Experimental instrument intelligent data management system and method based on RFID electronic tag

Abstract

The invention discloses an intelligent data management system and method for an experimental instrument based on an RFID electronic tag, and relates to the technical field of data management, and the method comprises the steps: carrying out the RFID electronic tag initialization of a pre-managed experimental instrument; performing instrument management deployment based on radio frequency management and application programming, and constructing an instrument intelligent management module, performing continuous radio frequency identification on the initialized RFID electronic tag, and determining an instrument data stream; receiving and storing instrument data streams in real time, and constructing an instrument database; and performing experimental instrument management and data flow sharing management based on the instrument database. The technical problems of low experimental instrument management efficiency and poorer instrument data instantaneity and accuracy caused by difficulty in quickly and accurately identifying the experimental instrument and tracking the use condition of the experimental instrument in real time in the existing experimental instrument data management are solved. The technical effect of improving the management efficiency of the experimental instrument data and the real-time performance and accuracy of the instrument data is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to data management, and specifically to an intelligent data management system and method for experimental instruments based on RFID electronic tags. Background Art

[0002] With the continuous progress of scientific research and experimental technology, the management and data processing of laboratory instruments have become increasingly important topics in laboratory management. The intelligent management of laboratory instruments has become a key link in improving scientific research efficiency, ensuring data accuracy and ensuring efficient use of laboratory resources. There are many types of laboratory instruments with different specifications. As the scale of the laboratory expands, the number of instruments continues to increase, resulting in a significant increase in the efficiency of instrument use and the difficulty of management. Traditional laboratory instrument management methods usually rely on manual records or partial digital systems. These methods often have problems such as low management efficiency, easy data errors, and difficult maintenance. They cannot meet the growing management needs of modern laboratories. The laboratory instrument data management system based on RFID electronic tags came into being. RFID (radio frequency identification) technology has been widely used in logistics tracking, asset management and other fields due to its non-contact, automatic identification, large data volume, and strong anti-interference ability. It is introduced into the field of laboratory instrument management. By equipping each laboratory instrument with a unique RFID electronic tag, the unique identification and rapid identification of the instrument identity are realized.

[0003] Therefore, in the current laboratory instrument data management related technologies, there are technical problems such as difficulty in quickly and accurately identifying laboratory instruments and tracking the usage of laboratory instruments in real time, which leads to inefficient laboratory instrument management and poor real-time and accuracy of instrument data. Summary of the invention

[0004] The present application provides an intelligent data management system and method for experimental instruments based on RFID electronic tags, thereby solving the technical problems existing in the existing experimental instrument data management, such as difficulty in quickly and accurately identifying experimental instruments and tracking the use of experimental instruments in real time, which leads to low efficiency in experimental instrument management and poor real-time and accuracy of instrument data. The application achieves the technical effect of improving the management efficiency, real-time and accuracy of instrument data.

[0005] The present application provides an intelligent data management system for experimental instruments based on RFID electronic tags, and the system includes: a tag initialization module, which is used to initialize the RFID electronic tags of pre-managed experimental instruments; an instrument management deployment module, which is used to perform instrument management deployment based on radio frequency management and application programming with software and hardware compatibility constraints, and build an instrument intelligent management module, wherein the application programming includes functional dimensions and update dimensions; an instrument data flow determination module, which is used to combine the instrument intelligent management module, with application programming as a guide, to assist a reader in performing continuous radio frequency identification on the initialized RFID electronic tags, and determine the instrument data flow, wherein continuous dynamic radio frequency identification is constrained by dynamic frame time slots; an instrument database construction module, which is used to plan the database structure with static and dynamic storage as a baseline, receive and store the instrument data flow in real time, and build an instrument database, wherein the database structure has dynamic and static data structure interactions; a data flow sharing management module, which is used to store the instrument database at the back end, and perform experimental instrument management and data flow sharing management based on the instrument database, wherein the instrument database has periodic reconstruction.

[0006] In a possible implementation, the instrument data flow determination module also performs the following processing: the instrument intelligent management module includes a radio frequency management unit and an application programming unit, the application programming unit includes a functional dimension branch and an update dimension branch for lateral interaction, wherein the application programming unit can be remotely operated; an initial time slot frame is set, and based on the initial time slot frame, an instrument time slot count value is set, radio frequency execution and read and write logic are performed, and the functional dimension branch in the application programming unit is updated, wherein a single tag response within a single time slot is used as a constraint; the radio frequency management unit responds to the functional dimension branch and performs collision-free radio frequency management based on the RFID electronic tag.

[0007] In a possible implementation, the instrument data flow determination module also performs the following processing: receiving RF response data and locating RF management anomalies, wherein blank response time slots and collision response time slots are used as positioning criteria; the update dimension branch performs logical updates based on the RF management anomalies and time slot frame adjustments to determine the update program; the functional dimension branch receives the update program and replaces it, and performs the next round of RF identification in response to the RF management unit.

[0008] In a possible implementation, the instrument data flow determination module also performs the following processing: introducing a grouping mechanism, the grouping mechanism groups the experimental instruments and marks them with RFID electronic tags; introducing a priority strategy, marking the experimental instruments with radio frequency sequences; and based on the grouping mechanism and the priority strategy, managing and constraining the radio frequency management unit.

[0009] In a possible implementation, the data stream sharing management module also performs the following processing: setting a preset period, wherein the preset period is the time interval for reorganizing the data of the instrument database; determining a periodic data set based on the preset period; traversing the periodic data set, reorganizing and resetting the storage of static periodic data sets and dynamic periodic data sets through dynamic and static conversion interactions, and determining to update the database, wherein the data link in the dynamic periodic data set is updated in real time.

[0010] In a possible implementation, the data stream sharing management module also performs the following processing: based on a preset time threshold, the dynamic periodic data set is updated and judged, and if the data link update is empty, it is converted into a data sequence and the data structure is transferred; based on the homology and correlation thresholds, the static periodic data set is judged, and if it is homologous data and meets the correlation threshold, the data structure is transferred.

[0011] In a possible implementation, the intelligent data management system for experimental instruments based on RFID electronic tags also performs the following processing: determining a multi-device configuration, wherein the multiple devices include experimental instruments and terminal devices; accessing a communication protocol, interconnecting the multi-device configuration, and performing device interaction management, including data sharing interaction from the experimental instrument side to the terminal device side, between terminal devices, and contactless control from the terminal device side to the experimental instrument side.

[0012] The present application also provides an intelligent data management method for experimental instruments based on RFID electronic tags, the method comprising: initializing the RFID electronic tags of pre-managed experimental instruments; deploying instrument management based on radio frequency management and application programming with software and hardware compatibility constraints, and building an instrument intelligent management module, wherein application programming includes functional dimensions and update dimensions; combining the instrument intelligent management module, guided by application programming, an auxiliary reader continuously performs radio frequency identification on the initialized RFID electronic tags to determine the instrument data stream, wherein continuous dynamic radio frequency identification is constrained by dynamic frame time slots; planning a database structure with static and dynamic storage as a baseline, receiving and storing the instrument data stream in real time, and building an instrument database, wherein the database structure has dynamic and static data structure interactions; storing the instrument database at the back end, and performing experimental instrument management and data stream sharing management based on the instrument database, wherein the instrument database has periodic reconstruction.

[0013] The present application proposes an intelligent data management system and method for experimental instruments based on RFID electronic tags, which initializes the RFID electronic tags of pre-managed experimental instruments; deploys instrument management based on radio frequency management and application programming, and builds an intelligent instrument management module, wherein: the initialized RFID electronic tags are continuously radio frequency identified to determine the instrument data stream; the instrument data stream is received and stored in real time to build an instrument database; and experimental instrument management and data stream sharing management are performed based on the instrument database. This solves the technical problem of the difficulty in quickly and accurately identifying experimental instruments and tracking the use of experimental instruments in real time in the existing experimental instrument data management, which leads to low efficiency in experimental instrument management and poor real-time and accuracy of instrument data, and achieves the technical effect of improving the management efficiency of experimental instrument data and the real-time and accuracy of instrument data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of the structure of an intelligent data management system for experimental instruments based on RFID electronic tags provided in an embodiment of the present application; Figure 2 A flowchart of an intelligent data management method for experimental instruments based on RFID electronic tags is provided in an embodiment of the present application.

[0016] Description of the reference numerals: label initialization module 10 , instrument management and deployment module 20 , instrument data flow determination module 30 , instrument database construction module 40 , data flow sharing management module 50 . DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides an intelligent data management system for experimental instruments based on RFID electronic tags, such as Figure 1 As shown, the system comprises: The tag initialization module 10 is used to initialize the RFID electronic tag of the pre-managed experimental instrument.

[0021] Preferably, RFID electronic tag initialization refers to configuring a unique RFID electronic tag for each experimental instrument before managing the experimental instrument, and binding the tag with the corresponding instrument information, digitizing the basic information of the instrument through the RFID tag, so that it can be quickly read and tracked through the radio frequency identification device in subsequent use and management. Specifically, RFID electronic tag initialization includes assigning a unique RFID electronic tag to each experimental instrument, which contains a unique identification code and is associated with the basic information of the instrument (such as model, number, function, usage record, etc.); entering the basic information of the experimental instrument (such as the physical characteristics, maintenance information, storage location, usage status, etc. of the experimental instrument) into the system, including medicine cabinet data entry and reagent data entry, entering the number, name, category, and storage location of these medicine cabinet data and reagent data, and binding this information to the RFID electronic tag; writing basic information related to the experimental instrument into the RFID tag to ensure that the RFID tag can correctly identify the instrument through the radio frequency reading device in subsequent management. The tag content usually contains the unique ID of the instrument, instrument attributes, usage records, etc. Through RFID electronic tag initialization, a one-to-one correspondence between RFID tags and experimental instruments is achieved.

[0022] The instrument management and deployment module 20 is used to perform instrument management and deployment based on radio frequency management and application programming with software and hardware compatibility constraints, and to build an instrument intelligent management module, wherein application programming includes functional dimensions and update dimensions.

[0023] Preferably, the software and hardware compatibility constraint means that the software programs and hardware devices (such as RFID tags, radio frequency readers, etc.) in the system need to be compatible with each other to ensure the stable operation of the entire system. For example, program plug-ins and software must support the management and application of RFID radio frequency technology, and the hardware devices can correctly execute the instructions of the programming part and interact with data to ensure the coordinated work of various components of the system and avoid system failure or abnormal function due to incompatibility; radio frequency management is responsible for instrument identification, data collection and communication through radio frequency technologies such as RFID. The radio frequency part transmits the status and location information of the instrument to the management system by reading the information in the RFID tag. Application programming controls, manages and processes data for the radio frequency management process by writing and executing software programs. Among them, application programming includes functional dimensions and update dimensions. The functional dimension in application programming defines the basic functions of the system, including how to manage instrument data, how to identify RFID tags, store and update information, etc. The update dimension refers to the system's ability to automatically update and adjust software programs or management strategies according to changes in management needs or operating environment to ensure that the system can continuously adapt to new conditions or requirements, for example, the system can specify the frequency of RFID, data processing method and how to handle defect information through the programming module; specifically, the programming part will pre-set the basic operation process of RFID management, called the initial RFID program, including how to read tags, collect instrument information, analyze data, etc. through RFID signals. The set initial RFID program is executed by the RFID part, which starts to communicate with the RFID tag and receive basic information of the instrument. After the RFID part executes the initial program, it receives the information stream from the RFID tag and processes the data. If any abnormality is found during the information reception process (such as missing data, signal interference, tag reading error, etc.), the system will locate the defect, that is, find the problem area in the data or abnormal instrument status. For the identified defects or abnormal conditions, the programming part will automatically adjust the program and update the processing logic to adapt to new needs or fix problems, such as adjusting the parameters of RFID, optimizing the data processing algorithm or fixing loopholes in the program, etc., and feed back these new settings and instructions to the RFID part. The RFID part re-executes the information reading and management process according to the updated program, thereby realizing the system's self-adaptation and dynamic adjustment. By combining programming and radio frequency technology, an intelligent management module is created that can automatically execute, identify, update and manage experimental instruments. This intelligent management module is the core of the entire management system and is responsible for coordinating the interaction between software and hardware to achieve intelligent management and ensure the accuracy and timeliness of experimental instrument data and the effectiveness of management.

[0024] The instrument data flow determination module 30 is used to combine with the instrument intelligent management module, guided by application programming, to assist the reader in performing continuous radio frequency identification on the initialized RFID electronic tag to determine the instrument data flow, wherein the continuous dynamic radio frequency identification is constrained by the dynamic frame time slot.

[0025] Preferably, the RFID electronic tag initialized by radio frequency identification is based on application programming, that is, the radio frequency identification mode, frequency and data processing rules are set through software programs. The application programming determines how the system uses RFID readers to identify RFID tags, how to receive and process data streams, and how to adjust the radio frequency identification process when necessary. Specifically, the auxiliary reader refers to an RFID reader that is specifically used to identify RFID electronic tags through radio waves. Continuous radio frequency identification refers to the auxiliary reader continuously scanning and reading the RFID tag information data attached to the experimental instrument in a continuous manner. It is not just a single read, but multiple identifications and readings are performed within a specific time period as needed. This continuous identification process helps to continuously obtain instrument information when the experimental instrument moves, changes position or updates its status, thereby ensuring the integrity and real-time nature of the data stream; through the continuous identification of the RFID reader, various data about the experimental instrument can be obtained, such as the status, location, usage records, etc. of the instrument, and these information are collected together to form Instrument data stream refers to a kind of experimental instrument-related data that is continuously updated and transmitted. The formation of data stream enables the laboratory management system to track and analyze the instrument usage, fault information, etc. in real time. Among them, continuous dynamic radio frequency identification is constrained by dynamic frame time slots, which is a time control mechanism in the radio frequency identification process. The RFID reader continues to communicate and identify with the RFID tag dynamically. The auxiliary reader can identify the same tag multiple times at different time points and in different scenarios to ensure that the latest data can still be obtained when the instrument moves or the environment changes. In the radio frequency identification process, the communication between the RFID reader and the tag is not carried out randomly, but at a certain time interval. The frame time slot refers to the time window for communication between the tag and the reader, that is, within the specified time period, the tag transmits data to the reader. The dynamic frame time slot means that this time window is flexible and can be dynamically adjusted according to the actual situation. For example, when the number of tags is large, the system can shorten the time slot to speed up the reading speed; when the number of tags is small, the system can extend the time slot to optimize performance. Through the constraints of dynamic frame time slots, the system can flexibly adjust the frequency and timing of RFID under different environments and data volumes, ensuring the real-time and integrity of data, avoiding conflicts and redundancy in data transmission, and improving recognition efficiency, data recognition accuracy and system adaptability.

[0026] The instrument database construction module 40 is used to plan the database structure based on static and dynamic storage, receive and store the instrument data stream in real time, and construct the instrument database, wherein the database structure has interaction between static and dynamic data structures.

[0027] Preferably, static storage and dynamic storage are two different data management methods. Specifically, static storage refers to the storage of relatively fixed data that does not change frequently, such as basic information, serial number, model, purchase date, etc. of experimental instruments. This information will not change for a period of time and belongs to static data. Static storage is usually used to save such historical or basic data; dynamic storage refers to the storage of data that will be frequently updated or change over time, such as the real-time status, usage record, maintenance history, current location, etc. of the instrument. Dynamic data is constantly updated as the use and status of the experimental instrument change, and the system needs to frequently store and process this data; based on these two storage methods, a database structure is planned for storing instrument-related data, which can balance the storage requirements of different types of data, ensuring the long-term storage of stable data by the system, and processing real-time changing data; the database structure can support the storage and interaction of two types of data. The core of the design is how to efficiently store, retrieve and process these different types of data to ensure the stability and real-time responsiveness of the system. By managing static data and dynamic data separately, the system can process data more efficiently. For example, the storage space optimization of static data and the frequent update of dynamic data can be carried out independently without affecting each other. During operation, real-time data streams of experimental instruments are continuously obtained from RFID and other devices, including dynamic information such as the instrument's status, location, and usage records. These data streams are classified and stored to ensure that the instrument information identified each time can be quickly stored in the database, and an instrument database is constructed to manage the data of all experimental instruments and support rapid retrieval, analysis, and sharing of data. Among them, dynamic and static data structure interaction refers to the interaction and collaboration between static data and dynamic data in the database. Static data (such as basic information about the instrument) provides the background and basic information of the data. When dynamic data (such as real-time status and usage) is updated in real time, it will refer to the static data for analysis and processing. For example, when monitoring the real-time status of an instrument, the system will consult its static information, such as the instrument's specifications and usage rules, to determine whether the current status is normal, ensuring that the system can combine static data for more accurate analysis and decision-making when processing dynamic data.

[0028] The data stream sharing management module 50 is used for back-end storage of the instrument database, and performs experimental instrument management and data stream sharing management based on the instrument database, wherein the instrument database is periodically reconstructed.

[0029] Preferably, the database of experimental instruments is not directly managed and stored on the front-end device (such as the laboratory computer or RFID reader), but the data is uploaded to the back-end server for storage and management. The back-end storage can provide the system with more powerful data processing and storage capabilities, and also allows data to be accessed and managed across multiple devices. Specifically, in the back-end storage, the database is responsible for saving all static and dynamic information related to the experimental instruments, including the basic properties, real-time status, usage records, maintenance information, etc. of each experimental instrument, to ensure the security, integrity and rapid access and processing capabilities of the data. Based on the instrument database stored in the back-end, the system can manage experimental instruments and share data streams, where experimental instrument management refers to the use of data in the database to manage experimental instruments. Carry out daily management, such as real-time tracking of the status, location, and usage of experimental instruments, record the usage and maintenance records of each instrument to facilitate subsequent traceability and management, and provide automated management functions, such as automatic detection of instrument failures, maintenance reminders, and scheduling of experimental instruments; data flow sharing management means that the management data of experimental instruments is not limited to a single device or laboratory. The data in the database can be shared among multiple systems or users. For example, the usage data of experimental instruments can be shared with different laboratories or research teams to facilitate the joint use and management of equipment, and the experimental data can be connected with other related systems (such as experimental management systems, resource management systems, etc.) to improve the efficiency of overall laboratory management, support different users to access the real-time data and historical data of the instrument, and realize information sharing and collaboration.

[0030] Preferably, periodic reconstruction means that the database will be regularly optimized or adjusted in structure according to the set time period or data changes during operation to ensure that the database can continue to operate efficiently and adapt to the growth of data volume and changes in system requirements. Specifically, periodic reconstruction includes data cleaning and archiving, index reconstruction, database table structure optimization, etc. As time goes by, a large amount of historical data will accumulate in the database, which may cause the system to run slowly or the storage space to be insufficient. Periodic reconstruction will regularly clean up expired data that is no longer needed or archive historical data to another storage space to keep the database running efficiently. For example, some older experimental data may be archived to cold storage and only restored when needed. In the database, the index is a key structure that helps to quickly find data. As the amount of data increases, the original index may become inefficient and affect the query speed. During periodic reconstruction, the database can rebuild the index structure to improve the speed and efficiency of data query. As the experimental instrument data and management requirements change, it may be necessary to optimize the table structure of the database, for example, adding new fields, adjusting the relationship between data tables, optimizing data storage methods, etc. These adjustments can help the system better adapt to new requirements and ensure that data storage and query are more efficient. Ensure that the database can maintain efficient and stable operation for a long time, while adapting to the increase in data volume and changes in system requirements.

[0031] According to an embodiment of the present invention, an intelligent data management system for laboratory instruments based on RFID electronic tags is used to solve the technical problems of the existing laboratory instrument data management, such as difficulty in quickly and accurately identifying laboratory instruments and tracking the use of laboratory instruments in real time, which leads to low management efficiency of laboratory instruments and poor real-time and accuracy of instrument data, thereby achieving the technical effect of improving the management efficiency, real-time and accuracy of laboratory instrument data. An intelligent data management system for laboratory instruments based on RFID electronic tags includes: a tag initialization module 10, an instrument management deployment module 20, an instrument data flow determination module 30, an instrument database construction module 40, and a data flow sharing management module 50.

[0032] The specific configuration of the instrument data flow determination module 30 will be described in detail below. The instrument data flow determination module 30 may further include: the instrument intelligent management module includes a radio frequency management unit and an application programming unit, the application programming unit includes a functional dimension branch and an update dimension branch of lateral interaction, wherein the application programming unit can be remotely operated; an initial time slot frame is set, based on the initial time slot frame, an instrument time slot count value is set, radio frequency execution and read-write logic are performed, and the functional dimension branch in the application programming unit is updated, wherein a single tag response within a single time slot is constrained; the radio frequency management unit responds to the functional dimension branch and performs collision-free radio frequency management based on the RFID electronic tag.

[0033] Preferably, the radio frequency management unit is responsible for performing the radio frequency identification task of the RFID electronic tag and managing the wireless communication with the electronic tag. Its main responsibilities include sending radio frequency signals, receiving data returned by the RFID tag, and processing and parsing this data; the application programming unit controls the operation of the radio frequency management unit through programming, and is mainly used to define and update the logic and process of radio frequency management. The application programming unit can set various operation modes and functions, such as RFID identification process, data processing method, dynamic adjustment, etc.; the functional dimension branch refers to a part of the application programming unit, which is specifically responsible for managing and executing the functional logic of radio frequency management. For example, it defines how to read tags, how to process data, How to perform RF operations, etc.; the update dimension branch is responsible for updating and adjusting the system. When certain functions of RF management need to be optimized or adjusted during system operation, the update dimension branch will perform self-correction and upgrade to ensure that the system can adapt to new needs or improve performance; lateral interaction refers to the interaction between the functional dimension branch and the update dimension branch. The two are interdependent. The operation of the functional dimension branch may be adjusted according to changes in the update dimension branch. The update dimension branch determines whether updating and optimization are needed by monitoring the execution of the functional dimension; the application programming unit can be controlled and managed through remote connections, which improves the flexibility and operability of the system and facilitates management and monitoring in multiple locations.

[0034] Preferably, an initial time slot frame is set, and based on the initial time slot frame, an instrument time slot count value is set to perform radio frequency execution and read and write logic. Specifically, the initial time slot frame refers to the time unit (frame) set when the radio frequency identification process begins, which defines the basic time window for communication between the RFID reader and the tag. Based on the initial time slot frame, a specific time slot count value is set for each experimental instrument (i.e., RFID tag) to ensure that different instrument tags can respond in different time slots without conflict. The time slot count value is used to manage the timing of tag response to ensure that each tag is correctly identified and read within the specified time. After setting the time slot frame and count value, the radio frequency management unit will perform radio frequency operations based on these time slots, including communication with the RFID tag (read and write operations), and will logically process the read data for subsequent data analysis and management; through the time slot count value and feedback in radio frequency execution To update the functional dimension branch of the application programming unit, that is, during the operation process, the functional dimension is adjusted and optimized according to the recognition efficiency or data accuracy to adapt to the changing needs. A single tag response in a single time slot means that only one RFID tag can respond in each time slot to ensure that there is no communication conflict between tags. Through this constraint, the system can avoid data loss or conflict problems caused by multiple tags responding at the same time, and ensure the stability and accuracy of the recognition process; collision-free radio frequency management means that the radio frequency management unit performs radio frequency management through the logic defined by the functional dimension branch in the application programming unit to ensure that the RFID tags will not generate data conflicts or collisions during the communication process. The radio frequency management unit will ensure that each tag responds in an independent time slot according to the set time slot mechanism to avoid signal conflicts (collisions) when multiple tags respond at the same time, thereby improving the efficiency and reliability of system recognition.

[0035] The specific configuration of the instrument data flow determination module 30 will be described in detail below. The instrument data flow determination module 30 may further include: receiving radio frequency response data and locating radio frequency management anomalies, wherein the blank response time slot and the collision response time slot are used as positioning criteria; the update dimension branch performs logical updates based on the radio frequency management anomaly and the time slot frame adjustment as a reference to determine the update program; the function dimension branch receives the update program and replaces it, and performs the next round of radio frequency identification in response to the radio frequency management unit.

[0036] Preferably, when the radio frequency management unit performs radio frequency identification operations, it will continue to receive response data from the RFID tag. If an abnormality occurs during the reading process (for example, data cannot be read or multiple tags respond at the same time, resulting in a collision), the system will use blank response time slots and collision response time slots as positioning standards to identify and locate these abnormalities, wherein a blank response time slot refers to a predetermined time slot in which no RFID tag responds, such as no tag is assigned to the time slot, or the tag fails to work properly; a collision response time slot refers to a time slot in which multiple RFID tags respond at the same time, resulting in a signal conflict, and the reader cannot correctly read the information of any tag. When this happens, the system will identify it as a collision event, thereby locating the abnormality in radio frequency management and determining whether there is a problem with the radio frequency identification process; the update dimension branch will respond by adjusting the time slot frame. For radio frequency management anomalies, adjust the time slot allocation method or add additional time slots to reduce collision or blank time slot problems. After completing the logic update, the update dimension branch will generate an update program, which includes the new logic of the radio frequency identification process, such as time slot reallocation, adjustment of tag response order, optimization of reading process, etc.; when the update dimension branch generates and transmits the update program, the functional dimension branch will receive these new programs and replace the old identification logic, indicating that the radio frequency identification logic has been updated to solve the abnormal problem previously located. When the functional dimension branch completes the replacement of the update program, it will continue with the next round of radio frequency identification operations. The radio frequency management unit will perform a new round of RFID tag identification operations based on the new time slot frame allocation logic and the optimized identification process, ensuring that the system's radio frequency management can dynamically adapt to environmental changes, continuously optimize identification efficiency, and reduce the occurrence of abnormal situations.

[0037] The specific configuration of the instrument data flow determination module 30 will be described in detail below. The instrument data flow determination module 30 may further include: introducing a grouping mechanism, the grouping mechanism groups the experimental instruments and marks them with RFID electronic tags; introducing a priority strategy, marking the experimental instruments with radio frequency sequences; and managing and constraining the radio frequency management unit based on the grouping mechanism and the priority strategy.

[0038] Preferably, a grouping mechanism and a priority strategy are introduced to optimize the efficiency of experimental instrument management and radio frequency identification, and the radio frequency management unit is managed and constrained through these mechanisms. Specifically, the grouping mechanism refers to classifying and grouping experimental instruments according to their different attributes or uses. Each group contains multiple experimental instruments, and RFID electronic tags are assigned to these instruments; the priority strategy is a strategy for optimizing the order of radio frequency identification of experimental instruments. According to the frequency of use, importance or urgency of the instrument, the system assigns different priorities to the RFID tags of the instruments. High-priority experimental instruments will be identified first during the radio frequency identification process, while low-priority instruments will be identified later; the radio frequency sequence tag assigns a serial number to the RFID tag of each instrument according to the priority strategy, indicating the processing order of the instrument in radio frequency identification, which means that when reading the RFID tag, These tags are processed in order of priority to ensure that key or commonly used instruments are identified and managed first; based on the grouping mechanism and priority strategy, the operation of the radio frequency management unit is managed and constrained. When identifying RFID tags, the radio frequency management unit will prioritize the tags of a certain group of instruments according to the logic of the grouping. For example, all RFID tags of a specific group (such as a commonly used equipment group) are processed first, and other groups are temporarily ignored. This group identification enables the system to manage a large number of experimental instruments more targeted, avoid disorderly processing, and improve management efficiency; when processing RFID tags, the radio frequency management unit will determine the processing order according to the priority strategy. High-priority experimental instruments will be identified and processed first to ensure that the information of key instruments is updated and managed in a timely manner. Low-priority instruments will be identified in subsequent rounds or when the system is idle. This priority management constraint ensures efficient use of resources and time.

[0039] The specific configuration of the data stream sharing management module 50 will be described in detail below. The data stream sharing management module 50 may further include: setting a preset period, wherein the preset period is the time interval for reorganizing the data of the instrument database; determining a periodic data set based on the preset period; traversing the periodic data set, reorganizing and resetting the storage of the static periodic data set and the dynamic periodic data set through dynamic and static conversion interaction, and determining to update the database, wherein the data link in the dynamic periodic data set is updated in real time.

[0040] Preferably, the preset cycle refers to the time interval set by the system for reorganizing the data in the database. The data in the database will be reorganized and optimized once at the end of each preset cycle. The periodic data set refers to the data that is marked as needing to be reorganized at the end of each preset cycle. Through the preset time period, the system will automatically determine which data needs to be reorganized and stored and reset within the current cycle, including static periodic data sets and dynamic periodic data sets. Among them, the static periodic data set mainly contains relatively fixed and less changing historical or basic data, such as the model, purchase time, basic equipment information, etc. of the experimental instrument, and the dynamic periodic data set includes those frequently changing data, such as the use record, maintenance record, real-time data of the sensor, etc. of the experimental instrument; traversing the periodic data set, interacting with dynamic and static conversions to ensure that the system can flexibly manage static and dynamic data The data in the database is then optimized, compressed or reorganized to improve data storage efficiency and ensure data integrity. For example, some dynamically changing data streams, such as the storage, transfer, and application of an instrument, belong to the data chain in the update stage before the end. They can first exist in the dynamic state. After the end, a data sequence is generated and stored in the static state. Some static data are directly stored in the static database. At the same time, the new dynamic data stream may be related to some of the data stored in the static state before, and it can be temporarily called into the dynamic state for overall traceability analysis. Dynamic data is continuously monitored and updated to ensure that the data link in the database is always kept up to date. After the above reorganization and storage reset are completed, the system will update the overall structure and content of the database to ensure the integrity and accuracy of the data and obtain an updated database.

[0041] The specific configuration of the data stream sharing management module 50 will be described in detail below. The data stream sharing management module 50 may further include: based on a preset time threshold, performing update judgment on the dynamic periodic data set, if the data link update is empty, converting it into a data sequence and transferring the data structure; based on the homology and correlation threshold, performing judgment on the static periodic data set, if it is homology data and meets the correlation threshold, transferring the data structure.

[0042] Preferably, the preset time threshold is a time interval set for the dynamic data set, which is used to determine the update status of the data. Each dynamic data set has a preset time threshold, such as 30 seconds or 5 minutes, which is used to determine whether the data needs to be updated. When each preset time threshold is reached, the dynamic data set is checked to see if there is a new data link or data update. If there is a new data update, the data set continues to be processed as a dynamic data set; if there is no new data update, it is converted into a data sequence and the data structure is transferred. Specifically, if there is no new update or change in the dynamic data set, it is regarded as a relatively static data sequence, and the data set is no longer treated as a dynamic data set, but converted into a serialized data structure. When the data set is converted into a data sequence, it is transferred from the dynamic storage area to the static storage area, which may include rearranging the storage location of the data and optimizing the storage format to meet the long-term storage requirements of the data. For example, the data is moved out of the real-time database and stored in the historical data repository or backup system.

[0043] Preferably, homology refers to the source or content similarity of data sets. For example, parameter data of multiple experimental instruments may come from the same experimental process. According to the set homology threshold, it is determined whether different static data sets can be classified as homologous data; correlation refers to the relationship or similarity between data. The correlation threshold is used to measure the degree of association between static data sets, such as the numerical trend, data type or time relationship between two data sets. If the correlation between two data sets exceeds the set threshold, the system considers that the data sets are sufficiently similar and can be further processed; determine whether multiple static data sets are homologous data and check whether they are within the correlation threshold. If the data sets have the same source and are sufficiently similar (such as parameters, trends, time series, etc.), these data sets are classified as one type of data. When the data sets meet the homology and correlation thresholds, the data structure is transferred, which means that the system will merge or classify these data sets to reduce redundancy and improve data management efficiency. For example, the system may merge multiple similar static data sets into one data block or index to optimize storage and query efficiency.

[0044] The following will continue to describe in detail the specific configuration of intelligent data management of laboratory instruments based on RFID electronic tags. Intelligent data management of laboratory instruments based on RFID electronic tags can further include: determining a multi-device configuration, wherein the multi-device includes laboratory instruments and terminal devices; accessing a communication protocol, interconnecting the multi-device configuration, and performing device interaction management, including data sharing interaction from the laboratory instrument side to the terminal device side, between terminal devices, and contactless control from the terminal device side to the laboratory instrument side.

[0045] Preferably, determine the configuration of experimental instruments and terminal devices, such as the configuration of various test instruments and sensors used in the laboratory, and the configuration of computers, mobile terminals or consoles interconnected with the experimental instruments, and clarify the collaborative working mode, communication mode and data interaction path between devices; the communication protocol is the key to realizing device interconnection, which can be a wireless communication protocol (such as Wi-Fi, Bluetooth, Zigbee) or a wired protocol (such as RS-232, Ethernet), which determines how to exchange data between devices, how to establish connections and how to ensure the reliability of data transmission. By accessing these communication protocols, experimental instruments and terminal devices can communicate with each other, realize smooth transmission of data flow and sharing of device status, and perform device interaction management. Specifically, device interaction management refers to the management and coordination of interaction behaviors between interconnected devices, including data sharing interaction from the experimental instrument side to the terminal device side, data sharing interaction between terminal devices and data sharing interaction from the terminal device side to the experimental instrument. Contactless control on the instrument side. The data collected by the experimental instrument will be transmitted to the terminal device through the communication protocol. The terminal device can be a device for data analysis, monitoring or storage. The main content of data sharing includes the real-time status of the experimental instrument, sensor data, experimental results, etc.; Data can be shared between terminal devices. For example, a device can collect data from the experimental instrument and synchronize it with another terminal device (such as a server or cloud platform) to facilitate subsequent analysis and storage, improve the efficiency of equipment collaboration, and support multiple devices to process and manage experimental data at the same time; It emphasizes the remote control of the experimental instrument by the terminal device without physical contact. Through the terminal device, the operator can remotely issue instructions, adjust the settings of the experimental instrument, start or stop the equipment, and other operations without direct contact with the instrument itself. The contactless control method has advantages in ensuring safety and improving the convenience of remote operation. It is particularly suitable for environments that are not convenient for direct operation (such as dangerous experimental environments, clean rooms, etc.). Through intelligent interconnection and remote control, more efficient and intelligent experimental equipment management and data processing can be achieved.

[0046] In the above, refer to Figure 1 The present invention describes in detail an intelligent data management system for experimental instruments based on RFID electronic tags according to an embodiment of the present invention. Figure 2 A method for intelligent data management of experimental instruments based on RFID electronic tags according to an embodiment of the present invention is described.

[0047] An intelligent data management method for experimental instruments based on RFID electronic tags, such as Figure 2As shown, the method includes: initializing the RFID electronic tag of the pre-managed experimental instrument; based on the software and hardware compatibility constraints, instrument management deployment is performed based on radio frequency management and application programming, and an instrument intelligent management module is constructed, wherein the application programming includes functional dimensions and update dimensions; in combination with the instrument intelligent management module, guided by application programming, an auxiliary reader continuously performs radio frequency identification on the initialized RFID electronic tag to determine the instrument data stream, wherein continuous dynamic radio frequency identification is constrained by dynamic frame time slots; based on static and dynamic storage as a baseline, a database structure is planned, the instrument data stream is received and stored in real time, and an instrument database is constructed, wherein the database structure has dynamic and static data structure interactions; the instrument database is stored in the back end, and experimental instrument management and data stream sharing management are performed based on the instrument database, wherein the instrument database has periodic reconstruction.

[0048] In a possible implementation, the auxiliary reader performs continuous radio frequency identification on the initialized RFID electronic tag, including: the instrument intelligent management module includes a radio frequency management unit and an application programming unit, the application programming unit includes a functional dimension branch and an update dimension branch for lateral interaction, wherein the application programming unit can be remotely operated; an initial time slot frame is set, and based on the initial time slot frame, an instrument time slot count value is set, radio frequency execution and read-write logic are performed, and the functional dimension branch in the application programming unit is updated, wherein a single tag response within a single time slot is used as a constraint; the radio frequency management unit responds to the functional dimension branch and performs collision-free radio frequency management based on the RFID electronic tag.

[0049] In one possible implementation, collision-free radio frequency management based on the RFID electronic tag is performed, including: receiving radio frequency response data and locating radio frequency management anomalies, wherein blank response time slots and collision response time slots are used as positioning criteria; the update dimension branch performs logical updates based on the radio frequency management anomalies and time slot frame adjustments to determine an update program; the function dimension branch receives the update program and replaces it, and performs the next round of radio frequency identification in response to the radio frequency management unit.

[0050] In a possible implementation, the instrument database is periodically reconstructed, including: introducing a grouping mechanism to group the experimental instruments and mark them with RFID electronic tags; introducing a priority strategy to mark the experimental instruments with radio frequency sequences; and managing and constraining the radio frequency management unit based on the grouping mechanism and the priority strategy.

[0051] In one possible implementation, static periodic data sets and dynamic periodic data sets are reorganized and storage reset, including: setting a preset period, wherein the preset period is the time interval for reorganizing data in the instrument database; determining a periodic data set based on the preset period; traversing the periodic data sets, reorganizing and storage reset the static periodic data sets and the dynamic periodic data sets through dynamic and static conversion interactions, and determining to update the database, wherein the data link in the dynamic periodic data set is updated in real time.

[0052] In one possible implementation, the reorganization and storage reset of the static periodic data set and the dynamic periodic data set include: based on a preset time threshold, making an update judgment on the dynamic periodic data set, and if the data link update is empty, converting it into a data sequence and transferring the data structure; based on the homology and correlation thresholds, making a judgment on the static periodic data set, and if it is homologous data and meets the correlation threshold, transferring the data structure.

[0053] In one possible implementation, an intelligent data management method for experimental instruments based on RFID electronic tags also includes: determining a multi-device configuration, wherein the multiple devices include experimental instruments and terminal devices; accessing a communication protocol, interconnecting the multi-device configuration, and performing device interaction management, including data sharing interaction from the experimental instrument side to the terminal device side, between terminal devices, and contactless control from the terminal device side to the experimental instrument side.

[0054] An intelligent data management system for experimental instruments based on RFID electronic tags provided in an embodiment of the present invention can execute an intelligent data management method for experimental instruments based on RFID electronic tags provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0055] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0056] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. An intelligent data management system for experimental instruments based on RFID electronic tags, characterized in that: The system comprises: Initialize RFID electronic tags for pre-managed experimental instruments; Based on the compatibility constraints of software and hardware, instrument management and deployment are carried out based on radio frequency management and application programming to build an instrument intelligent management module. Among them, application programming includes functional dimensions and update dimensions; Combined with the instrument intelligent management module, guided by application programming, the auxiliary reader performs continuous radio frequency identification on the initialized RFID electronic tag to determine the instrument data flow, wherein the continuous dynamic radio frequency identification is constrained by the dynamic frame time slot; Based on static and dynamic storage, a database structure is planned, the instrument data stream is received and stored in real time, and an instrument database is constructed, wherein the database structure has dynamic and static data structure interactions; The backend stores the instrument database, and performs experimental instrument management and data flow sharing management based on the instrument database, wherein the instrument database is periodically reconstructed.

2. The RFID-based intelligent data management system for experimental instruments according to claim 1, characterized in that: The auxiliary reader performs continuous radio frequency identification on the initialized RFID electronic tag, including: The instrument intelligent management module includes a radio frequency management unit and an application programming unit, wherein the application programming unit includes a functional dimension branch and an update dimension branch of lateral interaction, wherein the application programming unit can be remotely operated; Setting an initial time slot frame, setting an instrument time slot count value based on the initial time slot frame, performing radio frequency execution and read / write logicization, and updating a functional dimension branch in the application programming unit, wherein a single tag response within a single time slot is constrained; The radio frequency management unit performs collision-free radio frequency management based on the RFID electronic tag in response to the functional dimension branch.

3. The RFID-based intelligent data management system for experimental instruments as claimed in claim 2, characterized in that: The collision-free radio frequency management based on the RFID electronic tag includes: Receive radio frequency response data and locate radio frequency management anomalies, wherein blank response time slots and collision response time slots are used as positioning criteria; The update dimension branch performs logic update based on the radio frequency management anomaly and the time slot frame adjustment as a reference to determine the update program; The functional dimension branch receives the update program and replaces it, and performs the next round of radio frequency identification in response to the radio frequency management unit.

4. The RFID-based intelligent data management system for experimental instruments as claimed in claim 2, characterized in that: The radio frequency management unit included in the instrument intelligent management module includes: A grouping mechanism is introduced, and the grouping mechanism groups the experimental instruments and marks them with RFID electronic tags; A priority strategy is introduced to perform radio frequency sequence tagging on the experimental instruments; Based on the grouping mechanism and the priority strategy, management constraints are imposed on the radio frequency management unit.

5. The RFID-based intelligent data management system for experimental instruments as claimed in claim 1, characterized in that: The instrument database is periodically reconstructed, including: Setting a preset period, wherein the preset period is a time interval for reorganizing the data in the instrument database; Based on the preset period, determining a periodic data set; The periodic data set is traversed, and the static periodic data set and the dynamic periodic data set are reorganized and stored and reset by dynamic and static conversion interaction, and the database is determined to be updated, wherein the data link in the dynamic periodic data set is updated in real time.

6. The RFID-based intelligent data management system for experimental instruments as claimed in claim 5, characterized in that: Reorganize and restore static and dynamic periodic data sets, including: Based on a preset time threshold, the dynamic periodic data set is updated and determined, and if the data chain update is empty, it is converted into a data sequence and the data structure is transferred; The static periodic data set is judged based on homology and correlation thresholds, and if it is homology data and meets the correlation threshold, the data structure is transferred.

7. The RFID-based intelligent data management system for experimental instruments as claimed in claim 1, characterized in that: The system further comprises: Determine the multi-device configuration, where the multi-device includes experimental instruments and terminal devices; Access the communication protocol, interconnect the multiple device configurations, and perform device interaction management, including data sharing interaction from the experimental instrument side to the terminal device side, between terminal devices, and contactless control from the terminal device side to the experimental instrument side.

8. An intelligent data management method for experimental instruments based on RFID electronic tags, characterized in that: The method is applied to an intelligent data management system for experimental instruments based on RFID electronic tags as described in any one of claims 1 to 7, and the method comprises: Initialize RFID electronic tags for pre-managed experimental instruments; Based on the compatibility constraints of software and hardware, instrument management and deployment are carried out based on radio frequency management and application programming to build an instrument intelligent management module. Among them, application programming includes functional dimensions and update dimensions; Combined with the instrument intelligent management module, guided by application programming, the auxiliary reader performs continuous radio frequency identification on the initialized RFID electronic tag to determine the instrument data flow, wherein the continuous dynamic radio frequency identification is constrained by the dynamic frame time slot; Based on static and dynamic storage, a database structure is planned, the instrument data stream is received and stored in real time, and an instrument database is constructed, wherein the database structure has dynamic and static data structure interactions; The backend stores the instrument database, and performs experimental instrument management and data flow sharing management based on the instrument database, wherein the instrument database is periodically reconstructed.

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