Blood shelter management system and method based on radio frequency identification technology

Abstract

The present application relates to the technical field of online management, and is a blood shelter management system and method based on radio frequency identification technology, specifically comprising: collecting dynamic radio frequency data of a blood shelter during movement through a radio frequency identification device, and classifying the dynamic radio frequency data; inputting first dynamic radio frequency data of the blood shelter obtained into a motion-induced disturbance model to determine a signal instability coefficient; inputting second dynamic radio frequency data of the blood shelter obtained into a blood bag coupling detuning model to determine a dielectric detuning coefficient; inputting the calculated signal instability coefficient and dielectric detuning coefficient into an inventory anomaly judgment strategy to determine a blood inventory anomaly, and performing blood inventory detection and early warning during shelter movement according to the judgment result of the blood inventory anomaly. The present application solves the problem in the prior art that inventory anomalies cannot be accurately identified and warned, and the reliability and efficiency of blood inventory management are low.

Description

Technical Field

[0001] This invention relates to the field of online management technology, specifically a blood mobile hospital management system and method based on radio frequency identification (RFID) technology. Background Technology

[0002] In the management of mobile blood supply facilities, real-time monitoring of blood inventory is crucial, directly impacting the safety and accessibility of clinical blood use. Existing technologies are mostly designed for static or quasi-static environments, generally neglecting the unique challenges faced by mobile blood supply facilities as mobile medical units under complex road conditions (such as bumps, turns, and sudden braking). During the movement of the mobile blood supply facility, the violent motion not only causes significant swaying of blood bags, leading to multipath fading and phase jitter (i.e., signal instability) in radio frequency signals, but more importantly, the swaying of the liquid inside the blood bags alters their overall dielectric properties, resulting in complex electromagnetic coupling with the RFID tag antenna attached to them, causing a shift in the tag's resonant frequency. The combined effect of these two factors causes RFID systems that perform well under stable road conditions to experience a sharp drop in read rates and loss of inventory information in dynamic environments, seriously threatening the safety and traceability of blood transport.

[0003] The above background indicates that existing technologies cannot comprehensively analyze the radio frequency behavior of blood mobile units in dynamic mobile environments, especially the individual effects of motion interference and dielectric detuning of blood bags. This results in the inability to accurately identify and warn of inventory anomalies, reducing the reliability and efficiency of blood inventory management. Summary of the Invention

[0004] The technical problem to be solved by this invention is that the existing technology cannot accurately identify and warn of inventory anomalies, resulting in low reliability and efficiency of blood inventory management. This invention proposes a blood mobile cabin management system and method based on radio frequency identification technology.

[0005] This invention deploys multiple types of sensors to simultaneously collect kinematic data and radio frequency signal characteristic data of the mobile cabin. The acquired first dynamic radio frequency data (characterizing motion-induced disturbance) is imported into a motion-induced disturbance model to calculate the signal instability coefficient, and the second dynamic radio frequency data (characterizing blood bag coupling) is imported into a blood bag coupling detuning model to calculate the dielectric detuning coefficient. Finally, by fusing these two coefficients, inventory anomaly judgment and early warning are performed. This invention is the first to incorporate the liquid dynamic characteristics of blood bags and their dielectric changes into an RFID performance evaluation model, realizing the separate monitoring and comprehensive diagnosis of motion-induced disturbance and dielectric detuning. Thus, without stopping the vehicle or increasing the radio frequency power, it effectively improves the accuracy and reliability of blood inventory counting in complex mobile environments.

[0006] To achieve the above objectives, the technical solution of the blood mobile hospital management method based on radio frequency identification technology of the present invention includes the following steps:

[0007] S1. Install the monitoring radio frequency identification device at the location that needs to be monitored in the blood mobile cabin. The radio frequency identification device collects dynamic radio frequency data of the blood mobile cabin during its movement and classifies the dynamic radio frequency data.

[0008] S2. Import the obtained first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient;

[0009] S3. Import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient;

[0010] S4. The calculated signal instability coefficient and dielectric detuning coefficient are imported into the blood container inventory anomaly judgment strategy to judge blood inventory anomalies.

[0011] S5. Conduct blood inventory early warning detection during the relocation of the mobile hospital based on the judgment results of abnormal blood inventory.

[0012] Preferably, S1 includes:

[0013] S11. Install the monitoring radio frequency identification device at the designated location in the blood container that needs to be monitored, install the triaxial accelerometer on the load-bearing beam of the container and the blood bag suspension bracket, collect the linear acceleration and angular acceleration during the movement of the blood container, integrate the radio frequency signal analyzer and the reader, and collect the phase, power and tag response frequency of the signal.

[0014] S12. The curve of the three-axis acceleration data changing with time during the movement of the blood container is obtained and stored in the first storage module. At the same time, the curve of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood container is stored in the second storage module. Simultaneously, the curve of the resonant frequency deviation of the blood bag tag response changing with time during the movement of the blood container is obtained and stored in the third storage module.

[0015] Preferably, the motion-induced perturbation model in S2 includes:

[0016] S21. Extract the curves of the three-axis acceleration data changing with time during the movement of the blood transport container and the curves of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood transport container, and set them as the first dynamic radio frequency data.

[0017] S22. The extracted first dynamic radio frequency data is imported into the signal instability coefficient calculation formula to determine the signal instability coefficient. The signal instability coefficient calculation formula is as follows:

[0018] ;

[0019] in, The signal instability coefficient, These are the start and end times of the test. For test duration, The magnitude of the combined acceleration vector of the mobile cabin. Let be the received power of the radio frequency signal during time period t. This is the reference received power measured under static conditions; The standard deviation of the radio frequency signal phase during the movement of the blood transport mobile unit over time time t. dt is the set signal phase stability safety threshold, and dt is the integral over time.

[0020] Preferably, the blood bag coupling detuning model in S3 includes the following specific steps:

[0021] S31. Extract the three-dimensional acceleration curve of the blood bag suspension point over time and the blood bag tag response resonant frequency deviation curve over time during the movement of the blood container, and set them as the second dynamic radio frequency data.

[0022] S32. The extracted curves of the three-dimensional acceleration of the blood bag suspension point over time and the curve of the blood bag label response resonant frequency deviation over time during the movement of the blood container are imported into the dielectric detuning coefficient calculation formula to determine the dielectric detuning coefficient. The dielectric detuning coefficient calculation formula is as follows:

[0023] ;

[0024] in, The dielectric detuning coefficient; The vector magnitude of the overall swaying acceleration of the blood bag during time interval t;

[0025] Let be the resonant frequency offset of the i-th blood bag label during time period t;

[0026] The set resonant frequency offset safety threshold;

[0027] Let be the blood dielectric perturbation factor of the i-th blood bag during time period t.

[0028] Preferably, S4 includes:

[0029] S41. Extract the signal instability coefficient and dielectric detuning coefficient obtained during the test time;

[0030] S42. Substitute the obtained signal instability coefficient and dielectric detuning coefficient within the test time into the inventory anomaly judgment value calculation formula to determine the inventory anomaly judgment value. The inventory anomaly judgment value calculation formula is as follows: ;

[0031] in, This represents the proportion of signal instability coefficient. The proportion of dielectric detuning coefficient, where Meanwhile, considering the concealment and destructiveness of the blood bag liquid coupling effect, the following settings were made: ;

[0032] S43. Compare the calculated abnormal judgment value with the set abnormal judgment value. If the calculated abnormal judgment value is greater than or equal to the set abnormal judgment value, the blood container inventory behavior is judged to be abnormal and needs to be checked. If the calculated abnormal judgment value is less than the set abnormal judgment value, the blood container inventory behavior is judged to be normal.

[0033] Preferably, S5 includes: transmitting the judgment result to the mobile monitoring center via wireless early warning, and the monitoring center immediately notifying the blood mobile cabin management personnel or conducting emergency inventory verification and label repair work at the next site based on the judgment result.

[0034] In addition, the blood mobile hospital management system based on radio frequency identification technology of the present invention includes the following modules:

[0035] Data acquisition module, motion disturbance analysis module, blood bag coupling mismatch analysis module, inventory anomaly comprehensive judgment module, and mobile cabin anomaly early warning module;

[0036] The data acquisition module is used to install the monitoring radio frequency identification device at the designated location in the blood transport cabin that needs to be monitored. The radio frequency identification device collects dynamic radio frequency data from the blood transport cabin and classifies the dynamic radio frequency data.

[0037] The motion disturbance analysis module is used to import the first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient.

[0038] The blood bag coupling detuning analysis module is used to import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient.

[0039] The inventory anomaly comprehensive judgment module is used to import the calculated signal instability coefficient and dielectric detuning coefficient into the inventory anomaly judgment strategy to judge blood inventory anomalies.

[0040] The mobile cabin anomaly early warning module is used to detect and warn of blood inventory abnormalities during the movement of the mobile cabin based on the judgment results of blood inventory abnormalities.

[0041] A storage medium storing instructions that, when read by a computer, cause the computer to execute the blood mobile hospital management method based on radio frequency identification technology.

[0042] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned blood mobile hospital management method based on radio frequency identification technology.

[0043] Compared with the prior art, the technical effects of the present invention are as follows:

[0044] This invention, by constructing a motion-induced disturbance model and a blood bag coupling detuning model, is the first to combine the macroscopic motion of the blood transport unit with the microscopic electromagnetic property changes of the blood bag liquid, thus providing a dual modeling of RFID performance in mobile environments. In particular, it introduces parameters strongly correlated with blood characteristics, such as blood bag swaying acceleration, blood dielectric disturbance factor, and tag resonant frequency shift, to accurately quantify dielectric detuning problems that are undetectable by traditional methods. This method can effectively diagnose inventory reading anomalies caused by vehicle bumps and turns without stopping the vehicle or illegally increasing RF power, and distinguish whether the problem stems from signal propagation path deterioration or tag performance degradation. This provides a basis for precise intervention and greatly improves the reliability and safety of blood transport unit management in real mobile environments. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0046] Figure 1 This is a flowchart illustrating the blood mobile hospital management method based on radio frequency identification technology of the present invention.

[0047] Figure 2 This is a schematic diagram of the blood mobile hospital management system based on radio frequency identification technology of the present invention. Detailed Implementation

[0048] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0049] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0050] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0051] Example 1:

[0052] like Figure 1 As shown in the figure, the blood mobile hospital management method based on radio frequency identification technology in this embodiment of the invention is as follows: Figure 1 As shown, the specific steps include the following:

[0053] S1. Install the monitoring radio frequency identification device at the location that needs to be monitored in the blood mobile cabin. The radio frequency identification device collects dynamic radio frequency data of the blood mobile cabin during its movement and classifies the dynamic radio frequency data.

[0054] S1 includes:

[0055] S11. Install the monitoring radio frequency identification device at the designated location in the blood container that needs to be monitored, install the triaxial accelerometer on the load-bearing beam of the container and the blood bag suspension bracket, collect the linear acceleration and angular acceleration during the movement of the blood container, integrate the radio frequency signal analyzer and the reader, and collect the phase, power and tag response frequency of the signal.

[0056] S12. The curve of the three-axis acceleration data changing with time during the movement of the blood container is obtained and stored in the first storage module. At the same time, the curve of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood container is stored in the second storage module. Simultaneously, the curve of the resonant frequency deviation of the blood bag tag response changing with time during the movement of the blood container is obtained and stored in the third storage module.

[0057] S2. Import the obtained first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient;

[0058] The motion-induced perturbation model in S2 includes:

[0059] S21. Extract the curves of the three-axis acceleration data changing with time during the movement of the blood transport container and the curves of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood transport container, and set them as the first dynamic radio frequency data.

[0060] S22. The extracted first dynamic radio frequency data is imported into the signal instability coefficient calculation formula to determine the signal instability coefficient. The signal instability coefficient calculation formula is as follows:

[0061] ;

[0062] in, The signal instability coefficient, These are the start and end times of the test. For test duration, The magnitude of the combined acceleration vector of the mobile cabin. Let be the received power of the radio frequency signal during time period t. This is the reference received power measured under static conditions; it should be noted that... and The ratio represents the basic attenuation state of the channel. The smaller the ratio, the greater the signal path loss and the more sensitive it is to disturbances. The standard deviation of the radio frequency signal phase during the movement of the blood transport mobile unit over time time t. dt is the set signal phase stability safety threshold, and dt is the integral over time.

[0063] S3. Import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient;

[0064] The blood bag coupling detuning model in S3 includes the following specific steps:

[0065] S31. Extract the three-dimensional acceleration curve of the blood bag suspension point over time and the blood bag tag response resonant frequency deviation curve over time during the movement of the blood container, and set them as the second dynamic radio frequency data.

[0066] S32. The extracted curves of the three-dimensional acceleration of the blood bag suspension point over time and the curve of the blood bag label response resonant frequency deviation over time during the movement of the blood container are imported into the dielectric detuning coefficient calculation formula to determine the dielectric detuning coefficient. The dielectric detuning coefficient calculation formula is as follows:

[0067] ;

[0068] in, The dielectric detuning coefficient; The vector magnitude of the overall swaying acceleration of the blood bag during time interval t;

[0069] It should be noted that, This is used to quantify the overall mechanical excitation intensity applied to blood bags during the movement of the mobile shelter due to actions such as bumps, turns, and sudden braking. The greater the acceleration, the more violent the sloshing of the liquid inside the blood bag, and the stronger the disturbance to the label.

[0070] Let be the resonant frequency offset of the i-th blood bag label during time period t;

[0071] It should be noted that these are direct observations at the radio frequency level, reflecting the degree of detuning of the tag antenna performance due to the aforementioned mechanical and dielectric coupling effects;

[0072] The set resonant frequency offset safety threshold;

[0073] Let be the blood dielectric perturbation factor of the i-th blood bag during time period t.

[0074] It should be noted that, It is a comprehensive characterization parameter. Liquid sloshing causes dynamic changes in the distribution of the equivalent dielectric constant of the blood bag, and may cause physical deformation of the tag, thereby deteriorating the radiation performance of the tag antenna. The degree of this deterioration is determined by... Characterization, exemplarily, in this embodiment, provides a Here is an example of how to obtain it:

[0075] Step 1: The system adopts dual-frequency excitation radio frequency sensing technology, including: the reader operates at the main frequency used for communication, while simultaneously transmitting an extremely low-power auxiliary low-frequency signal for sensing;

[0076] Step two: In the main frequency channel, read the tag's resonant frequency offset. ;

[0077] Step 3: In the auxiliary sensing channel, measure the dielectric loss tangent of the composite medium consisting of the blood bag-tag system. It should be noted that blood, as a complex biological electrolyte solution, is extremely sensitive to mechanical shaking in its dielectric properties (especially dielectric relaxation). Liquid shaking can lead to changes in ion distribution and protein orientation, thereby significantly altering its dielectric loss.

[0078] Step 4: Construct the dielectric fingerprint of all blood bags in the blood transport cabin, including: pre-measuring and storing the reference dielectric loss tangent for each blood bag while the cabin is stationary. and its reference resonant frequency at the main frequency ;

[0079] Step 5: Real-time calculation of blood dielectric perturbation factors, including:

[0080] ;

[0081] It should be noted that, The dielectric instability of blood refers to the shaking of blood bags caused by vehicle bumps and turns, which disrupts the microscopic electrical balance of the blood medium and causes drastic fluctuations in dielectric loss. The dielectric instability of blood measures the relative change of the current dielectric loss of blood relative to its steady state. The tag relative detuning is quantified as the relative shift of the resonant frequency of the tag antenna due to external conditions. In this embodiment, the external conditions are mainly changes in the electromagnetic coupling state of the blood. It should also be noted that the tag relative detuning is strongly nonlinearly positively correlated with the dielectric instability of the blood. That is, the more violent the blood sloshing, the greater the change in its dielectric properties, and thus the stronger the destructive coupling to the performance of the tag antenna.

[0082] S4. The calculated signal instability coefficient and dielectric detuning coefficient are imported into the blood container inventory anomaly judgment strategy to judge blood inventory anomalies.

[0083] S4 includes:

[0084] S41. Extract the signal instability coefficient and dielectric detuning coefficient obtained during the test time;

[0085] S42. Substitute the obtained signal instability coefficient and dielectric detuning coefficient within the test time into the inventory anomaly judgment value calculation formula to determine the inventory anomaly judgment value. The inventory anomaly judgment value calculation formula is as follows: ;

[0086] in, This represents the proportion of signal instability coefficient. The proportion of dielectric detuning coefficient, where Meanwhile, considering the concealment and destructiveness of the blood bag liquid coupling effect, the following settings were made: ;

[0087] S43. Compare the calculated abnormal judgment value with the set abnormal judgment value. If the calculated abnormal judgment value is greater than or equal to the set abnormal judgment value, the blood container inventory behavior is judged to be abnormal and needs to be checked. If the calculated abnormal judgment value is less than the set abnormal judgment value, the blood container inventory behavior is judged to be normal.

[0088] S5. Conduct blood inventory early warning detection during the relocation of the mobile hospital based on the judgment results of abnormal blood inventory.

[0089] S5 includes: transmitting the judgment result to the mobile monitoring center via wireless early warning; the monitoring center immediately notifies the blood mobile hospital management personnel or conducts emergency inventory verification and label repair work at the next site based on the judgment result.

[0090] For example, it should be noted that in this embodiment, a strategy for obtaining the values ​​of signal instability coefficient ratio, dielectric detuning coefficient ratio, and anomaly judgment value is provided. Specifically, dynamic radio frequency data of 3,000 blood mobile cabins under different road conditions (high-speed, curves, bumpy roads) are obtained. Normal cabins and abnormal inventory cabins are classified by 30 experts in the field in combination with the results of high-frequency manual inventory. The dynamic radio frequency data is substituted into the anomaly judgment value calculation formula to judge the anomaly judgment value. The calculated anomaly judgment value and classification results are imported into fitting software, and the optimal values ​​of signal instability coefficient ratio, dielectric detuning coefficient ratio, and anomaly judgment value that meet the judgment accuracy are output.

[0091] Here are some common existing methods used to check blood inventory:

[0092] 1. Static fixed-point scanning: When the mobile hospital is docked, batch scanning is performed using fixed RFID readers, which cannot reflect the real-time status of the blood mobile hospital during its movement.

[0093] 2. Periodic manual inventory: Relying on personnel to manually count at the site is inefficient and cannot detect abnormalities that occur during the movement of the blood mobile unit;

[0094] 3. Basic modular cabin movement detection: It only monitors whether the modular cabin is moving, and cannot distinguish the specific impact of normal movement and abnormal bumps and turns on the radio frequency system;

[0095] 4. Single-parameter RFID monitoring: It only monitors the tag reading success rate and cannot diagnose whether the reading failure is caused by signal obstruction, multipath interference or tag detuning.

[0096] In this embodiment, it is worth noting that its advantages over existing technologies are as follows: By constructing a motion-induced disturbance model and a blood bag coupling detuning model, this embodiment combines for the first time the macroscopic motion of the blood container with the microscopic electromagnetic property changes of the blood bag liquid, thus performing dual modeling of RFID performance in mobile environments. Specifically, it introduces parameters strongly correlated with blood characteristics, such as blood bag shaking acceleration, blood dielectric disturbance factor, and tag resonant frequency offset, accurately quantifying dielectric detuning problems that are undetectable by traditional methods. This method can effectively diagnose inventory reading anomalies caused by vehicle bumps and turns without stopping the vehicle or illegally increasing RF power, and distinguish whether the problem stems from signal propagation path deterioration or tag performance degradation, thereby providing a basis for precise intervention and greatly improving the reliability and safety of blood container management in real mobile environments.

[0097] Example 2:

[0098] like Figure 2 As shown, the blood mobile hospital management system based on radio frequency identification technology in this embodiment of the invention, such as Figure 2As shown, it includes the following modules:

[0099] Data acquisition module, motion disturbance analysis module, blood bag coupling mismatch analysis module, inventory anomaly comprehensive judgment module, and mobile cabin anomaly early warning module;

[0100] The data acquisition module is used to install the monitoring radio frequency identification device at the designated location in the blood transport cabin that needs to be monitored. The radio frequency identification device collects dynamic radio frequency data from the blood transport cabin and classifies the dynamic radio frequency data.

[0101] The motion disturbance analysis module is used to import the first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient.

[0102] The blood bag coupling detuning analysis module is used to import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient.

[0103] The inventory anomaly comprehensive judgment module is used to import the calculated signal instability coefficient and dielectric detuning coefficient into the inventory anomaly judgment strategy to judge blood inventory anomalies.

[0104] The mobile cabin anomaly early warning module is used to detect blood inventory anomalies during the mobile cabin relocation process based on the judgment results of blood inventory anomalies.

[0105] For example, in this embodiment, the mobile cabin anomaly early warning module includes multi-level early warning units, specifically including:

[0106] Level 1 Early Warning Unit (i.e., Observation Level): When the abnormal judgment value approaches the threshold, a notice is sent to the monitoring center, suggesting that it pay closer attention;

[0107] Level 2 early warning unit (i.e., handling level): When the abnormal judgment value exceeds the threshold, an immediate handling instruction is sent to the blood mobile hospital management personnel, requiring verification at the next site;

[0108] Level 3 early warning unit (i.e. emergency level): When the abnormal judgment value significantly exceeds the threshold and continues to deteriorate, an emergency alarm is sent to the dispatch center, suggesting a change of movement route or activation of emergency response.

[0109] Example 3:

[0110] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0111] The processor executes the aforementioned blood mobile hospital management method based on radio frequency identification technology by calling the computer program stored in the memory.

[0112] The electronic device can vary considerably depending on its configuration or performance. It may include one or more Central Processing Units (CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the blood transport facility management method based on radio frequency identification (RFID) technology provided in the above-described embodiment. The electronic device may also include other components for implementing its functions; for example, it may have wired or wireless network interfaces and input / output interfaces for data input and output. Further details are omitted in this embodiment.

[0113] Example 4:

[0114] This embodiment proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored.

[0115] When the computer program runs on the computer device, it causes the computer device to execute the aforementioned blood mobile cabin management method based on radio frequency identification technology.

[0116] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices.

[0117] It should be understood that, in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0118] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0119] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0120] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only one method, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0121] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0122] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0123] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0124] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A blood transport mobile hospital management method based on radio frequency identification (RFID) technology, characterized in that, The method includes: S1. Install the monitoring radio frequency identification device at the location that needs to be monitored in the blood mobile cabin. The radio frequency identification device collects dynamic radio frequency data of the blood mobile cabin during its movement and classifies the dynamic radio frequency data. S2. Import the obtained first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient; The motion-induced perturbation model in S2 includes: S21. Extract the curves of the three-axis acceleration data changing with time during the movement of the blood transport container and the curves of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood transport container, and set them as the first dynamic radio frequency data. S22. The extracted first dynamic radio frequency data is imported into the signal instability coefficient calculation formula to determine the signal instability coefficient. The signal instability coefficient calculation formula is as follows: ； in, The signal instability coefficient, These are the start and end times of the test. For test duration, The magnitude of the combined acceleration vector of the mobile cabin. Let be the received power of the radio frequency signal during time period t. This is the reference received power measured under static conditions; The standard deviation of the radio frequency signal phase during the movement of the blood transport mobile unit over time time t. The set signal phase stability safety threshold, where dt is the integral over time; S3. Import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient; The blood bag coupling detuning model in S3 includes the following specific steps: S31. Extract the three-dimensional acceleration curve of the blood bag suspension point over time and the blood bag tag response resonant frequency deviation curve over time during the movement of the blood container, and set them as the second dynamic radio frequency data. S32. The extracted curves of the three-dimensional acceleration of the blood bag suspension point over time and the curve of the blood bag label response resonant frequency deviation over time during the movement of the blood container are imported into the dielectric detuning coefficient calculation formula to determine the dielectric detuning coefficient. The dielectric detuning coefficient calculation formula is as follows: ； in, The dielectric detuning coefficient; The vector magnitude of the overall swaying acceleration of the blood bag during time interval t; Let be the resonant frequency offset of the i-th blood bag label during time period t; The set resonant frequency offset safety threshold; Let be the blood dielectric perturbation factor of the i-th blood bag during time period t; S4. The calculated signal instability coefficient and dielectric detuning coefficient are imported into the blood container inventory anomaly judgment strategy to judge blood inventory anomalies. S5. Conduct blood inventory early warning detection during the relocation of the mobile hospital based on the judgment results of abnormal blood inventory.

2. The blood transport facility management method based on radio frequency identification technology according to claim 1, characterized in that, S1 includes: S11. Install the monitoring radio frequency identification device at the designated location in the blood container that needs to be monitored, install the triaxial accelerometer on the load-bearing beam of the container and the blood bag suspension bracket, collect the linear acceleration and angular acceleration during the movement of the blood container, integrate the radio frequency signal analyzer and the reader, and collect the phase, power and tag response frequency of the signal. S12. The curve of the three-axis acceleration data changing with time during the movement of the blood container is stored in the first storage module. At the same time, the curve of the phase fluctuation intensity of the radio frequency signal changing with time during the movement of the blood container is stored in the second storage module. Meanwhile, the curve of the resonant frequency deviation of the blood bag tag response changing with time during the movement of the blood container is stored in the third storage module.

3. The blood mobile hospital management method based on radio frequency identification technology according to claim 2, characterized in that, S4 include: S41. Extract the signal instability coefficient and dielectric detuning coefficient obtained during the test time; S42. Substitute the obtained signal instability coefficient and dielectric detuning coefficient within the test time into the inventory anomaly judgment value calculation formula to determine the inventory anomaly judgment value. The inventory anomaly judgment value calculation formula is as follows: ; in, This represents the proportion of the signal instability coefficient. The proportion of dielectric detuning coefficient, where Meanwhile, considering the concealment and destructiveness of the blood bag liquid coupling effect, the following settings were made: ; S43. Compare the calculated abnormal judgment value with the set abnormal judgment value. If the calculated abnormal judgment value is greater than or equal to the set abnormal judgment value, the blood container inventory behavior is judged to be abnormal and needs to be checked. If the calculated abnormal judgment value is less than the set abnormal judgment value, the blood container inventory behavior is judged to be normal.

4. The blood transport facility management method based on radio frequency identification technology according to claim 3, characterized in that, S5 includes: transmitting the judgment result to the mobile monitoring center via wireless early warning; the monitoring center immediately notifies the blood mobile hospital management personnel or conducts emergency inventory verification and label repair work at the next site based on the judgment result.

5. A blood mobile hospital management system based on radio frequency identification (RFID) technology, used to implement the blood mobile hospital management method based on RFID technology as described in any one of claims 1-4, characterized in that, The system includes the following modules: Data acquisition module, motion disturbance analysis module, blood bag coupling mismatch analysis module, inventory anomaly comprehensive judgment module, and mobile cabin anomaly early warning module; The data acquisition module is used to install the monitoring radio frequency identification device at the designated location in the blood transport cabin that needs to be monitored. The radio frequency identification device collects dynamic radio frequency data from the blood transport cabin and classifies the dynamic radio frequency data. The motion disturbance analysis module is used to import the first dynamic radio frequency data of the blood container into the motion disturbance model to determine the signal instability coefficient. The blood bag coupling detuning analysis module is used to import the acquired second dynamic radio frequency data of the blood container into the blood bag coupling detuning model to determine the dielectric detuning coefficient. The inventory anomaly comprehensive judgment module is used to import the calculated signal instability coefficient and dielectric detuning coefficient into the inventory anomaly judgment strategy to judge blood inventory anomalies. The mobile cabin anomaly early warning module is used to detect and warn of blood inventory abnormalities during the movement of the mobile cabin based on the judgment results of blood inventory abnormalities.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the blood mobile cabin management method based on radio frequency identification technology as described in any one of claims 1-4.

7. An electronic device, characterized in that, include: Memory, used to store instructions; A processor is configured to execute the instructions, causing the device to perform operations that implement the blood mobile hospital management method based on radio frequency identification technology as described in any one of claims 1-4.

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