Data acquisition method and system

Abstract

The invention discloses a data acquisition method, system and device. The method comprises the following steps: defining acquisition configuration according to an object; acquiring and analyzing an acquisition instruction to obtain a data identifier; performing data acquisition based on the data identifier and the acquisition configuration; performing format conversion on the data of the object based on the informatization standard of the corresponding scene; and uploading the converted security component based on the corresponding security component. The system comprises a definition module, an instruction analysis module, an acquisition module, a conversion module and an uploading module. The device comprises a memory and a processor used for executing the data acquisition imaging method. By using the method and the device, human intervention in the data acquisition process is avoided, and the data security is improved. The method can be widely applied to the field of data arrangement.

Description

Technical Field

[0001] The present invention relates to the field of data collation, and in particular to a data collection method and system. Background Art

[0002] Existing sample data collection is mostly manual on-site operations and collection or manual operation and maintenance. The advantage of this solution is that it is convenient and easy to operate and manage in real time, but it is not applicable in some application scenarios. For example, the CDC sample library belongs to a high-risk area. Researchers and relevant staff enter and exit the sample library to complete sample data collection and operation and maintenance of sample library-related equipment, and actually bear certain infection risks.

[0003] Therefore, there is an urgent need for an automatic data collection method to avoid the risk of human infection. Summary of the invention

[0004] In view of this, in order to solve the technical problem that the existing data collection method cannot avoid human intervention and cannot meet all application scenarios, the present invention proposes a data collection method, which includes the following steps:

[0005] Define the collection configuration according to the object;

[0006] Obtain and analyze the collection instructions to obtain data identification;

[0007] Perform data collection based on the data identifier and the collection configuration to obtain data of the object;

[0008] Based on a preset information standard, the data of the object is formatted to obtain converted data;

[0009] The converted data is uploaded based on the security component.

[0010] The collection configuration includes an identification number ID, a signal strength indicator, an access port, a URL path and a storage structure.

[0011] In some embodiments, different steps are added to achieve corresponding functions, such as:

[0012] Build a cluster to monitor the collection process to obtain log data;

[0013] Message queues and transmission channels are coordinated based on the cluster.

[0014] Through this optimization step, queues and channels are allocated in an orderly manner for real-time monitoring, which is helpful for subsequent equipment operation and maintenance and abnormality tracing.

[0015] Additionally, you can:

[0016] Constructing state intervals based on preset thresholds;

[0017] The data of the object is analyzed according to the state interval to obtain an analysis result.

[0018] Through this preferred step, data can be used to make a quick judgment and quickly obtain the status of the object, which is helpful for equipment operation and maintenance.

[0019] The present invention also proposes a data acquisition system, the system comprising:

[0020] A definition module, used to define acquisition configuration according to objects;

[0021] The instruction analysis module is used to obtain and analyze the collection instructions to obtain data identification;

[0022] A collection module collects data based on the data identifier and the collection configuration to obtain data of the object;

[0023] A conversion module, based on a preset information standard, converts the format of the data of the object to obtain converted data;

[0024] The upload module uploads the converted data based on the security component.

[0025] The present invention also proposes a data acquisition device, comprising:

[0026] at least one processor;

[0027] at least one memory for storing at least one program;

[0028] When the at least one program is executed by the at least one processor, the at least one processor implements the data collection method as described above.

[0029] Based on the above scheme, the present invention provides a data collection method, system and device, which can realize automatic monitoring of the operating status of sample analysis equipment and ultra-low temperature sample storage equipment, and obtain and safely transmit sample analysis data in real time. This greatly reduces the occurrence of researchers entering high-risk areas of sample libraries and conducting sample analysis on site, reduces the risk of infection incidents in sample libraries, and improves the safety of relevant personnel in CDCs engaged in sample analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a flow chart of steps of a data collection method of the present invention;

[0031] Figure 2 It is a structural block diagram of a data acquisition system of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] It should be noted that, for the convenience of description, only the parts related to the relevant invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0034] It should be understood that the "system", "device", "unit" and / or "module" used in this application is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the word can be replaced by other expressions.

[0035] Unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements. The elements defined by the sentence "includes a..." do not exclude the existence of other identical elements in the process, method, commodity or device that includes the elements.

[0036] In the description of the embodiments of the present application, "plurality" means two or more than two. The following terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0037] In addition, flow charts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or a certain step or several steps of operations may be removed from these processes.

[0038] Reference Figure 1 , is a flow chart of an optional example of the data collection method proposed in the present invention. The method can be applied to computer devices. The application scenario of this embodiment is the data collection of the sample library of the CDC. The data collection method proposed in this embodiment may include but is not limited to the following steps:

[0039] Step S1, define acquisition configuration according to the object;

[0040] The collection configuration includes an identification number ID, a signal strength index, an access port, a URL path, and a storage structure. Through this setting, targeted settings can be made for different objects to improve the applicability of this solution.

[0041] In this implementation scenario, a communication connection can be established with the sample analysis device and the ultra-low temperature sample storage device through the serial port.

[0042] Step S2, obtaining the collection instruction and analyzing it to obtain the data identification;

[0043] Step S3, performing data collection based on the data identifier and the collection configuration to obtain data of the object;

[0044] In steps S2-S3, each data corresponds to an identification code. During the collection process, the data is identified based on the corresponding cryptographic platform to determine the data identification corresponding to the data; when collecting data, the platform receives the connection request message sent by the terminal, and the platform returns the data to the perception terminal. The cryptographic platform identifies the data and determines its corresponding data identification code, and provides users with identified data. The data obtained in this way is safe, reliable, mutually recognized and shared, achieving the technical effect of improving data collection efficiency and reliability.

[0045] Step S4: based on a preset information standard, convert the data of the object into a format to obtain converted data;

[0046] Step S5: uploading the converted data based on the security component.

[0047] In this implementation scenario, in general, steps S2 to S5 can be summarized as follows: receiving the operating data of the sample analysis equipment and the sample storage equipment, and uploading them to the equipment operation and maintenance detection system to realize the operation monitoring of the relevant equipment; receiving the analysis result data of the sample analysis equipment, and completing the conversion of the manufacturer's sampling data to the standard sample information data in accordance with the requirements of the "CDC Sample Informationization Standard"; "operating the security component of the CDC sample library informationization annotation" and uploading the data to the CDC sample library.

[0048] Step S6, analyzing the data of the object in combination with a preset threshold to obtain an analysis result;

[0049] Step S7: Building a cluster for collection and monitoring, and coordinating message queues and transmission channels based on the cluster.

[0050] In this application scenario, the cluster can be a ZooKeepe cluster. ZooKeeper is a distributed, open source distributed application coordination service. It is an open source implementation of Google's Chubby and an important component of Hadoop and Hbase. It is a software that provides consistency services for distributed applications. The functions it provides include: configuration maintenance, domain name services, distributed synchronization, group services, etc. The goal of ZooKeeper is to encapsulate complex and error-prone key services and provide users with simple and easy-to-use interfaces and high-performance, stable systems. ZooKeeper contains a simple set of primitives and provides Java and C interfaces.

[0051] In the step S6, it also includes:

[0052] S6.1. Calculate the data of the object according to a preset weighting rule to obtain a comparison value;

[0053] Among them, the weighted rules can be set according to different scenarios. For example, corresponding coefficients can be set for temperature, current, voltage, and humidity respectively to achieve weighted calculation and obtain a comparison value.

[0054] Specifically, through this setting, the solution can be applied to different objects and scenarios.

[0055] S6.2. Compare the comparison value with a preset threshold value, generate the state of the object, and obtain an analysis result.

[0056] In the step S7, it also includes:

[0057] S7.1. Based on the order in which the cluster sends connection requests to the reader / writer and allocates communication addresses and communication times, it can be set that each communication address corresponds to a communication time of a preset length;

[0058] S7.2, based on sending the data transmission instruction to the multiple terminals, and sequentially receiving the data sent by the terminals within the communication time corresponding to the allocated communication address;

[0059] S7.3, sorting and processing the monitored data, and putting the sorted data into the pre-trained decision tree;

[0060] S7.4. Traverse the decision tree and classify the data by type according to the nodes in the decision tree.

[0061] Among them, the decision tree is a tree structure, in which each internal node represents a test on an attribute, each branch represents a test output, and each leaf node represents a category. The classification tree (decision tree) is a very commonly used classification method. It is a supervised learning. The so-called supervised learning is given a bunch of samples, each sample has a set of attributes and a category, these categories are determined in advance, then a classifier is obtained through learning, and this classifier can give the correct classification of new objects. This kind of machine learning is called supervised learning.

[0062] like Figure 2 As shown, a data acquisition system comprises:

[0063] A definition module, used to define acquisition configuration according to objects;

[0064] The instruction analysis module is used to obtain and analyze the collection instructions to obtain data identification;

[0065] A collection module collects data based on the data identifier and the collection configuration to obtain data of the object;

[0066] A conversion module, based on a preset information standard, converts the format of the data of the object to obtain converted data;

[0067] The upload module uploads the converted data based on the security component.

[0068] 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.

[0069] A data collection device:

[0070] at least one processor;

[0071] at least one memory for storing at least one program;

[0072] When the at least one program is executed by the at least one processor, the at least one processor implements the data collection method as described above.

[0073] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device 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.

[0074] A storage medium stores processor-executable instructions, which are used to implement a data acquisition method as described above when executed by the processor.

[0075] The contents of the above method embodiments are all applicable to the present storage medium embodiments. The functions specifically implemented by the present storage medium 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.

[0076] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art may 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 data collection method, characterized in that: The following steps are involved: Define the collection configuration according to the object; Obtain and analyze the collection instructions to obtain data identification; Perform data collection based on the data identifier and the collection configuration to obtain data of the object; Based on a preset information standard, the data of the object is formatted to obtain converted data; The converted data is uploaded based on the security component.

2. A data collection method according to claim 1, characterized in that: Also includes: The data of the object is analyzed in combination with a preset threshold to obtain an analysis result.

3. A data collection method according to claim 2, characterized in that: The collection configuration includes an identification number ID, a signal strength indicator, an access port, a URL path and a storage structure.

4. A data collection method according to claim 2, characterized in that: Also includes: Build a cluster for collection and monitoring; Message queues and transmission channels are coordinated based on the cluster.

5. A data collection method according to claim 4, characterized in that: The step of coordinating the message queue and the transmission channel based on the cluster specifically includes: Based on the order in which the cluster sends connection requests to the reader / writer and allocates communication addresses and communication times; Based on the sending of data transmission instructions to multiple terminals, the data sent by the terminals within the communication time corresponding to the allocated communication addresses are received in sequence.

6. A data collection method according to claim 4, characterized in that: Also includes: Sorting the monitored data and putting the sorted data into the pre-trained decision tree; The decision tree is traversed, and the data is classified according to type according to the nodes in the decision tree.

7. A data collection method according to claim 1, characterized in that: The step of analyzing the data of the object in combination with a preset threshold to obtain an analysis result specifically includes: Calculating the data of the object according to a preset weighting rule to obtain a comparison value; The comparison value is compared with a preset threshold value to generate the state of the object and obtain an analysis result.

8. A data acquisition system, characterized in that: include: A definition module is used to define acquisition configuration according to the object; The instruction analysis module is used to obtain and analyze the collection instructions to obtain data identification; A collection module collects data based on the data identifier and the collection configuration to obtain data of the object; A conversion module, based on a preset information standard, converts the format of the data of the object to obtain converted data; The upload module uploads the converted data based on the security component.

9. A data acquisition device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a data collection method as described in any one of claims 1-7.

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