaaS cloud platform does not receive the Internet of Things SaaS application platform within a preset first time threshold The returned data reception response re-forwards the second target data to the IoT SaaS application platform through the IoT PaaS cloud platform according to a preset re-push rule until the IoT PaaS cloud platform receives the data reception response returned by the IoT SaaS application platform; When the Internet of Things PaaS cloud platform does not receive a data reception response returned by the Internet of Things SaaS application platform within a preset second time threshold, a data push failure record is generated and stored through the Internet of Things PaaS cloud platform.

8. A NB-IoT gas equipment data collection and optimization system, characterized in that: include: A service registration message parsing module, used to obtain a service registration message of a target NB-IoT gas device through an Internet of Things PaaS cloud platform, and parse the service registration message to obtain first service parsing data; A registration success notification return module, used to decrypt and enhance the first service parsing data to obtain first target data, and return a registration success notification to the target NB-IoT gas device according to the first target data and the corresponding device linkage rule; An actual business message parsing module, used to obtain the actual business message of the target NB-IoT gas equipment through the Internet of Things PaaS cloud platform, and parse the actual business message to obtain second business parsing data; The target data push module is used to decrypt and enhance the second business analysis data to obtain the second target data, and return a successful reception notification to the target NB-IoT gas device according to the second target data and the corresponding device linkage rules, and then forward the second target data to the Internet of Things SaaS application platform.

9. An electronic device, characterized in that: The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, the steps of the NB-IoT gas equipment data collection optimization method as described in any one of claims 1 to 7 are realized.

10. A storage medium, the storage medium being a computer-readable storage medium, used for computer-readable storage, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the NB-IoT gas equipment data collection optimization method as described in any one of claims 1 to 7.

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