Blood warehouse-in and warehouse-out management method based on Internet of Things

Abstract

The invention discloses a blood warehouse-in and warehouse-out management method based on the Internet of Things, and belongs to the technical field of the Internet of Things, and the method specifically comprises the steps: constructing a three-dimensional temperature control thermodynamic diagram of a blood refrigeration house, and dividing each region into a high-fluctuation region and a low-fluctuation region according to a temperature change rate threshold value; after a transportation instruction is received, according to the blood activity attenuation curve screening area and the set transportation duration, a spiral progressive path of carrier transportation is generated; a speed-temperature linkage control model is established in the transportation process, the carrier transportation speed in a low-fluctuation area is in negative correlation with the temperature change rate of each area, and staged speed control is executed when the carrier enters a high-fluctuation area; calculating the accumulative exposure of the blood transportation path in real time, when the accumulative exposure reaches an activity tolerance threshold value, controlling the carrier to slow down to a set stop point for residence, planning a detouring path based on the updated thermodynamic diagram, and updating a speed curve; according to the invention, excessive attenuation of blood activity is avoided while warehouse-in and warehouse-out efficiency is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a blood storage and out-of-warehouse management method based on Internet of Things. Background Art

[0002] In the modern medical system, blood is an extremely critical medical resource, and strict control of its quality is directly related to the effectiveness of medical treatment. The storage and transportation environment of blood has a significant impact on its activity and quality, especially the temperature factor. Therefore, building an efficient and accurate blood in and out management system to ensure that blood is in a suitable environment throughout the entire process has become an important issue that needs to be urgently addressed in the medical industry. The rise of Internet of Things technology has made it possible to achieve refined blood management. Through real-time monitoring and intelligent regulation, it is expected to improve the quality and efficiency of blood management.

[0003] At present, in the blood storage and warehousing management process, automated equipment such as robotic arms or transport vehicles undertake key transportation tasks. In terms of path planning, traditional practices mostly use the shortest path algorithm, among which the Dijkstra algorithm is widely used. This type of algorithm aims to find the route with the shortest physical distance between two points. For example, in a warehouse environment, it usually gives priority to seemingly direct paths such as straight lines through the center of the warehouse. However, the actual environment of the warehouse is complex. Due to the limitations of the structural design and the unreasonable layout of the equipment, there are some areas in the warehouse, such as near the vents, the edge of the refrigeration equipment, or the parts with poor airflow affected by the building structure. These areas become weak temperature control areas.

[0004] When automated equipment performs blood storage and retrieval tasks according to the traditional shortest path algorithm, it will inevitably pass through these temperature-controlled weak areas. The activity of blood will be significantly affected when passing through the temperature-controlled weak areas due to large temperature fluctuations. This not only reduces the quality of blood and increases medical risks, but may also cause blood to be scrapped and waste medical resources. The traditional blood storage and retrieval management path planning method has obvious deficiencies in ensuring blood activity and quality because it fails to fully consider temperature factors. Summary of the invention

[0005] The purpose of the present invention is to provide a blood storage management method based on the Internet of Things to solve the following technical problems:

[0006] When automated equipment performs blood storage and retrieval tasks according to the traditional shortest path algorithm, it will pass through areas with weak temperature control. Since the temperature in these areas fluctuates greatly, the activity of the blood will be significantly affected when passing through them.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A blood storage management method based on the Internet of Things includes the following steps:

[0009] Construct a three-dimensional temperature-controlled thermal map of the blood cold storage, mark the temperature fluctuation intensity and allowable exposure duration of each area of the cold storage, and divide each area into high-fluctuation areas and low-fluctuation areas according to the temperature change rate threshold;

[0010] When a transportation instruction is received, obtain the activity decay curve of the target blood changing with time at different temperatures, screen the area and set the transportation duration according to the activity decay curve, and generate a spiral progressive path for vehicle transportation within the screened area. The curvature radius of the path is negatively correlated with the temperature fluctuation intensity of the area passed through, and the distance between the turning points of the path is positively correlated with the temperature fluctuation intensity;

[0011] Establish a speed-temperature linkage control model during transportation. The vehicle transportation speed in the low-fluctuation area is negatively correlated with the temperature change rate of each area, and when entering the high-fluctuation area, perform staged speed control;

[0012] Calculate the cumulative exposure amount of the blood transportation path in real time. When the activity tolerance threshold is reached, control the vehicle to decelerate to the set stopping point and stay. During the stay period, update the thermal map, plan a detour path based on the updated thermal map and update the speed curve.

[0013] As a further solution of the present invention: The process of obtaining the activity decay curve and transportation parameters is as follows:

[0014] When the blood is put into storage, collect the red blood cell concentration, platelet activity index and coagulation factor stability in the blood bag at preset time intervals through a multispectral sensor to form a time series data set; perform polynomial fitting and exponential decay analysis on the time series data, and extract key decay parameters, including the activity half-life, critical inactivation temperature threshold and vibration sensitivity coefficient;

[0015] Divide the cold storage into three-dimensional grid cells, calculate the matching degree score between the environmental parameters and activity decay parameters of each cell, and mark the area with a matching degree score higher than the set threshold as the screened area; calculate the average decay rate by weighting the real-time environmental parameters of the screened area, set the activity threshold, calculate the duration to reach the activity threshold according to the activity half-life and average decay rate, and obtain the transportation duration based on the set proportional value.

[0016] As a further solution of the present invention: The generation process of the spiral progressive path is as follows:

[0017] Establish a polar coordinate system with the transportation starting point as the pole, convert the destination coordinates into the target polar angle, and the initial path unfolds along a spiral. The unfolding angle of the spiral is adjusted according to the real-time temperature fluctuation data; calculate the temperature fluctuation integral value at each set path decision point. When the integral value exceeds the preset second threshold, adjust the rotation angle increment of the path through the vibration sensitivity coefficient;

[0018] In low-fluctuation areas, the turning point density is set based on the path curvature change gradient. The greater the curvature change gradient, the higher the turning point density. In high-fluctuation areas, the turning point interval is extended according to the product of the temperature fluctuation intensity and the path curvature. The path curvature radius is calculated based on the blood tolerance acceleration and the path friction coefficient.

[0019] As a further solution of the present invention: the staged control includes:

[0020] The driving path of the vehicle in the high fluctuation area and the temperature fluctuation intensity distribution in the high fluctuation area are obtained, and the path above the set threshold is marked as the core stage, and the paths before and after the core stage are marked as the initial stage and the disengagement stage respectively. When entering the initial stage, the vehicle speed is reduced to the preset steady speed threshold through multi-stage deceleration control, and the path curvature is increased according to the spatial distribution characteristics of the current temperature fluctuation intensity; in the core stage, the straight path is switched and the steady speed cruise is maintained, and the vehicle's own cold air flow is started to control the temperature of the blood, and the temperature adjustment amplitude of the cold air flow is proportional to the temperature deviation of the current area; in the disengagement stage, the temperature fluctuation intensity trend is detected, and the curvature attenuation rate is synchronized with the temperature fluctuation intensity decrease rate.

[0021] As a further solution of the present invention: the specific process of setting the stop point is:

[0022] Pre-generate set stop points during path planning, and the set stop point selection criteria include being located in a low fluctuation intensity area and having an environmental compensation interface; when the vehicle stops, a transition path including a deceleration arc is generated, and the arc radius is dynamically calculated based on the current vehicle kinetic energy and path curvature; during the stop period, a cold air flow is released through the environmental compensation interface to correct the blood temperature to the storage temperature; after the correction is completed, the path curvature distribution is re-planned based on the updated thermal map, the cumulative exposure of the new path is reset, and the compensation weight coefficient of each area path is set according to the exposure of the passed area.

[0023] As a further solution of the present invention: the calculation method of the cumulative exposure amount is:

[0024] The transport path is dynamically segmented, and the exposure amount of each path is calculated by the peak temperature fluctuation intensity, duration and average attenuation rate of the corresponding interval; sensors are deployed at the turning points of the path to collect actual blood activity parameters and compare them with the predicted attenuation curve, and a dynamic adjustment factor is generated according to the deviation, and the dynamic adjustment factor is proportional to the deviation; the total exposure amount is obtained by accumulating the product of the exposure amount of each segment and the dynamic adjustment factor.

[0025] As a further solution of the present invention: the speed-temperature linkage control model comprises:

[0026] Calculate the reference speed based on the current path curvature radius and the blood tolerance acceleration, where the reference speed is proportional to the square root of the curvature radius;

[0027] Generate a correction amount for the reference speed according to the absolute value of the real-time temperature change rate within the low-fluctuation region. The amplitude of the correction amount is related to the exponential function of the temperature change rate, and limit the final speed within the preset safe speed; when entering the high-fluctuation region, increase the limit of the preset safe speed according to the temperature fluctuation intensity of the high-fluctuation region.

[0028] As a further solution of the present invention: record the path efficiency index of each transportation task, where the index is calculated by the normalized product of the total path length, the actual time taken, and the activity loss amount, and mark the path with an index higher than the set threshold as a high-efficiency path; extract the feature vector set of the high-efficiency path through a convolutional neural network, where the feature vector set includes the path curvature sequence, the speed adjustment frequency, and the environmental response parameters, and perform iterative optimization of the control parameters regularly.

[0029] Advantages of the present invention:

[0030] By constructing a three-dimensional temperature-controlled thermal map and dividing the cold storage into high- and low-fluctuation regions, the present invention can visually present the temperature fluctuation situation and avoid the vehicle selecting weak temperature-controlled areas during transportation. Based on the activity decay curve, select regions and set the transportation duration. The generated spiral progressive path curvature radius is negatively correlated with the temperature fluctuation intensity, and the turning point spacing is positively correlated with it, so that the path planning fully considers the influence of temperature on blood activity. The phased control, the speed-temperature linkage control model, and the real-time calculation and response to the cumulative exposure amount can effectively regulate the vehicle speed, reduce the exposure time and influence degree of blood in the high-fluctuation region. Setting the docking points and related operations can correct the temperature deviation in time and re-plan the path to reduce subsequent risks. It comprehensively protects the activity of blood during the inbound and outbound transportation process, and solves the technical problem that the traditional shortest path algorithm affects the blood activity due to ignoring the temperature factor. Description of the Drawings

[0031] The following further describes the present invention with reference to the drawings.

[0032] Figure 1 is the flow schematic diagram of the present invention. Detailed Embodiments

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0034] Please refer toFigure 1 As shown, the present invention is a blood storage and transportation management method based on the Internet of Things, comprising the following steps:

[0035] Constructing a three-dimensional temperature control thermal map of the blood cold storage is the basic link of the entire management process. With the help of Internet of Things technology, a large number of temperature sensors distributed throughout the cold storage continuously collect real-time temperature data. These data are transmitted to the system background and analyzed and processed through complex algorithms. Based on the analysis results, the temperature fluctuation intensity of each area in the cold storage can be accurately marked, that is, the magnitude of temperature change per unit time. At the same time, through a large number of experiments, scientific researchers have clarified the law of activity change of different types of blood under different temperature environments, and accordingly determined the allowable exposure time of blood in each area. To further distinguish and manage the cold storage areas, according to the pre-set temperature change rate threshold, each area in the cold storage is divided into high-fluctuation areas and low-fluctuation areas. A high-fluctuation area indicates that the temperature in this area changes frequently and significantly, while a low-fluctuation area has relatively stable temperature. The construction of the three-dimensional temperature control thermal map provides intuitive and accurate data support for subsequent transportation route planning and temperature regulation, and helps to identify in advance areas that are not conducive to blood storage or transportation.

[0036] When the system receives a blood transportation instruction, it immediately enters the in-depth analysis process of the target blood characteristics. Through professional blood detection equipment and technologies, the activity decay curve of the target blood over time at different temperatures is obtained. This curve is drawn based on a large amount of experimental data and reflects the trend of blood activity decreasing over time under different temperature conditions. Based on this curve, the system can comprehensively consider the optimal conditions for maintaining blood activity, screen out the area with the least impact on blood activity as the potential transportation route area. At the same time, combined with the blood activity decay speed reflected by the curve, the transportation duration is scientifically and reasonably set to ensure that the blood activity is always within an acceptable range during transportation. Subsequently, within the selected area, the system uses a specially designed algorithm to generate a spiral progressive path for the vehicle transportation. The principle is that the curvature radius of the path is negatively correlated with the temperature fluctuation intensity of the area passed through. This is because in areas with high temperature fluctuation intensity, a smaller curvature radius can make the vehicle driving path smoother, reducing the shaking of the blood caused by operations such as turning and the possible impact on activity; while the distance between the path turning points is positively correlated with the temperature fluctuation intensity. Increasing the turning point distance in areas with large temperature fluctuations can avoid frequent turning of the vehicle, further reducing the interference to blood activity and ensuring the stability of the blood during transportation to the greatest extent.

[0037] During the transportation process, a speed-temperature linkage control model is established. In the low-fluctuation area, the vehicle transportation speed is negatively correlated with the temperature change rate of each area. The principle is that when the regional temperature change rate is low, it means that the temperature in the area is relatively stable. The vehicle can speed up the transportation process by appropriately increasing the driving speed, and it will not have a significant impact on the blood activity; when the temperature change rate increases, the vehicle automatically reduces the speed to better cope with the impact that temperature changes may have on the blood and ensure the stability of blood activity. When the vehicle enters the high-fluctuation area, a staged speed control strategy is implemented. In the initial stage of entering the high-fluctuation area, the vehicle speed is steadily reduced to the preset steady speed threshold through multi-stage deceleration control, so that the vehicle can safely adapt to the complex temperature environment in the high-fluctuation area. At the same time, according to the spatial distribution characteristics of the current temperature fluctuation intensity, the path curvature is increased to form a buffer curve, so that the vehicle has a transition buffer process before entering the core crossing stage. In the core crossing stage, switch to a straight path and maintain a steady cruise, and start the vehicle's own temperature control device to spray a small amount of directional cold air flow. The temperature adjustment range of the cold air flow is proportional to the temperature deviation of the current area, that is, the greater the deviation of the regional temperature from the suitable blood storage temperature, the greater the temperature adjustment range of the cold air flow, so as to ensure that the blood is always in a suitable temperature environment. During the separation stage, the system detects the trend of temperature fluctuation intensity in real time, so that the curvature attenuation rate is synchronized with the temperature fluctuation intensity decrease rate, so that the vehicle can smoothly and safely leave the high fluctuation area. The whole process realizes the precise coordinated control of speed and temperature, and comprehensively guarantees the activity of blood during transportation.

[0038] The function of calculating the cumulative exposure of the blood transportation route in real time. Various sensors are distributed on the transportation route to continuously collect key data such as temperature and time. The system integrates and calculates these data based on a specific algorithm to obtain the cumulative exposure of blood during transportation in real time. This value reflects the comprehensive degree to which blood is affected by factors such as temperature during transportation. When the cumulative exposure reaches the pre-set activity tolerance threshold, it means that the blood activity is facing a greater risk. At this time, the system immediately issues an instruction to control the vehicle to slow down and stay at the set stop point. During the vehicle's stay, the IoT device is used to update the thermal map in real time to obtain the latest temperature distribution and fluctuations. Based on the updated thermal map, the system re-plans a safe detour route to avoid areas that may have a serious impact on blood activity, and updates the speed curve synchronously. The new path and speed planning will continue to serve to ensure blood activity and ensure that blood can complete the in-and-out transportation tasks safely and efficiently.

[0039] In another preferred embodiment of the present invention, the process of obtaining the activity decay curve and the transport parameters is:

[0040] In the blood storage process, the multispectral sensor plays a crucial role. It can accurately collect the red blood cell concentration, platelet activity index, and coagulation factor stability in the blood bag at preset time intervals. This is because the states of red blood cells, platelets, and coagulation factors directly reflect the activity of blood, and they will change under different conditions such as temperature and time. By continuously collecting these indicators, a time series dataset can be formed, which records the dynamic changes of blood indicators over time.

[0041] Next, polynomial fitting and exponential decay analysis are performed on this time series data. Polynomial fitting is a mathematical method that can approximately describe the change trend of data with a polynomial function. By continuously adjusting the coefficients of the polynomial, the fitting curve can be made as close as possible to the actual data points. Exponential decay analysis is based on the characteristic that the decay processes of many bioactive substances conform to the exponential law. By analyzing the data, the exponential characteristics of blood activity decay can be determined. Through these two analysis methods, key decay parameters can be extracted, including the activity half-life, critical inactivation temperature threshold, and vibration sensitivity coefficient. The activity half-life represents the time required for the blood activity to decrease to half of the initial value, which reflects the speed of blood activity decay; the critical inactivation temperature threshold is the temperature limit at which the blood activity begins to decline rapidly; the vibration sensitivity coefficient reflects the sensitivity of blood to vibration. Vibration may accelerate the destruction of components in the blood and affect blood activity. These parameters provide an important basis for subsequent transportation planning.

[0042] To screen out the areas suitable for blood transportation, the cold storage is divided into three-dimensional grid cells. Each grid cell has its specific environmental parameters, such as temperature and humidity. The matching degree score between the environmental parameters of each cell and the previously extracted activity decay parameters is calculated. The higher the matching degree score, the more favorable the environment of the cell is for maintaining blood activity. The areas with matching degree scores higher than the set threshold are marked as screening areas, so that the areas suitable for blood storage and transportation can be accurately found. Then, according to the real-time environmental parameters of the screening areas, corresponding weights are assigned to different parameters, and the average decay rate is calculated by weighted calculation. This average decay rate reflects the average decrease speed of blood activity in the screening areas. Next, an activity threshold is set, which is the lowest activity standard that the blood can meet the medical use requirements. Based on the activity half-life and the average decay rate, the time required to reach the activity threshold can be calculated. Finally, the transportation time is obtained based on the set proportion value, which is determined by comprehensively considering various factors to ensure that the blood activity can be maintained within an acceptable range during transportation.

[0043] In a preferred case of this embodiment, the generation process of the spiral progressive path is as follows:

[0044] First, a polar coordinate system is established with the starting point of transportation as the pole. This is a commonly used mathematical coordinate system that can easily describe the position and direction of the path. The destination coordinates are converted into the target polar angle to determine the approximate direction of transportation. The initial path unfolds along a spiral line, which has the characteristic of continuous change, allowing the vehicle to gradually approach the destination during driving. The expansion angle of the spiral line is adjusted according to the real-time temperature fluctuation data. This is because temperature fluctuations can affect blood activity. When the temperature fluctuation is large, adjusting the expansion angle can make the path avoid areas with large temperature fluctuations, or cross these areas in a more appropriate way.

[0045] At each set path decision point, the temperature fluctuation integral value is calculated. The temperature fluctuation integral value reflects the cumulative effect of temperature fluctuations within a certain period of time. When the integral value exceeds the preset second threshold, it means that the temperature fluctuation in this area may have a greater impact on blood activity. At this time, the rotation angle increment of the path is adjusted by the vibration sensitivity coefficient. The vibration sensitivity coefficient reflects the sensitivity of blood to vibration. Adjusting the rotation angle of the path in combination with the temperature fluctuation situation can reduce the damage of vibration to the blood while avoiding the impact of temperature fluctuations.

[0046] In low-fluctuation areas, the turning point density is set based on the path curvature change gradient. The curvature change gradient indicates how fast the path curvature changes. The larger the curvature change gradient, the more dramatic the change in the curvature of the path. In this case, increasing the turning point density can enable the vehicle to adapt to path changes more flexibly and reduce the impact of path mutations on the blood. In high-fluctuation areas, the turning point interval is extended according to the product of the temperature fluctuation intensity and the path curvature. When the temperature fluctuation intensity is large, a larger turning point interval can reduce the number of vehicle turns and reduce the impact of the vibration caused by the turn on the blood activity. At the same time, the path curvature radius is calculated based on the blood tolerance acceleration and the path friction coefficient. The blood tolerance acceleration determines the maximum acceleration change that the blood can withstand, and the path friction coefficient affects the driving stability of the vehicle on the path. By comprehensively considering these two factors to calculate the path curvature radius, it can be ensured that the vehicle will not cause damage to the blood due to excessive acceleration during driving, nor will it cause driving instability due to unreasonable path curvature.

[0047] In another preferred embodiment of the present invention, the staged control includes:

[0048] First, the system will obtain the vehicle's driving path in the high-fluctuation area and the detailed distribution of the temperature fluctuation intensity in the area. Set a threshold and mark the part of the path above this threshold as the core stage. The temperature fluctuation in this part of the area is the most drastic, posing the greatest threat to blood activity. The path before the core stage is defined as the initial stage, and the path after that is the disengagement stage. When entering the initial stage, considering that the vehicle enters the high-fluctuation area from a relatively stable environment, in order to avoid the blood being subjected to a strong impact of the rapid temperature change due to excessive speed, the vehicle speed is gradually reduced to the preset steady speed threshold through multi-stage deceleration control. At the same time, according to the spatial distribution characteristics of the current temperature fluctuation intensity, the path curvature is flexibly increased. If the temperature fluctuation intensity changes greatly in a certain direction, then the path curvature is increased in that direction to make the vehicle's driving path smoother, reduce blood shaking caused by operations such as rapid steering, and reduce the potential impact of temperature fluctuations on blood activity.

[0049] In the core stage, switch to a straight path and maintain a steady cruise speed. This is because straight-line driving can reduce the interference of the vehicle's turning on the blood, and a steady speed helps keep the blood in a relatively stable state of motion. At the same time, start the vehicle's built-in cold air flow device to control the temperature of the blood. The temperature adjustment amplitude of the cold air flow is proportional to the temperature deviation of the current area, that is, the greater the deviation between the temperature in the area and the suitable storage temperature of the blood, the greater the amplitude of the cold air flow temperature adjustment, so as to quickly and accurately maintain the blood temperature within the appropriate range, effectively reducing the damage of high temperature fluctuations to blood activity.

[0050] During the separation phase, the system closely monitors the trend of temperature fluctuation intensity. At this time, the curvature decay rate is synchronized with the temperature fluctuation intensity decrease rate. As the temperature fluctuation intensity gradually decreases, the path curvature also slowly decreases, allowing the vehicle to smoothly transition from a high fluctuation state to a relatively stable state, avoiding the impact of sudden changes in path curvature on the blood and ensuring the stability of the blood during the entire transportation process.

[0051] In another preferred embodiment of the present invention, the specific process of setting the stop point is:

[0052] At the beginning of path planning, set stop points are pre-generated. The selection of these stop points follows strict criteria. First, they must be located in low fluctuation intensity areas, because in such areas, blood is less affected by temperature fluctuations; second, they must have an environmental compensation interface to facilitate subsequent temperature adjustment and other operations.

[0053] When the vehicle stays at the docking point, a transition path including a deceleration arc is generated. The arc radius is dynamically calculated based on the current kinetic energy of the vehicle and the path curvature. The kinetic energy of the vehicle determines its inertia, and the path curvature reflects the degree of bending of the path. By comprehensively calculating these two factors for the arc radius, it can ensure a smooth transition of the vehicle's motion state when decelerating into the docking point and accelerating away from the docking point, reducing the impact on the blood. During the stay, cold air is released through the environmental compensation interface, and its purpose is to correct the blood temperature to the storage temperature. Because during transportation, even with various temperature control measures, the blood temperature may still deviate to a certain extent. At this time, using the cold air at the docking point for temperature calibration can effectively maintain the blood activity. After the correction is completed, the path curvature distribution is re-planned based on the updated thermal map. Since the latest environmental temperature information is obtained at the docking point, the thermal map is updated. Re-planning the path curvature according to the new temperature distribution can make the subsequent path more conducive to ensuring the blood activity. At the same time, the cumulative exposure of the new path is reset because the previous transportation situation has been adjusted and processed at the docking point. Recalculating the cumulative exposure can more accurately reflect the impact of subsequent transportation on the blood activity. And, according to the exposure of the passed areas, a compensation weight coefficient for each area's path is set. For areas with a larger previous exposure, a higher weight is given in subsequent path planning, that is, it is more inclined to avoid these areas or specially optimize the paths passing through these areas to reduce the risk of the blood being adversely affected again.

[0054] In another preferred embodiment of the present invention, the calculation method of the cumulative exposure is as follows:

[0055] First, the transportation path is dynamically segmented. Instead of dividing it into fixed lengths, the length of each segment is flexibly determined according to the changes in the actual transportation environment, such as temperature fluctuations and path characteristics. The exposure of each segment of the path is jointly calculated by the peak value of the temperature fluctuation intensity, the duration, and the average attenuation rate in the corresponding interval of this segment. The peak value of the temperature fluctuation intensity reflects the maximum degree of temperature fluctuation in this segment of the path, the duration reflects the exposure time of the blood in this temperature fluctuation environment, and the average attenuation rate combines the characteristics of the blood itself and the impact of the environment in this segment on the attenuation of the blood activity. By comprehensively considering these three factors, the impact degree of each segment of the path on the blood activity can be more accurately quantified.

[0056] Sensors are deployed at turning points of the route because the change in the vehicle's motion state at the turning points may have additional effects on blood activity. The sensors collect the actual blood activity parameters and compare them with the attenuation predicted by the activity attenuation curve obtained previously. A dynamic adjustment factor is generated based on the deviation between the two, and the dynamic adjustment factor is proportional to the deviation. If the actual activity parameters deviate greatly from the predicted values, it means that the current transportation environment or other factors have an impact on blood activity that exceeds expectations. In this case, the dynamic adjustment factor is larger, otherwise it is smaller. Finally, the total exposure is obtained by adding the product of the exposure of each segment and the dynamic adjustment factor. This calculation method not only takes into account the actual impact of each segment of the route, but also combines the real-time monitoring of blood activity changes for dynamic adjustment.

[0057] In another preferred embodiment of the present invention, the speed-temperature linkage control model comprises:

[0058] First, the model calculates the reference speed based on the current path curvature radius and the blood tolerance acceleration. The path curvature radius determines the curvature of the vehicle's driving path, and the blood tolerance acceleration reflects the maximum acceleration change that the blood can withstand during transportation. If this limit is exceeded, the cell structure in the blood may be damaged, affecting its activity. Research and practice have verified that the reference speed is proportional to the square root of the curvature radius. This means that the larger the path curvature radius (that is, the flatter the path), the higher the reference speed at which the vehicle can safely travel; conversely, the smaller the path curvature radius (the more tortuous the path), the lower the reference speed. For example, in a wide, nearly straight transportation channel, the path curvature radius is large, and the vehicle can travel at a higher reference speed to improve transportation efficiency; while in narrow areas with many bends, the path curvature radius is small, and in order to ensure blood safety, the vehicle needs to travel at a lower reference speed.

[0059] In the low fluctuation area, the temperature is relatively stable and poses less threat to blood activity. At this time, the model generates a correction to the baseline speed based on the absolute value of the real-time temperature change rate. The real-time temperature change rate reflects the temperature change amplitude per unit time. The larger its absolute value, the more drastic the temperature change and the greater the potential impact on blood activity. The correction amplitude is related to the exponential function of the temperature change rate. This is because the effect of temperature change on blood activity is not linear, but shows an accelerated deterioration trend as the temperature change rate increases. For example, when the temperature change rate is small, the correction amplitude increases slowly and the adjustment to the baseline speed is small; when the temperature change rate increases sharply, the correction amplitude will rise rapidly, greatly reducing the vehicle speed to reduce the impact of temperature changes on the blood. At the same time, to ensure the safety of the vehicle, the final speed will be limited to the preset safety speed to avoid excessive pursuit of adapting to temperature changes or path conditions, resulting in too low speed affecting transportation efficiency, or too high speed causing safety accidents.

[0060] When the vehicle enters a high-fluctuation area, the high temperature fluctuation intensity in this area poses a serious threat to blood activity. At this time, the model will increase the preset safety speed limit according to the temperature fluctuation intensity in the high-fluctuation area. The greater the temperature fluctuation intensity, the greater the increase. This is because in high-fluctuation areas, fast passage can reduce the time the blood is exposed to the harsh environment and reduce activity loss. For example, in areas with extremely drastic temperature fluctuations, the preset safety speed limit is appropriately increased to allow the vehicle to pass through the area at a faster speed while ensuring safety, thereby reducing the impact of temperature fluctuations on blood activity.

[0061] In another preferred embodiment of the present invention, the path efficiency index of each transport task is recorded. The path efficiency index is calculated by the normalized product of the total length of the path, the actual time consumption and the amount of active loss. The total length of the path reflects the length of the transport path. A shorter path can theoretically reduce the transport time and cost; the actual time consumption reflects the speed of the transport process; and the amount of active loss is directly related to the quality of the blood. By normalizing these three key factors, the effects caused by different units or numerical magnitudes are eliminated, and then they are multiplied to obtain the path efficiency index. The higher the index is, the more reasonable the path planning is, the higher the transport efficiency is, and the better the protection of blood activity is in this transport task. Paths with an index higher than the set threshold are marked as high-efficiency paths. These paths have good comprehensive performance and are important references for subsequent optimization.

[0062] The high-efficiency path is deeply analyzed through the convolutional neural network to extract its feature vector set. The feature vector set includes the path curvature sequence, speed adjustment frequency and environmental response parameters. The path curvature sequence records the curvature changes of the vehicle's path during the entire transportation process, reflecting the consideration of the path planning for the environment and blood safety; the speed adjustment frequency reflects the frequency of the vehicle's flexible speed change in different sections according to factors such as temperature and path, reflecting the execution effect of the speed-temperature linkage control model; the environmental response parameters cover the response strategies and actual adjustments to environmental factors such as temperature and humidity. By extracting and analyzing these feature vectors, the convolutional neural network can dig out the common patterns and key features of the high-efficiency path. The system regularly performs iterative optimization of control parameters, and adjusts the parameters in the speed-temperature linkage control model and the parameters in the path planning algorithm based on the feature vector information extracted by the convolutional neural network. For example, according to the characteristics of the speed adjustment frequency in the high-efficiency path, the calculation parameters of the speed correction amount are optimized; according to the characteristics of the environmental response parameters, the relevant parameters of the cold air flow temperature adjustment amplitude are adjusted. Through continuous iterative optimization, the entire blood storage and warehousing management method can better adapt to various transportation environments, improve transportation efficiency, and maximize blood activity and quality.

[0063] The above has described in detail an embodiment of the present invention, but the above content is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made in accordance with the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. An Internet of Things-based blood storage and retrieval management method, characterized in that It includes the following steps: Construct a three-dimensional temperature-controlled thermal map of the blood cold storage, mark the temperature fluctuation intensity and allowable exposure duration of each area of the cold storage, and divide each area into a high-fluctuation area and a low-fluctuation area according to the temperature change rate threshold; When a transportation instruction is received, obtain the activity decay curve of the target blood changing with time at different temperatures, screen the area and set the transportation duration according to the activity decay curve, and generate a spiral progressive path for vehicle transportation within the screened area. The curvature radius of the path is negatively correlated with the temperature fluctuation intensity of the area passed through, and the distance between the turning points of the path is positively correlated with the temperature fluctuation intensity; Establish a speed-temperature linkage control model during transportation. The vehicle transportation speed in the low-fluctuation area is negatively correlated with the temperature change rate of each area. When entering the high-fluctuation area, implement staged speed control; Calculate the cumulative exposure amount of the blood transportation path in real time. When the activity tolerance threshold is reached, control the vehicle to decelerate to the set stop point and stay. During the stay period, update the thermal map, plan a detour path based on the updated thermal map, and update the speed curve.

2. The method for managing blood storage and retrieval based on the Internet of Things according to claim 1, wherein The process of obtaining the activity decay curve and transportation parameters is as follows: When the blood is put into storage, collect the red blood cell concentration, platelet activity index, and coagulation factor stability in the blood bag at preset time intervals through a multispectral sensor to form a time series data set; perform polynomial fitting and exponential decay analysis on the time series data, and extract key decay parameters, including the activity half-life, critical inactivation temperature threshold, and vibration sensitivity coefficient; Divide the cold storage into three-dimensional grid cells, calculate the matching degree score between the environmental parameters and the activity decay parameters of each cell, and mark the area with a matching degree score higher than the set threshold as the screened area; calculate the average decay rate by weighting the real-time environmental parameters of the screened area, set the activity threshold, calculate the duration to reach the activity threshold according to the activity half-life and the average decay rate, and obtain the transportation duration based on the set ratio value.

3. The method for managing blood storage and retrieval based on the Internet of Things according to claim 2, wherein The generation process of the spiral progressive path is as follows: Establish a polar coordinate system with the transportation starting point as the pole, convert the destination coordinates into the target polar angle, and the initial path unfolds along a spiral. The unfolding angle of the spiral is adjusted according to the real-time temperature fluctuation data; calculate the temperature fluctuation integral value at each set path decision point. When the integral value exceeds the preset second threshold, adjust the rotation angle increment of the path through the vibration sensitivity coefficient; Set the turning point density based on the path curvature change gradient in the low-fluctuation area. The greater the curvature change gradient, the higher the turning point density. In the high-fluctuation area, expand the turning point interval according to the product value of the temperature fluctuation intensity and the path curvature; Calculate the path curvature radius according to the blood tolerance acceleration and the path friction coefficient.

4. The blood storage-in and storage-out management method based on the Internet of Things according to claim 1, wherein, The staged control includes: Obtain the driving path of the vehicle in the high-fluctuation area and the temperature fluctuation intensity distribution in the high-fluctuation area. Mark the path above the set threshold as the core stage, and mark the paths before and after the core stage as the initial stage and the detachment stage respectively. When entering the initial stage, the vehicle speed is reduced to the preset stable speed threshold through multi-stage deceleration control, and at the same time, the path curvature is increased according to the spatial distribution characteristics of the current temperature fluctuation intensity; in the core stage, switch to a straight path and maintain a stable speed cruise, and start the vehicle's built-in cold air flow to control the temperature of the blood. The temperature adjustment range of the cold air flow is proportional to the temperature deviation of the current area; in the detachment stage, detect the trend of the temperature fluctuation intensity, and the curvature decay rate is synchronized with the temperature fluctuation intensity decline rate.

5. The blood storage-in and storage-out management method based on the Internet of Things according to claim 1, wherein The specific process of setting the designated stop point is as follows: During path planning, pre-generate the designated stop point. The selection criteria for the designated stop point include being located in the low-fluctuation intensity area and having an environmental compensation interface; when the vehicle stays, generate a transition path including a deceleration arc, and the arc radius is dynamically calculated according to the current vehicle kinetic energy and path curvature; during the stay, release cold air flow through the environmental compensation interface to correct the blood temperature to the storage temperature; After the correction is completed, re-plan the path curvature distribution based on the updated heat map, reset the cumulative exposure of the new path, and set the compensation weight coefficient of each area path according to the exposure of the passed area.

6. The blood storage and retrieval management method based on the Internet of Things according to claim 2, wherein The calculation method of the cumulative exposure is as follows: Dynamically segment the transportation path. The exposure of each path segment is jointly calculated by the peak value of the temperature fluctuation intensity, the duration, and the average decay rate of the corresponding interval of this segment; deploy sensors at the path turning points, collect the actual activity parameters of the blood and compare them with the predicted decay curve, and generate a dynamic adjustment factor according to the deviation degree. The dynamic adjustment factor is proportional to the deviation degree; the total exposure is obtained by accumulating the product values of the exposure of each segment and the dynamic adjustment factor.

7. A method for managing the blood storage and retrieval based on the Internet of Things according to claim 1, characterized in that, The speed-temperature linkage control model includes: Calculate the reference speed according to the current path curvature radius and the blood tolerance acceleration. The reference speed is proportional to the square root of the curvature radius; In the low-fluctuation area, generate a correction amount of the reference speed according to the absolute value of the real-time temperature change rate. The amplitude of the correction amount is related to the exponential function of the temperature change rate, and the final speed is limited within the preset safe speed; when entering the high-fluctuation area, increase the limit of the preset safe speed according to the temperature fluctuation intensity of the high-fluctuation area.

8. The blood storage-in and storage-out management method based on the Internet of Things according to claim 1, characterized in that Record the path efficiency index of each transportation task. The index is calculated by the normalized product of the total path length, the actual time consumption, and the activity loss amount. Mark the path with an index higher than the set threshold as a high-efficiency path; extract the feature vector set of the high-efficiency path through a convolutional neural network. The feature vector set includes the path curvature sequence, the speed adjustment frequency, and the environmental response parameters, and perform iterative optimization of the control parameters regularly.

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