Measurement data acquisition method and device, equipment and storage medium

Abstract

The invention relates to the technical field of Internet of Things, and discloses a method, a device and equipment for obtaining measurement data and a storage medium, and the method comprises the steps: obtaining the measurement data collected by measurement instrument equipment under the condition that target indication information is received; according to a network connection condition, the measurement data is stored in a local cache, or the measurement data is uploaded to a back-end server, or the measurement data is backed up to a cloud end at regular time; acquiring an uploading state and ID identification information of the measurement data; and under the condition that the measurement data is modified, acquiring first measurement data according to the uploading state and the ID identification information, and updating the measurement data by using the first measurement data. According to the data synchronization method and device, the obtained measurement data are stored in the local cache or uploaded to the back-end server, or the measurement data are backed up to the cloud end at regular time, the data storage forms are diversified, meanwhile, the updated measurement data can be obtained at the first time according to the uploading state and the ID identification information of the measurement data, and data synchronization is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of Internet of Things (IoT) technology, specifically to methods, apparatus, devices, and storage media for acquiring measurement data. Background Technology

[0002] With the continuous development of technology, the application scenarios of measuring equipment have expanded significantly, and the amount of measurement data generated has also increased. Therefore, it is necessary to adopt corresponding methods to obtain the measurement data of measuring equipment.

[0003] To address the aforementioned issues, relevant technologies typically employ manual methods to acquire measurement data. However, traditional manual methods have many drawbacks and limitations: manual methods can only store data on paper, which is prone to loss or damage, affecting the integrity and accuracy of the data; manual methods cannot synchronize data in real time, and data cannot be uploaded or accessed remotely in real time, making timely diagnosis or decision-making impossible.

[0004] Therefore, traditional manual methods for acquiring measurement data suffer from problems such as limited data storage and inability to achieve data synchronization. Summary of the Invention

[0005] In view of this, the present disclosure provides a method, apparatus, device, and storage medium for acquiring measurement data, in order to solve the problems of traditional manual methods in the related art having a single data storage method and being unable to achieve data synchronization when acquiring measurement data.

[0006] In a first aspect, this disclosure provides a method for acquiring measurement data, the method comprising: Upon receiving the target indication information, the measurement data collected by the measuring instrument is acquired, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected; Depending on network connectivity, the measurement data can be stored in a local cache, uploaded to a backend server, or backed up to the cloud periodically. Obtain the upload status and ID identification information of the measurement data; If the measurement data has been modified, the first measurement data is obtained based on the upload status and ID identification information, and the measurement data is updated with the first measurement data, wherein the first measurement data is the latest modified measurement data to be synchronized.

[0007] In this embodiment, upon receiving target indication information, measurement data collected by the measuring instrument is acquired, where the target indication information indicates that the measuring instrument has been automatically connected. Measurement data is stored in a local cache based on network connection conditions, or stored in a local cache and periodically backed up to the cloud. The upload status and ID of the measurement data are acquired. After determining that the measurement data has been modified, the first measurement data corresponding to the current modification can be obtained based on the upload status and ID of the measurement data. Finally, the first measurement data is synchronized. Because this embodiment stores the acquired measurement data in a local cache, uploads the measurement data to a backend server, or periodically backs up the measurement data to the cloud, the data storage format is diverse. Simultaneously, updated measurement data can be obtained immediately based on the upload status and ID of the measurement data, achieving data synchronization.

[0008] In one optional implementation, after acquiring the measurement data collected by the measuring instrument, the method further includes: The measurement data is parsed and converted to obtain second measurement data in the target format, where the target format is used to characterize the readability of the second measurement data.

[0009] In this embodiment, by parsing and format-converting the measurement data, second measurement data in the target format is obtained, thereby converting the measurement data into readable second measurement data and enabling data storage in various formats. Automated acquisition, processing, and storage of measurement data improves data acquisition efficiency and ensures data accuracy and consistency.

[0010] In an alternative implementation, before receiving the target indication information, the method further includes: According to the preset connection mechanism, it periodically sends connection request information to the measuring instrument.

[0011] In this embodiment of the disclosure, by periodically sending connection request information to the measuring instrument according to a preset connection mechanism, the stability of the connection can be ensured and the connection can be prevented from being interrupted unexpectedly.

[0012] In one optional implementation, the measurement data is stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud, depending on network connectivity conditions. In the event of a network connection failure, the measurement data will be stored in a local cache. Under normal network conditions, the measurement data is uploaded to the backend server according to the upload operation performed by the user, or the measurement data is backed up to the cloud in real time and on a regular schedule, provided that the network connection is normal.

[0013] In this embodiment, by storing measurement data locally in the event of network connectivity issues, data loss or corruption caused by network connectivity problems can be prevented. When the network connection is normal, uploading the measurement data to a backend server or periodically backing it up to the cloud enables data synchronization and sharing, ensuring data real-time performance. Through multiple storage mechanisms, data integrity and accuracy can be ensured.

[0014] In one optional implementation, the measurement data is stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud, depending on network connectivity conditions. In the event of a network connection failure, the measurement data is compressed and stored in a local cache; alternatively, keyword information is extracted from the measurement data and stored in a local cache. Under normal network conditions, the measurement data is compressed according to the upload operation performed by the user, and the compressed measurement data is uploaded to the backend server; or, keyword information is extracted from the measurement data and uploaded to the backend server. Under normal network conditions, compress the measurement data and back it up to the cloud periodically; or, extract keyword information from the measurement data and back it up to the cloud periodically.

[0015] In this embodiment of the disclosure, the problem of insufficient local storage space can be solved by compressing measurement data or storing only keyword information.

[0016] In one alternative implementation, the method further includes: Compare the measurement data stored in the local cache with the measurement data backed up in the cloud; If the measurement data stored in the local cache is inconsistent with the measurement data backed up in the cloud, the measurement data stored in the local cache will be supplemented and improved based on the measurement data backed up in the cloud.

[0017] In this embodiment of the disclosure, by comparing the measurement data stored in the local cache with the measurement data backed up in the cloud, and improving the measurement data stored in the local cache according to the comparison results, the data integrity of the measurement data when stored locally is ensured.

[0018] In one alternative implementation, the method further includes: Obtain historical measurement data for a preset time period; Transform historical measurement data into a preset display format and perform visual analysis on the historical measurement data.

[0019] In this embodiment of the disclosure, by converting historical measurement data into a preset display format and performing visual analysis on the historical measurement data, the problem of inconvenient data management can be solved, and the data can be utilized more effectively.

[0020] Secondly, this disclosure provides an apparatus for acquiring measurement data, the apparatus comprising: The first acquisition module is used to acquire measurement data collected by the measuring instrument when receiving target indication information, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected. The first storage module is used to store measurement data in a local cache, upload measurement data to a backend server, or back up measurement data to the cloud periodically, depending on network connection conditions. The second acquisition module is used to acquire the upload status and ID identification information of the measurement data; The update module is used to obtain the first measurement data based on the upload status and ID identification information when there is a modification to the measurement data, and update the measurement data with the first measurement data, wherein the first measurement data is the latest modified measurement data to be synchronized.

[0021] Thirdly, this disclosure provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the method for acquiring measurement data described in the first aspect or any corresponding embodiment.

[0022] Fourthly, this disclosure provides a computer-readable storage medium storing computer instructions for causing a computer to perform the method for acquiring measurement data described in the first aspect or any corresponding embodiment.

[0023] Fifthly, this disclosure provides a computer program product, including computer instructions for causing a computer to execute the method for acquiring measurement data described in the first aspect or any corresponding embodiment. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the specific embodiments of this disclosure or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating a method for acquiring measurement data according to an embodiment of the present disclosure; Figure 2 This is a structural block diagram of an apparatus for acquiring measurement data according to an embodiment of the present disclosure; Figure 3 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present disclosure. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0027] With the continuous development of technology, the application scenarios of measuring equipment have expanded significantly, and the amount of measurement data generated has also increased. Therefore, it is necessary to adopt corresponding methods to obtain the measurement data of measuring equipment.

[0028] To address the aforementioned issues, relevant technologies typically employ manual methods to acquire measurement data. However, traditional manual methods have numerous drawbacks and limitations: manual data measurement is time-consuming, especially when processing large volumes of data, resulting in low efficiency; manual input or recording of data is prone to errors and omissions, leading to inaccurate data; manual methods can only store data on paper, which is easily lost or damaged, affecting data integrity and accuracy; manually recorded paper data is difficult to archive, query, and analyze, and cannot generate historical records, trend analyses, etc., resulting in insufficient ability to effectively utilize data; manual methods cannot synchronize data in real time, and data cannot be uploaded or accessed remotely in real time, hindering timely diagnosis or decision-making; manual methods cannot automatically collect, process, and store data, impeding the realization of automated data analysis functions.

[0029] Therefore, traditional manual methods for acquiring measurement data suffer from problems such as low efficiency, poor data accuracy, limited data storage methods, inconvenient data management, inability to achieve data synchronization, and inability to automate the process.

[0030] To address the aforementioned problems, according to an embodiment of this disclosure, a method for acquiring measurement data is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This embodiment provides a method for acquiring measurement data, such as Figure 1 As shown, Figure 1This is a flowchart illustrating a method for acquiring measurement data according to an embodiment of the present disclosure. This process can be applied to a mobile app and includes the following steps: Step S101: Upon receiving the target indication information, acquire the measurement data collected by the measuring instrument, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected.

[0032] Optionally, in this embodiment of the disclosure, the APP can communicate with the measuring instrument via Bluetooth. The measurement data may include length, angle, area, etc.

[0033] Specifically, the APP first initializes the Bluetooth module and starts the Bluetooth function. Then, it scans Bluetooth devices to find the measuring instrument, automatically establishes a connection with the measuring instrument, obtains target indication information, and then acquires the measurement data collected by the measuring instrument.

[0034] Furthermore, in the mobile application (based on React Native), device connectivity is managed uniformly through the encapsulated BluetoothManager (which internally integrates a BleManager instance of react-native-ble-plx). The application first calls requestPermissions() for permission management, checkBluetoothState() for Bluetooth status checking, and checkLocationService() for location service verification to request Bluetooth / location permissions and verify the system status. If any step fails, a prompt is immediately given and subsequent operations are blocked.

[0035] After successful permission and environment verification, `startScan()` is called to initiate a BLE scan. This uses a pre-maintained device whitelist to filter out measuring devices and updates `deviceInfo` (device information) in real time to mark them as "searching / discovered". When a supported measuring device is detected, `createBLEConnection()` is automatically called to establish a GATT connection: first, pairing is completed via `manager.connectToDevice()`, then `discoverAllServicesAndCharacteristics()` is executed. Subsequently, based on the pre-defined service UUID (Universally Unique Identifier) ​​in the whitelist, `monitorCharacteristicForService()` is called to subscribe to notifications, and `readRSSIForDevice()` is used periodically to collect signal strength.

[0036] When the measuring instrument reports measurement data, the corresponding parsing algorithm is selected based on the model: for example, measuring instrument A first performs Base64 decoding on the feature value, filters control characters and removes unit symbols, and then formats it as a floating-point number; measuring instrument B restores the feature value to a DataView and parses it as little-endian floating-point, then performs multi-level rounding, and finally packages it into a {value, unit, type} structure. The parsing result is written to a JavaScript state management library in real time, such as to MobX, so that the measurement value can be observed, and the user interface can inject the value into the currently selected parameter input box to achieve automatic filling of the measurement result.

[0037] The UI layer displays the connection status, scan button, and disconnection logic through BluetoothScreen (i.e., the screen or page component of the UI layer), and triggers the above process in KeyboardAwareModal (i.e., the intelligent modal dialog box); at the same time, it combines TemplateStore (i.e., the template state repository) to centrally manage the measurement template parameters, default values, extensions, and image collection, so that Bluetooth measurement and data form entry form a closed loop.

[0038] Step S102: Depending on the network connection conditions, the measurement data is stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud.

[0039] Optionally, in this embodiment, the measurement data is first stored in a locally cached database, and can subsequently be uploaded to a backend server based on network conditions and user manual upload methods. Simultaneously, the measurement data can also be periodically backed up and uploaded to the cloud based on network conditions.

[0040] In addition, the app employs asynchronous processing and batch upload mechanisms when storing data. Asynchronous processing means that while the server is executing one task, it can continue executing other tasks without waiting for that task to complete. Batch upload is a data transmission strategy that involves uploading data in multiple batches instead of transmitting it all at once.

[0041] Step S103: Obtain the upload status and ID identification information of the measurement data.

[0042] Optionally, the measurement data currently exists in three states on the APP: not uploaded, uploaded, and modified but not uploaded. The APP also has a local cache database, and each piece of measurement data has a unique UUID, i.e., a unique ID identifier. In step S104, if the measurement data has been modified, the first measurement data is obtained based on the upload status and ID identifier, and the measurement data is updated with the first measurement data, which is the latest modified measurement data to be synchronized.

[0043] Optionally, when measurement data is modified or data changes occur, the upload status and ID identification information of the measurement data are obtained. If the upload status of the modified measurement data is not uploaded or the modified data is not uploaded, the newly written first measurement data can be directly overwritten based on the ID identification information.

[0044] If the data has already been uploaded, its upload status needs to be changed to "modified but not uploaded," indicating that the measurement data has undergone abnormal changes and needs to be updated and uploaded again. Finally, all measurement data that is neither uploaded nor modified but not uploaded is transmitted to the backend server or backed up to the cloud.

[0045] In this embodiment, upon receiving target indication information, measurement data collected by the measuring instrument is acquired, where the target indication information indicates that the measuring instrument has been automatically connected. Measurement data is stored in a local cache based on network connection conditions, or stored in a local cache and periodically backed up to the cloud. The upload status and ID of the measurement data are acquired. After determining that the measurement data has been modified, the first measurement data corresponding to the current modification can be obtained based on the upload status and ID of the measurement data. Finally, the first measurement data is synchronized. Because this embodiment stores the acquired measurement data in a local cache, uploads the measurement data to a backend server, or periodically backs up the measurement data to the cloud, the data storage format is diverse. Simultaneously, updated measurement data can be obtained immediately based on the upload status and ID of the measurement data, achieving data synchronization.

[0046] In some optional implementations, after acquiring the measurement data collected by the measuring instrument, the method further includes: The measurement data is parsed and converted to obtain second measurement data in the target format, where the target format is used to characterize the readability of the second measurement data.

[0047] Optionally, in this embodiment of the disclosure, after the APP obtains the measurement data collected by the measuring instrument, it extracts valid measurement information from the measurement data according to the data parsing algorithm and converts it into readable second measurement data.

[0048] In this embodiment of the disclosure, by parsing and format conversion of the measurement data, second measurement data in the target format is obtained, thereby converting the measurement data into readable second measurement data, which can improve data acquisition efficiency and ensure the accuracy and consistency of the data.

[0049] In some alternative implementations, the method further includes, prior to receiving the target indication information: According to the preset connection mechanism, it periodically sends connection request information to the measuring instrument.

[0050] Optionally, in this embodiment of the disclosure, the preset connection mechanism includes a continuous monitoring mechanism and an automatic reconnection mechanism. The continuous monitoring mechanism can continuously monitor the connection status between the APP and the measuring instrument by setting heartbeat packets or periodically sending preset data (such as fields like "stay active"). A heartbeat packet refers to a custom command word that periodically notifies the APP and the measuring instrument of its status, sent at regular intervals, similar to a heartbeat, hence the name. The heartbeat packet is used to determine whether the APP and the measuring instrument are operating normally, using a simple communication packet sent periodically. If no response is received within a specified time period, the connection is considered interrupted. The automatic reconnection mechanism refers to automatically triggering a reconnection when the Bluetooth connection is interrupted.

[0051] Specifically, before receiving the target indication information, the APP periodically sends connection request information to the measuring instrument according to the preset connection mechanism.

[0052] In this embodiment of the disclosure, by periodically sending connection request information to the measuring instrument according to a preset connection mechanism, the stability of the connection can be ensured and the connection can be prevented from being interrupted unexpectedly.

[0053] In some optional implementations, the measurement data may be stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud, depending on network connectivity conditions. These options include: In the event of a network connection failure, the measurement data will be stored in a local cache. Under normal network conditions, the measurement data is uploaded to the backend server according to the upload operation performed by the user, or the measurement data is backed up to the cloud in real time and on a regular schedule, provided that the network connection is normal.

[0054] Optionally, in this embodiment of the disclosure, network connection conditions include both abnormal network connection and normal network connection.

[0055] Specifically, measurement data is stored in different locations depending on network connectivity. In the event of a network connection failure, the measurement data is simply stored in a local cache. If the network connection is normal, in addition to storing the measurement data locally, it can also be uploaded to the backend server based on user-manual upload operations. Furthermore, the measurement data can be backed up to the cloud in real-time via cloud functions on a scheduled basis.

[0056] It's important to note that uploading measurement data to the backend server depends on user-initiated upload actions. For example, the app only uploads the data to the backend server when it receives a user click on the measurement data. If the app doesn't receive any user input, there's no need to upload the measurement data to the backend server.

[0057] When backing up measurement data to the cloud, a mandatory binding of a "user identifier" (such as user ID or device serial number to ensure unique user ownership) and a "timestamp" (such as the precise time the data was generated, in the format YYYY-MM-DD HH:MM:SS.XXX, accurate to the millisecond level, to avoid data conflicts from the same user at the same time) is implemented. The timestamp here refers to the time identifier used to mark the measurement data when it is stored in the cloud database.

[0058] In this embodiment, by storing measurement data in a local cache when network connectivity is abnormal, data loss or corruption caused by network connectivity issues can be prevented. When network connectivity is normal, uploading measurement data to a backend server or cloud database enables data synchronization and sharing, ensuring data real-time performance. This combined storage mechanism of local caching, backend servers, and cloud databases ensures data integrity and accuracy.

[0059] In some optional implementations, the measurement data may be stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud, depending on network connectivity conditions. These options include: In the event of a network connection failure, the measurement data is compressed and stored in a local cache; alternatively, keyword information is extracted from the measurement data and stored in a local cache. Under normal network conditions, the measurement data is compressed according to the upload operation performed by the user, and the compressed measurement data is uploaded to the backend server; or, keyword information is extracted from the measurement data and uploaded to the backend server. Under normal network conditions, compress the measurement data and back it up to the cloud periodically; or, extract keyword information from the measurement data and back it up to the cloud periodically.

[0060] Optionally, in this embodiment of the disclosure, regardless of whether the measurement data is stored in a local cache, uploaded to a backend server, or backed up to the cloud, compression techniques can be used to compress the measurement data. For example, Huffman coding can be used: an optimal coding tree is constructed according to the frequency of data occurrence, with short codes for high-frequency data and long codes for low-frequency data, resulting in compressed measurement data. Another example is arithmetic coding, which maps the entire data sequence to a single floating-point number, offering higher coding efficiency than Huffman coding and is suitable for batch compression of continuous measurement data.

[0061] Furthermore, regardless of whether the measurement data is stored in a local cache, uploaded to a backend server, or backed up to the cloud, keyword extraction techniques can be used to process the measurement data. By extracting keyword information from the measurement data, such as measurement type, measurement unit, and measurement dimension, only this keyword information is uploaded to the local cache, backend server, or cloud.

[0062] In this embodiment of the disclosure, the problem of insufficient local storage space can be solved by compressing measurement data or storing only keyword information.

[0063] In some alternative implementations, the method further includes: Compare the measurement data stored in the local cache with the measurement data backed up in the cloud; If the measurement data stored in the local cache is inconsistent with the measurement data backed up in the cloud, the measurement data stored in the local cache will be supplemented and improved based on the measurement data backed up in the cloud.

[0064] Optionally, in this embodiment, measurement data in the local cache is used first, and if the measurement data is lost, the measurement data is obtained from the cloud.

[0065] The acquisition method is as follows: using the user's account ID as the comparison object, all measurement data corresponding to the timestamps under that account are retrieved. Then, the measurement data stored in the local cache for each timestamp is compared with the measurement data backed up in the cloud. If the measurement data is inconsistent, the measurement data backed up in the cloud takes precedence, and the local cache is supplemented and improved.

[0066] The above method is applicable to scenarios where local data is lost / errored due to equipment failure or storage damage, or where some measurement data is accidentally deleted by local devices, resulting in incomplete synchronization of data in the local cache.

[0067] In this embodiment of the disclosure, measurement data stored in the local cache is supplemented and improved by measurement data backed up in the cloud, ensuring that the measurement data in the local cache is reliable and usable, and avoiding the impact of local data problems on subsequent analysis and application.

[0068] In some alternative implementations, the method further includes: Obtain historical measurement data for a preset time period; Transform historical measurement data into a preset display format and perform visual analysis on the historical measurement data.

[0069] Optionally, in this embodiment of the disclosure, the preset display format includes chart format, statistical lookup format, etc.

[0070] Specifically, a historical data module is created in the APP. Through functions such as pagination loading and data filtering, historical measurement data within a preset time period is obtained. Then, the historical measurement data is converted into preset display formats such as charts for visual analysis.

[0071] In addition, after performing visual analysis on historical measurement data, the app can also return the analysis results through the application programming interface and render them on the app's front-end interface, displaying the measurement data and analysis results in real time according to the data refresh mechanism.

[0072] In this embodiment of the disclosure, by converting historical measurement data into a preset display format and performing visual analysis on the historical measurement data, the problem of inconvenient data management can be solved, and the data can be utilized more effectively.

[0073] This embodiment also provides a device for acquiring measurement data, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0074] This embodiment provides a device for acquiring measurement data, such as... Figure 2 As shown, it includes: The first acquisition module 201 is used to acquire measurement data collected by the measuring instrument when receiving target indication information, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected. The first storage module 202 is used to store measurement data in a local cache according to network connection conditions, or upload measurement data to a backend server, or back up measurement data to the cloud periodically. The second acquisition module 203 is used to acquire the upload status and ID identification information of the measurement data; The update module 204 is used to obtain the first measurement data based on the upload status and ID identification information when there is a modification to the measurement data, and update the measurement data with the first measurement data, wherein the first measurement data is the latest modified measurement data to be synchronized.

[0075] In this embodiment, upon receiving target indication information, measurement data collected by the measuring instrument is acquired, where the target indication information indicates that the measuring instrument has been automatically connected. Measurement data is stored in a local cache based on network connection conditions, or stored in a local cache and periodically backed up to the cloud. The upload status and ID of the measurement data are acquired. After determining that the measurement data has been modified, the first measurement data corresponding to the current modification can be obtained based on the upload status and ID of the measurement data. Finally, the first measurement data is synchronized. Because this embodiment stores the acquired measurement data in a local cache, uploads the measurement data to a backend server, or periodically backs up the measurement data to the cloud, the data storage format is diverse. Simultaneously, updated measurement data can be obtained immediately based on the upload status and ID of the measurement data, achieving data synchronization.

[0076] In some alternative embodiments, the device further includes: The module is used to parse and convert the measurement data collected by the measuring instrument after obtaining the measurement data to obtain the second measurement data in the target format. The target format is used to characterize the readability of the second measurement data.

[0077] In some alternative embodiments, the device further includes: The sending module is used to periodically send connection request information to the measuring instrument according to a preset connection mechanism before receiving target indication information.

[0078] In some alternative implementations, the first storage module 202 includes: The first storage unit is used to store measurement data in a local cache in the event of a network connection failure; The first upload unit is used to upload measurement data to the backend server according to the upload operation performed by the user when the network connection is normal, or to back up the measurement data to the cloud in real time and on a regular basis when the network connection is normal.

[0079] In some alternative implementations, the first storage module 202 includes: The second storage unit is used to compress the measurement data and store the compressed measurement data in the local cache in the event of a network connection failure; or to extract keyword information from the measurement data and store the keyword information in the local cache. The second upload unit is used to compress the measurement data according to the upload operation performed by the user when the network connection is normal, and upload the compressed measurement data to the backend server; or, extract keyword information from the measurement data and upload the keyword information to the backend server. The backup unit is used to compress measurement data and back up the compressed measurement data to the cloud periodically when the network connection is normal; or, to extract keyword information from the measurement data and back up the keyword information to the cloud periodically.

[0080] In some alternative embodiments, the device further includes: The comparison unit is used to compare the measurement data stored in the local cache with the measurement data backed up in the cloud; The supplementary unit is used to supplement and improve the measurement data stored in the local cache based on the measurement data backed up in the cloud when the measurement data stored in the local cache is inconsistent with the measurement data backed up in the cloud.

[0081] In some alternative embodiments, the device further includes: The third acquisition module is used to acquire historical measurement data within a preset time period; The analysis module is used to convert historical measurement data into a preset display format and perform visual analysis on the historical measurement data.

[0082] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0083] In this embodiment, the device for acquiring measurement data is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0084] This disclosure also provides a computer device having the above-described features. Figure 2 The device shown is for acquiring measurement data.

[0085] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of this disclosure, such as... Figure 3As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 3 Take a processor 10 as an example.

[0086] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0087] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0088] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0089] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0090] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0091] This disclosure also provides a computer-readable storage medium in which the methods described in this disclosure can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium after being downloaded over a network. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium may be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium may also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0092] A portion of this disclosure can be applied to computer program products, such as computer program instructions, which, when executed by a computer, can invoke or provide methods and / or technical solutions according to this disclosure through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, and installation package files. Accordingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions; the computer compiling the instructions and then executing the corresponding compiled program; the computer reading and executing the instructions; or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0093] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for acquiring measurement data, characterized in that, The method includes: Upon receiving target indication information, the measurement data collected by the measuring instrument is acquired, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected; Depending on network connectivity, the measurement data may be stored in a local cache, uploaded to a backend server, or periodically backed up to the cloud. Obtain the upload status and ID identification information of the measurement data; if the measurement data has been modified, obtain the first measurement data according to the upload status and the ID identification information, and update the measurement data with the first measurement data, wherein the first measurement data is the latest modified measurement data to be synchronized.

2. The method according to claim 1, characterized in that, After acquiring the measurement data collected by the measuring instrument, the method further includes: The measurement data is parsed and converted to obtain second measurement data in a target format, wherein the target format is used to characterize the readability of the second measurement data.

3. The method according to claim 1, characterized in that, Prior to receiving the target indication information, the method further includes: According to a preset connection mechanism, it periodically sends connection request information to the measuring instrument.

4. The method according to claim 1, characterized in that, The step of storing the measurement data in a local cache according to network connection conditions, or uploading the measurement data to a backend server, or periodically backing up the measurement data to the cloud includes: In the event of a network connection failure, the measurement data will be stored in the local cache. Under normal network conditions, the measurement data is uploaded to the backend server according to the upload operation performed by the user, or the measurement data is backed up to the cloud in real time and periodically, under normal network conditions.

5. The method according to claim 4, characterized in that, The step of storing the measurement data in a local cache according to network connection conditions, or uploading the measurement data to a backend server, or periodically backing up the measurement data to the cloud includes: In the event of a network connection failure, the measurement data is compressed and the compressed measurement data is stored in the local cache; or, keyword information is extracted from the measurement data and the keyword information is stored in the local cache. Under normal network connectivity, the measurement data is compressed according to the upload operation performed by the user, and the compressed measurement data is uploaded to the backend server; or, keyword information is extracted from the measurement data and the keyword information is uploaded to the backend server. Under normal network connectivity, the measurement data is compressed, and the compressed measurement data is backed up to the cloud periodically; or, keyword information is extracted from the measurement data, and the keyword information is backed up to the cloud periodically.

6. The method according to claim 1, characterized in that, The method further includes: The measurement data stored in the local cache is compared with the measurement data backed up in the cloud; If the measurement data stored in the local cache is inconsistent with the measurement data backed up in the cloud, the measurement data stored in the local cache shall be supplemented and improved based on the measurement data backed up in the cloud.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Obtain historical measurement data for a preset time period; The historical measurement data is converted into a preset display format and then visualized and analyzed.

8. A device for acquiring measurement data, characterized in that, The device includes: The first acquisition module is used to acquire measurement data collected by the measuring instrument when receiving target indication information, wherein the target indication information is used to indicate that the measuring instrument has been automatically connected; The first storage module is used to store the measurement data in a local cache according to the network connection conditions, or upload the measurement data to the backend server, or back up the measurement data to the cloud periodically; The second acquisition module is used to acquire the upload status and ID identification information of the measurement data; The update module is used to obtain first measurement data based on the upload status and the ID identification information when there is a modification to the measurement data, and update the measurement data with the first measurement data, wherein the first measurement data is the latest modified measurement data to be synchronized.

9. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for acquiring measurement data as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of acquiring measurement data as described in any one of claims 1 to 7.

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