An intelligent storage and retrieval system for blood

Abstract

The present invention discloses an intelligent storage-in and -out system for blood, which specifically relates to the technical field of blood storage management, and is used to solve the problem of insufficient early warning in the existing evaluation of the impact of ambient light on the blood storage-in and -out process; through the ambient light analysis module, the system can evaluate the excitation risk of photosensitive components under a specific spectrum; the energy density analysis module identifies the potential impact of locally enhanced energy wavelengths on blood through a multi-fractal analysis method; the comprehensive execution analysis module makes a comprehensive judgment on the photosensitivity risk and the impact of local energy wavelengths; the label reading monitoring module ensures the accuracy of label information reading during the blood storage process; the spectrum similarity evaluation module compares the similarity of the current ambient spectrum with the historical harmful spectrum through a dynamic time bending algorithm, and evaluates the risk of blood storage-in and -out in real time, thereby realizing comprehensive monitoring and intelligent management of the blood storage-in and -out process and ensuring the safety of blood.

Description

Technical Field

[0001] The present invention relates to the technical field of blood storage management, and more specifically, to an intelligent storage and warehousing system for blood. Background Art

[0002] The safe storage and efficient in-and-out management of blood are extremely important links in medical institutions, and are crucial to ensuring the quality of clinical blood transfusion and the safety of patients. Blood needs to go through a strict storage and management process before clinical use to maintain its activity and biological functions. In order to ensure that the blood maintains appropriate environmental conditions such as temperature and humidity during storage, medical institutions usually use a series of equipment to strictly control the environment of blood. During the storage and in-and-out process of blood, lighting equipment is usually required to meet operational requirements.

[0003] However, existing technologies do not provide sufficient early warning for the assessment of the impact of ambient light and cannot ensure the safety of the blood storage process. The specific wavelengths of light emitted by lighting equipment may cause physical or chemical changes in photosensitive components in the blood, thereby affecting the function and safety of the blood, possibly leading to a decline in blood quality and increasing the risk of clinical blood transfusions.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent storage and retrieval system for blood to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent storage and warehousing system for blood, comprising an environmental illumination analysis module, an energy density analysis module, a comprehensive execution analysis module, a label reading monitoring module and a spectrum similarity evaluation module;

[0008] The ambient light analysis module is used to evaluate the potential risk of photosensitive components being excited under a specific spectrum by analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood before blood is stored in and out of the blood bank;

[0009] The energy density analysis module is used to analyze the energy density fluctuation of the irradiation spectrum by using the multi-fractal analysis method before the blood is stored and discharged, and to identify the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules of the blood;

[0010] A comprehensive execution analysis module is used to comprehensively analyze the potential risk of photosensitive components being excited under a specific spectrum and the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood, and determine whether blood can be entered or exited from the storage;

[0011] The label reading monitoring module is used to monitor whether the deformation of the blood bag due to pressure changes during storage will affect the reading of label information when the blood is in and out of the warehouse;

[0012] The spectrum similarity assessment module is used to compare the current environmental spectrum with the historical harmful spectrum pattern by using a dynamic time bending algorithm when the tag reading information is not affected, evaluate the similarity between the current spectrum and the known harmful spectrum, and judge the risk of real-time blood in and out of the warehouse;

[0013] Among them, by analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood, the potential risk of photosensitive components being excited under a specific spectrum is evaluated, specifically:

[0014] Calculate the probability of state transition: ;in, Indicates that the photosensitive molecule changes from an energy state Transfer to energy state The probability of and They represent the energy of the photosensitive molecules in different energy states. is the Boltzmann constant, Indicates the ambient temperature of the system, is the allocation function of the system;

[0015] Calculate the overall firing probability: ;in, represents the overall average excitation probability; In each simulation, the photosensitive molecule changes from state To status The transition probability, represents the total number of simulations, is the number of simulations;

[0016] Calculate the energy transfer rate: ;in, Indicates that the photosensitive molecule changes from state Transfer to state The energy transfer rate, is the reduced Planck constant, Indicates that the photosensitive molecule is in the state and The interaction Hamiltonian between Indicates energy status The state density of

[0017] Based on the overall excitation probability and energy transfer rate, the total risk value of the photosensitive molecule is calculated.

[0018] In a preferred embodiment, the total risk value of the photosensitive molecule is expressed as: ;in, represents the total risk value of photosensitive molecules, Indicates that the photosensitive molecule is in an energy state The average excitation probability under Indicates that the photosensitive molecule changes from state To status The energy transfer rate, represents the total number of energy states, The number of the energy state.

[0019] In a preferred embodiment, the energy density fluctuation of the irradiation spectrum is analyzed by using a multifractal analysis method to identify the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood, specifically:

[0020] Acquire spectral data in the blood bank environment through a spectral acquisition device; pre-process the spectral data in the blood bank environment;

[0021] The fractal dimension of spectral data is calculated by multifractal method, and the calculation formula is: ;in, represents the fractal dimension of the spectral data, is the fractal index, Indicated in scale Next The probability distribution of an interval, is the partition scale;

[0022] Evaluate the local enhanced energy density: ;in, Indicates wavelength The local enhanced energy density at represents the spectral energy density after filtering;

[0023] Calculate the spectral overlap: ;in, is the spectral overlap ratio, represents the absorption spectrum of the photosensitive molecule, represents the energy density at the local enhancement wavelength, and are the lower and upper limits of the wavelength range of the absorption spectrum respectively.

[0024] In a preferred embodiment, a comprehensive analysis is performed on the potential risk of photosensitive components being excited under a specific spectrum and the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood to determine whether blood storage and outbound operations can be performed, specifically:

[0025] The total risk value and spectral overlap rate of the photosensitive molecules are normalized; the total risk value and spectral overlap rate of the normalized photosensitive molecules are respectively assigned weight coefficients, and the photosensitivity hidden danger coefficient for storage is calculated;

[0026] Compare the photosensitivity hazard coefficient of inbound and outbound storage with its preset safety threshold For comparison:

[0027] when , it is determined that it is not recommended to perform blood storage and outbound operations;

[0028] when , then it is determined that blood storage and out-of-warehouse operations can be performed.

[0029] In a preferred embodiment, when blood is in and out of the storage, monitoring whether the deformation of the blood bag due to pressure changes during storage will affect the reading of the label information specifically includes:

[0030] Real-time monitoring of internal and external pressure changes of blood bags during storage and acquisition of pressure data;

[0031] Use deformation detection algorithm to analyze the data of pressure sensor, predict the deformation of blood bag caused by pressure change, and generate deformation estimation result;

[0032] Read and record the label information of the blood bag;

[0033] The deformation estimation result is compared with the label reading data to determine whether the blood bag deformation affects the reading accuracy of the label information.

[0034] In a preferred embodiment, when the tag reading information is not affected, the current environmental spectrum is compared with the historical harmful spectrum mode by using a dynamic time warping algorithm to evaluate the similarity between the current spectrum and the known harmful spectrum, and to determine the risk of real-time blood storage. Specifically,

[0035] Invoke harmful spectral patterns known to affect photosensitive components of blood;

[0036] The dynamic time warping algorithm is used to compare the current environmental spectrum with the historical harmful spectrum and evaluate the similarity between the two, which is performed by the following formula: ;in, To show the real-time spectral similarity of incoming and outgoing data, Indicated in wavelength and The spectral energy difference at is the data length of the current spectrum and the historical spectrum, Indicates the historical harmful spectrum at wavelength The energy density at Indicates wavelength The spectral energy density at and All are wavelength indexed;

[0037] The real-time spectral similarity between incoming and outgoing data and the preset threshold For comparison:

[0038] when , it is determined that it is not recommended to continue the blood storage and outflow operations;

[0039] when , it is determined that blood storage and out-of-pocket operations can be carried out safely.

[0040] The technical effects and advantages of the intelligent storage and retrieval system for blood of the present invention are as follows:

[0041] 1. The intelligent blood storage and access system realizes all-round monitoring and risk assessment of blood in and out of the storage process by integrating modules such as ambient light analysis, energy density analysis, comprehensive execution analysis, label reading monitoring and spectral similarity evaluation. Before the blood is in and out of the storage, the ambient light analysis module can analyze the energy exchange process between photons in ambient light and blood photosensitive molecules, evaluate the potential risk of photosensitive components being excited under a specific spectrum, and avoid the impact of light of a specific wavelength on blood quality. The energy density analysis module uses a multi-fractal analysis method to deeply analyze the energy density fluctuations of the irradiation spectrum, identify the locally enhanced energy wavelengths in the environment, and predict the potential impact of blood photosensitive molecules. This multi-level illumination analysis ensures the safety of blood in and out of the storage process and reduces the risk of changes in blood function caused by illumination.

[0042] 2. The comprehensive execution analysis module comprehensively evaluates the excitation risk of photosensitive components and the influence of locally enhanced energy wavelengths in the environment to accurately determine whether blood storage operations can be safely performed, thereby improving the system's decision-making ability and reliability. The label reading monitoring module monitors the pressure changes and deformation of blood bags during storage in real time to ensure accurate reading of label information, avoid information reading errors caused by blood bag deformation, and ensure the accuracy of blood management. The spectral similarity assessment module uses a dynamic time bending algorithm to compare the current environmental spectrum with historical harmful spectrum patterns, and evaluates the similarity between the current spectrum and known harmful spectra in real time, providing an early warning mechanism to prevent potential risks. Overall, the system improves the intelligence and safety of blood storage management, ensures the function and quality of blood, reduces the risk of clinical blood transfusion, and provides reliable technical support for medical institutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The figure is a schematic diagram of the structure of an intelligent storage and retrieval system for blood according to the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0045] Figure 1 A structural schematic diagram of an intelligent storage-in and storage-out system for blood of the present invention is given, which includes an ambient light analysis module, an energy density analysis module, a comprehensive execution analysis module, a label reading monitoring module and a spectral similarity evaluation module.

[0046] The ambient light analysis module is used to evaluate the potential risk of photosensitive components being excited under a specific spectrum by analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood before blood is stored.

[0047] The energy density analysis module is used to analyze the energy density fluctuation of the irradiation spectrum by using the multifractal analysis method before the blood is put into or taken out of the storage, so as to identify the potential influence of the locally enhanced energy wavelength in the environment on the photosensitive molecules of the blood.

[0048] The comprehensive execution analysis module is used to comprehensively analyze the potential risk of photosensitive components being excited under a specific spectrum and the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood, and determine whether blood storage and outbound operations can be executed.

[0049] The label reading monitoring module is used to monitor whether the deformation of the blood bag due to pressure changes during storage will affect the reading of label information when the blood is in and out of the warehouse.

[0050] The spectral similarity assessment module is used to compare the current environmental spectrum with the historical harmful spectrum pattern by adopting a dynamic time bending algorithm when the tag reading information is not affected, evaluate the similarity between the current spectrum and the known harmful spectrum, and judge the real-time risk of blood entering and leaving the warehouse.

[0051] In the blood storage system, photons of specific wavelengths in ambient light interact with photosensitive molecules in the blood, which may lead to energy transfer and excitation of photosensitive molecules. This excitation can affect the function and safety of blood.

[0052] By analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood, the potential risk of photosensitive components being excited under a specific spectrum is evaluated, specifically:

[0053] A simulation model based on the quantum Monte Carlo method is established to simulate the energy exchange process between photons and photosensitive molecules. The model simulates energy exchange by randomly selecting the wavelength of photons and the energy state of photosensitive molecules. The state transition process of photosensitive molecules can be described as the probability of their transition from one energy state to another. The probability of this state transition is related to the ambient temperature and the energy difference of the photosensitive molecules.

[0054] The probability of state transition is calculated by the following formula: ;in, Indicates that the photosensitive molecule changes from an energy state Transfer to energy state probability; and They represent the energy of the photosensitive molecule in different energy states, in electron volts (eV); is the Boltzmann constant; Indicates the ambient temperature of the system in Kelvin (K); is the distribution function of the system, which is used to normalize the probability distribution of the entire system.

[0055] Photosensitive molecules change from energy states Transfer to energy state The probability describes the possibility of a photosensitive molecule transitioning from one energy state to another. The higher the temperature, the greater the probability of the molecule transitioning between different states.

[0056] Monte Carlo simulation obtains the number of successful energy exchanges by randomly sampling the energy of photons of different wavelengths and the state of photosensitive molecules. The calculation formula for the overall excitation probability is: ;in, represents the overall average excitation probability; In each simulation, the photosensitive molecule changes from state To status The transition probability of represents the total number of simulations, is the number of simulations.

[0057] By randomly sampling photons of different wavelengths, the probability distribution of energy exchange between photosensitive molecules and photons is obtained. The more simulation times, the closer the result is to the actual energy exchange probability.

[0058] The overall risk of photosensitive molecules is assessed by combining the energy transfer rate. The energy transfer rate indicates the rate at which photosensitive molecules transfer between different energy states. The higher the rate, the more frequent the state changes of the photosensitive molecules, and the greater the risk of the system.

[0059] The energy transfer rate is calculated as: ;in, Indicates that the photosensitive molecule changes from state Transfer to state The energy transfer rate is the reduced Planck constant; Indicates that the photosensitive molecules are in the state and The interaction Hamiltonian between Indicates energy status The state density of .

[0060] The stability of photosensitive molecules in different energy states is evaluated based on the transfer rate. The higher the rate, the more unstable the system is and the greater the risk.

[0061] The total risk value of photosensitive molecules is calculated as follows: ;in, represents the total risk value of photosensitive molecules; Indicates that the photosensitive molecule is in an energy state The average excitation probability under ; Indicates that the photosensitive molecule changes from state To status The energy transfer rate Represents the total number of energy states; The number of the energy state.

[0062] This formula combines the excitation probability and energy transfer rate of photosensitive molecules to derive the total risk value of photosensitive molecules.

[0063] The greater the total risk value of the photosensitive molecules, the higher the potential risk of the photosensitive components being excited under a specific spectrum. The higher the probability of excitation, the greater the possibility that the photosensitive molecules are excited by photons under a specific spectrum. The higher the energy transfer rate, the faster the frequency of the photosensitive molecules changing from one energy state to another, that is, the more unstable the system. The combination of these two reflects the degree of excitation and instability of the photosensitive components of the blood by ambient light, indicating that the photosensitive molecules in the blood are more susceptible to the influence of ambient light.

[0064] By analyzing the energy density fluctuations of the irradiation spectrum using multifractal analysis, the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood is identified, specifically:

[0065] Under certain irradiation conditions, the energy density distribution in the environment may produce locally enhanced wavelength regions that may not be identified in routine analysis but have potential effects on photosensitive molecules in the blood.

[0066] The spectral data in the blood bank environment is obtained through the spectral acquisition device. The acquisition device detects the energy of photons of different wavelengths and generates corresponding energy density distribution maps. The goal of this step is to record the change of photon energy with wavelength and provide raw data for subsequent energy fluctuation analysis.

[0067] The spectral data are described by the following formula: ;in, Indicates wavelength The spectral energy density at , in watts per square meter per nanometer (W / m² / nm); Indicates Wavelength, in nanometers (nm); Indicates Photons in wavelength The energy at , in joules (J); is at wavelength The number of photons detected at .

[0068] Spectral data may be affected by various interference factors, such as external noise and equipment noise. Therefore, before subsequent analysis, the collected raw data must be preprocessed to remove noise and other interference to ensure the accuracy and reliability of the data.

[0069] The preprocessing process can be achieved by the following filtering formula: ;in, represents the spectral energy density after filtering; Indicated in wavelength The noise energy at , also in watts per square meter per nanometer (W / m² / nm).

[0070] The filtering process eliminates the influence of external interference on the data by subtracting noise energy, ensuring the purity of the spectral data and providing a reliable basis for subsequent multifractal analysis.

[0071] The preprocessed spectral data are processed using multifractal analysis to capture the local fluctuations in the energy density in the spectrum. Multifractal analysis is a statistical method that can characterize local inhomogeneities in complex systems. It reveals the multiscale characteristics of the system by calculating the changes in data at different scales.

[0072] The fractal dimension of spectral data is calculated by multifractal method to describe the energy fluctuation of the spectrum at different wavelengths. The calculation formula of fractal dimension is: ;in, Represents the fractal dimension of spectral data; It is a fractal index, which is used to measure fluctuations at different scales; Indicated in scale Next The probability distribution of an interval; is the partition scale, which indicates the spatial scale of the analysis.

[0073] By calculating the fractal dimension under different fractal indices, the local fluctuation and inhomogeneity of the spectral energy density can be captured. The fluctuation of the fractal dimension reflects the local enhancement of the energy density of the spectrum at certain specific wavelengths, suggesting that there may be abnormal wavelengths that affect photosensitive molecules.

[0074] By performing multifractal analysis on the spectral data, local enhancements in energy density at certain wavelengths can be identified. These wavelength regions with local enhancements are areas in the spectrum where energy density fluctuates greatly and may have an impact on photosensitive molecules in the blood.

[0075] When identifying the local enhancement wavelength, the following formula is used to evaluate the local enhancement energy density: ;in, Indicates wavelength The energy density is locally enhanced.

[0076] By combining the filtered spectral energy density and fractal dimension, it is possible to accurately identify local enhanced wavelengths in the spectrum. These local enhanced wavelengths represent areas with large fluctuations in energy density in the illumination environment, which may have potential effects on photosensitive molecules.

[0077] The identified local enhanced wavelengths are compared with the absorption spectra of photosensitive molecules in the blood to assess whether these abnormal wavelengths may have an excitation effect on the photosensitive molecules. The absorption spectrum of a photosensitive molecule indicates its sensitivity to photons of different wavelengths, and any local enhanced wavelength that overlaps with the absorption spectrum may affect it.

[0078] The overlap of the absorption spectrum and the local enhancement wavelength can be calculated using the following formula: ;in, is the spectral overlap ratio, which indicates the overlap ratio between the local enhancement wavelength and the absorption spectrum of the photosensitive molecule; Represents the absorption spectrum of photosensitive molecules, the unit is relative absorbance; represents the energy density at the local enhancement wavelength; and are the lower and upper limits of the wavelength range of the absorption spectrum respectively.

[0079] By calculating the overlap rate between the local enhanced wavelength and the absorption spectrum of the photosensitive molecules, it is possible to evaluate whether the locally enhanced energy wavelength may have an excitation effect on the photosensitive molecules in the blood. If the overlap rate is high, it indicates that these locally enhanced wavelengths may pose a threat to the function and safety of the blood; that is, the greater the spectral overlap rate, the greater the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood.

[0080] Comprehensively analyze the potential risk of photosensitive components being excited under specific spectra and the potential impact of locally enhanced energy wavelengths in the environment on blood photosensitive molecules to determine whether blood storage and outbound operations can be performed, specifically:

[0081] The total risk value and spectral overlap rate of photosensitive molecules are normalized. The goal of normalization is to standardize the values ​​of different dimensions to the range of [0,1] so that they can be weighted summed in the same framework.

[0082] The total risk value and spectral overlap rate of the normalized photosensitive molecules are assigned weight coefficients respectively, and the photosensitivity hidden danger coefficient for storage is calculated. The expression is: ;in, is the photosensitivity hazard coefficient for in-and-out storage, and are the total risk value of photosensitive molecules and the weight coefficient of spectral overlap rate, and are greater than 0, is the normalized total risk value of the photosensitive molecules, is the normalized spectral overlap ratio.

[0083] The greater the photosensitivity risk coefficient of blood entering and leaving the warehouse, the higher the potential risk of the current ambient light to the photosensitive molecules in the blood, and the less likely it is that blood can be entered and left the warehouse.

[0084] Set the preset safety threshold It will be used as a criterion to compare the photosensitive hazard coefficient of inbound and outbound storage with its preset safety threshold:

[0085] when , it is determined that it is not recommended to perform blood storage and outbound operations;

[0086] when , then it is determined that blood storage and out-of-warehouse operations can be performed.

[0087] in, It is set based on the actual safety requirements for the photosensitive molecules in the blood on the entry and exit of blood and other actual conditions, which will not be elaborated here.

[0088] When blood is in and out of the warehouse, monitor whether the deformation of the blood bag due to pressure changes during storage will affect the reading of label information, including:

[0089] Real-time monitoring of internal and external pressure changes of blood bags during storage to obtain accurate pressure data:

[0090] During the blood storage process, the storage environment of the blood bag may be affected by external pressure, such as temperature changes, gravity pressure caused by stacking, etc. In order to ensure that the deformation of the blood bag does not affect the reading of the label information, multiple high-precision pressure sensors are installed around and inside the blood bag to monitor the internal and external pressure changes during the storage process of the blood bag in real time.

[0091] Specifically, the pressure sensor detects the pressure exerted on the blood bag under different storage conditions (such as constant temperature or low temperature environment, vertical or horizontal stacking). The accuracy of the pressure sensor can reach tiny pressure changes per square centimeter, thus ensuring that the impact of tiny external environmental changes on the blood bag is captured.

[0092] The deformation detection algorithm is used to analyze the data of the pressure sensor, predict the deformation of the blood bag that may be caused by pressure changes, and generate deformation estimation results:

[0093] Pressure changes may cause blood bags to deform to varying degrees during storage. To assess whether deformation will affect the reading of blood bag labels, a deformation detection algorithm based on finite element analysis (FEA) can be used. This algorithm simulates the deformation process of blood bags under different pressure conditions to predict the degree of deformation in a specific pressure environment. Specifically, it uses the data provided by the pressure sensor to generate a pressure distribution map of the blood bag. Then, the deformation detection algorithm calculates the possible deformation of each part by simulating the response of the blood bag material under different pressure conditions. The physical properties of the blood bag material, such as elastic modulus, thickness, and pressure tolerance limit, will be fully considered in this calculation, thereby improving the accuracy of deformation prediction.

[0094] The deformation prediction results include the maximum stress points in different areas of the blood bag surface, the deformation amplitude, and the key areas that may affect the reading of label information. The results can be presented in the form of 3D images, which makes it easier for operators to intuitively understand the deformation of the blood bag.

[0095] Read and record the label information of the blood bag to ensure the accuracy of information collection:

[0096] Each blood bag is attached with a unique identification tag, which can be read using RFID (radio frequency identification) technology or barcode technology. In order to ensure that the label information can be accurately read when the blood bag is deformed, the system will collect and record the label information of the blood bag multiple times at different time points.

[0097] A label reading device (such as an RFID reader or a barcode scanner) is arranged in the storage area of ​​the blood bag and can scan the label of the blood bag regularly.

[0098] Compare the deformation estimation result with the label reading data to determine whether the blood bag deformation affects the reading accuracy of the label information:

[0099] The deformation estimation result of the blood bag generated by the deformation detection algorithm is compared with the real-time label reading data to determine whether the deformation of the blood bag has affected the accuracy of reading the label information. If the reading success rate of the label reading device is abnormal under certain pressure conditions, and the deformation detection algorithm predicts that the blood bag has undergone a large deformation in the corresponding area, it will be determined that the deformation of the blood bag may have affected the accurate reading of the label information.

[0100] Analyze whether the key area of ​​deformation estimation overlaps with the reading position of the tag reading device. If the overlapping area happens to be the key position of tag information transmission, it is determined that the deformation may have affected the reading of the tag. By statistically analyzing the changing trend of the tag reading success rate and combining the amplitude and position of the blood bag deformation, an accurate judgment can be made.

[0101] When the tag reading information is not affected, the dynamic time bending algorithm is used to compare the current environmental spectrum with the historical harmful spectrum mode, evaluate the similarity between the current spectrum and the known harmful spectrum, and judge the risk of real-time blood in and out of the warehouse. Specifically:

[0102] Recall harmful spectral patterns known to affect photosensitive blood components. The database contains spectral features known to cause chemical reactions in photosensitive blood components, such as photon energy of certain specific wavelengths resonating with photosensitive molecules in the blood, causing changes in the molecular energy state.

[0103] The dynamic time warping (DTW) algorithm is used to compare the current environmental spectrum with the historical harmful spectrum to evaluate the similarity between the two. The DTW algorithm is a commonly used time series matching algorithm that can effectively compare sequences of different lengths and calculate the shortest distance between two curves by allowing dynamic adjustment of alignment, thereby evaluating their similarity.

[0104] The similarity calculation of the DTW algorithm is performed using the following formula: ;in, To represent the real-time spectral similarity between the incoming and outgoing data, the dynamic time-bending distance between the current environmental spectrum and the historical harmful spectrum is expressed; Indicated in wavelength and The spectral energy difference at is the data length of the current spectrum and the historical spectrum (i.e. the number of wavelengths); Indicates the historical harmful spectrum at wavelength The energy density at Indicates wavelength The spectral energy density at , in watts per square meter per nanometer (W / m² / nm); It represents the wavelength index, which is used to indicate the first wavelength points; Also stands for wavelength index, which is used to represent a wavelength point in the historical harmful spectrum.

[0105] The greater the similarity of real-time spectra in and out of the warehouse, the higher the similarity between the current environmental spectrum and the historical harmful spectrum, which means that the risk of real-time blood in and out of the warehouse is greater. At this time, it is not recommended to perform blood in and out of the warehouse. It is recommended to take timely measures to analyze and adjust the current spectral environment to prevent damage to the photosensitive components of the blood.

[0106] The real-time spectral similarity between incoming and outgoing data and the preset threshold For comparison:

[0107] when , indicating that the current environmental spectrum is highly similar to the historical harmful spectrum, and there is a greater risk. At this time, the current lighting environment may have an adverse effect on the photosensitive components of the blood, and it is determined that it is not recommended to continue the blood storage and outbound operations, and protective measures need to be taken or the environmental spectrum conditions need to be adjusted.

[0108] when , indicating that the current spectrum is less similar to the historical harmful spectrum, the potential impact of the environment on the photosensitive components of blood is small, and the risk is low. At this time, it is determined that blood storage and outbound operations can be carried out safely.

[0109] in, It is a fixed reference value used to measure the safety standard of spectral similarity.

[0110] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0111] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0112] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0113] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0114] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0115] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0117] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0118] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0119] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent storage and retrieval system for blood, characterized in that: It includes an ambient light analysis module, an energy density analysis module, a comprehensive execution analysis module, a tag reading monitoring module, and a spectrum similarity evaluation module; The ambient light analysis module is used to evaluate the potential risk of photosensitive components being excited under a specific spectrum by analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood before blood is stored in and out of the blood bank; The energy density analysis module is used to analyze the energy density fluctuation of the irradiation spectrum by using the multifractal analysis method before the blood is stored in and out of the storage, so as to identify the potential influence of the locally enhanced energy wavelength in the environment on the photosensitive molecules of the blood; A comprehensive execution analysis module is used to comprehensively analyze the potential risk of photosensitive components being excited under a specific spectrum and the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood, and determine whether blood can be entered or exited from the storage; The label reading monitoring module is used to monitor whether the deformation of the blood bag due to pressure changes during storage will affect the reading of label information when the blood is in and out of the warehouse; The spectrum similarity assessment module is used to compare the current environmental spectrum with the historical harmful spectrum pattern by using a dynamic time bending algorithm when the tag reading information is not affected, evaluate the similarity between the current spectrum and the known harmful spectrum, and judge the risk of real-time blood in and out of the warehouse; Among them, by analyzing the energy exchange process between photons in ambient light and photosensitive molecules in blood, the potential risk of photosensitive components being excited under a specific spectrum is evaluated, specifically: Calculate the probability of state transition: ;in, Indicates that the photosensitive molecule changes from an energy state Transfer to energy state The probability of and They represent the energy of the photosensitive molecules in different energy states. is the Boltzmann constant, Indicates the ambient temperature of the system, is the allocation function of the system; Calculate the overall firing probability: ;in, represents the overall average excitation probability; In each simulation, the photosensitive molecule changes from state To status The transition probability, represents the total number of simulations, is the number of simulations; Calculate the energy transfer rate: ;in, Indicates that the photosensitive molecule changes from state Transfer to state The energy transfer rate, is the reduced Planck constant, Indicates that the photosensitive molecule is in the state and The interaction Hamiltonian between Indicates energy status The state density of Based on the overall excitation probability and energy transfer rate, the total risk value of the photosensitive molecule is calculated.

2. The intelligent storage and retrieval system for blood according to claim 1, characterized in that: The total risk value of photosensitive molecules is expressed as: ;in, represents the total risk value of photosensitive molecules, Indicates that the photosensitive molecule is in an energy state The average excitation probability under Indicates that the photosensitive molecule changes from state To status The energy transfer rate, represents the total number of energy states, The number of the energy state.

3. The intelligent storage and retrieval system for blood according to claim 2, characterized in that: By analyzing the energy density fluctuations of the irradiation spectrum using multifractal analysis, the potential impact of the locally enhanced energy wavelength in the environment on the photosensitive molecules in the blood is identified, specifically: Acquire spectral data in the blood bank environment through a spectral acquisition device; pre-process the spectral data in the blood bank environment; The fractal dimension of spectral data is calculated by multifractal method, and the calculation formula is: ;in, represents the fractal dimension of the spectral data, is the fractal index, Indicated in scale Next The probability distribution of an interval, is the partition scale; Evaluate the local enhanced energy density: ;in, Indicates wavelength The local enhanced energy density at represents the spectral energy density after filtering; Calculate the spectral overlap: ;in, is the spectral overlap ratio, represents the absorption spectrum of the photosensitive molecule, represents the energy density at the local enhancement wavelength, and are the lower and upper limits of the wavelength range of the absorption spectrum respectively.

4. The intelligent storage and retrieval system for blood according to claim 3 is characterized in that: Comprehensively analyze the potential risk of photosensitive components being excited under specific spectra and the potential impact of locally enhanced energy wavelengths in the environment on blood photosensitive molecules to determine whether blood storage and outbound operations can be performed, specifically: The total risk value and spectral overlap rate of the photosensitive molecules are normalized; the total risk value and spectral overlap rate of the normalized photosensitive molecules are respectively assigned weight coefficients, and the photosensitivity hidden danger coefficient for storage is calculated; Compare the photosensitivity hazard coefficient of inbound and outbound storage with its preset safety threshold For comparison: when , it is determined that it is not recommended to perform blood storage and out-of-stock operations; when , then it is determined that blood storage and out-of-warehouse operations can be performed.

5. The intelligent storage and retrieval system for blood according to claim 4, characterized in that: When blood is in and out of the warehouse, monitor whether the deformation of the blood bag due to pressure changes during storage will affect the reading of label information, including: Real-time monitoring of internal and external pressure changes of blood bags during storage and acquisition of pressure data; Use deformation detection algorithm to analyze the data of pressure sensor, predict the deformation of blood bag caused by pressure change, and generate deformation estimation result; Read and record the label information of the blood bag; The deformation estimation result is compared with the label reading data to determine whether the blood bag deformation affects the reading accuracy of the label information.

6. The intelligent storage and retrieval system for blood according to claim 5, characterized in that: When the tag reading information is not affected, the dynamic time bending algorithm is used to compare the current environmental spectrum with the historical harmful spectrum mode, evaluate the similarity between the current spectrum and the known harmful spectrum, and judge the risk of real-time blood in and out of the warehouse. Specifically: Invoke harmful spectral patterns known to affect photosensitive components of blood; The dynamic time warping algorithm is used to compare the current environmental spectrum with the historical harmful spectrum and evaluate the similarity between the two, which is performed by the following formula: ;in, To show the real-time spectral similarity of incoming and outgoing data, Indicated in wavelength and The spectral energy difference at is the data length of the current spectrum and the historical spectrum, Indicates the historical harmful spectrum at wavelength The energy density at Indicates wavelength The spectral energy density at and All are wavelength indexed; The real-time spectral similarity between incoming and outgoing data and the preset threshold For comparison: when , it is determined that it is not recommended to continue the blood storage and outflow operations; when , it is determined that blood storage and out-of-pocket operations can be carried out safely.

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