Full-dimensional monitoring system of intelligent specimen cabinet

Abstract

The invention discloses a full-dimension monitoring system of an intelligent specimen cabinet, and belongs to the technical field of biological sample storage management. The full-dimension monitoring system is arranged in the intelligent specimen cabinet, the full-dimension monitoring system receives a sample access instruction, generates a moving path based on the position of an access target and performs access movement on the access target, and the full-dimension monitoring system constructs the full-dimension monitoring system including environmental parameter monitoring, safety protection monitoring and three-dimensional construction. The operation state of the specimen cabinet is comprehensively controlled, the stability of a sample storage environment is guaranteed, risks caused by unauthorized invasion and equipment abnormity are prevented, and a full-dimension monitoring system obtains temperature actual measurement values and humidity actual measurement values corresponding to all positions in the specimen cabinet main body and sends the temperature actual measurement values and the humidity actual measurement values to a server. And calculating a sample risk value of a failure risk degree of the placed sample corresponding to each position in real time, identifying a sample failure high-risk area and performing early warning, performing real-time association and generating a four-dimensional data set, and identifying a hidden risk of the sample caused by small environmental fluctuation accumulation and operation interference.

Description

Technical Field

[0001] This invention relates to the field of biological sample storage and management technology, and in particular to a full-dimensional monitoring system for intelligent specimen cabinets. Background Technology

[0002] In the storage and management of biological samples and chemical reagents, traditional specimen cabinets have long relied on manual operation, which has many technical limitations. Traditional equipment lacks comprehensive monitoring methods, and environmental parameter monitoring mostly depends on single-point sensors, which cannot accurately reflect the differences in temperature, humidity, and gas concentration in different storage areas. When anomalies occur, timely warnings are difficult to provide, often resulting in the loss of batches of samples. In terms of security, relying solely on simple door locks is insufficient to prevent unauthorized intrusion and security incidents caused by mechanical failures. Furthermore, operation records are mostly handwritten, resulting in low traceability efficiency. Once sample confusion or loss occurs, it is impossible to quickly locate the responsible party. Summary of the Invention

[0003] The purpose of this invention is to provide a full-dimensional monitoring system for intelligent specimen cabinets to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a full-dimensional monitoring system for an intelligent specimen cabinet, wherein the full-dimensional monitoring system is installed inside the intelligent specimen cabinet, the full-dimensional monitoring system receives instructions to access samples, generates a movement path based on the location of the access target, and performs access and movement of the access target; The all-dimensional monitoring system periodically collects environmental data in the intelligent specimen cabinet, which includes the measured temperature and humidity values ​​at each location in the intelligent specimen cabinet. It also monitors the preservation environment inside the intelligent specimen cabinet, calculates the sample risk value in real time to indicate the degree of failure of the samples placed at each location, identifies high-risk areas for sample failure based on changes in the preservation environment, triggers an early warning mechanism, and intervenes dynamically. The full-dimensional monitoring system records the operation records of storing and retrieving samples and verifies whether they are compliant, identifies violations and hidden risks caused by the accumulation of minor environmental fluctuations or operational interference.

[0005] Furthermore, the intelligent specimen cabinet includes a specimen cabinet body and a reagent refrigerator. The specimen cabinet body is located inside the reagent refrigerator. The front of the reagent refrigerator has a sample inlet / outlet. The sample inlet / outlet is equipped with an automatic door and a telescopic tray. The interior of the specimen cabinet body is divided into storage columns by longitudinal partitions, and sample holders are placed in the storage columns.

[0006] Furthermore, the all-dimensional monitoring system includes: The intelligent transfer scheduling module is configured as follows: After receiving the user's instruction to access the sample, the system obtains the coordinates of the target location, generates the optimal movement path, and then moves the sample of the target to access the sample based on the optimal movement path. The environmental parameter monitoring module is configured as follows: Environmental data is collected according to a preset sampling period. The environmental data is compared with a preset threshold range. When the environmental data deviates from the preset threshold range, an early warning mechanism is triggered, and environmental control equipment is activated for dynamic intervention. The security protection and monitoring module is configured as follows: Real-time monitoring of the reagent refrigerator's interior and sample entry / exit points to ensure no unauthorized objects enter; The operation behavior traceability module is configured as follows: Generate operation records containing time, location, operation object, and execution result; use a rule engine to perform compliance verification on the operation records and identify violations. The 3D building module is configured as follows: A 3D model of the specimen cabinet body is constructed using 3D modeling, and the internal structure, specimen distribution, and environmental parameters of the specimen cabinet body are visualized based on the 3D model. The sample state association module is configured as follows: By linking environmental parameters and sample operation data in real time to form a four-dimensional dataset, the hidden risks caused by the accumulation of minor environmental fluctuations and operational interference can be identified, and targeted intervention measures can be initiated.

[0007] Furthermore, the environmental parameter monitoring module includes: The multi-source data acquisition unit is configured as follows: By deploying temperature and humidity sensor groups, gas concentration detector arrays and air pressure sensors in different areas inside the reagent refrigerator, environmental data is collected synchronously according to a preset sampling cycle, the collected environmental data is cached and a raw dataset of environmental parameters is generated. The dynamic threshold early warning unit is configured as follows: Call the preset environmental parameter threshold matrix, which includes the upper and lower limits of temperature and humidity and the safe threshold of gas concentration for different storage areas; The original dataset of environmental parameters is compared point by point with the threshold matrix of environmental parameters, and the deviation of parameters is obtained by the deviation calculation algorithm. When the deviation exceeds the preset threshold, the early warning mechanism and adjustment signal are triggered according to the degree of deviation, the abnormal information is recorded and the audible and visual alarm device is activated, the early warning signal is sent to the management terminal at the same time, and the three-dimensional coordinates of the abnormal area are marked. The environment adaptive adjustment unit is configured as follows: Upon receiving the adjustment signal, the environmental control equipment in the corresponding area is activated; Temperature regulation is achieved through the coordinated operation of the compressor refrigeration module and the heating wire assembly, which automatically adjusts the output power according to the temperature difference; humidity regulation is achieved through bidirectional control of the dehumidifying fan and the humidifying atomizer, which adjusts the running time according to the humidity deviation. During the adjustment process, environmental parameter changes are collected in real time until the environmental data returns to the threshold range, at which point the adjustment equipment is automatically stopped and the adjustment curve is recorded.

[0008] Furthermore, the security protection and monitoring module includes: The multimodal intrusion detection unit is configured as follows: The infrared thermal imaging sensor array deployed inside the reagent refrigerator captures temperature field distribution images in real time, and simultaneously activates the laser contour scanner integrated into the sample inlet and outlet to generate three-dimensional contour data. The temperature field distribution image is compared with the preset environmental temperature field benchmark model to identify abnormally high temperature areas; Feature extraction is performed on the 3D contour data generated by the laser contour scanner, and it is matched with the 3D feature library of authorized objects. When the matching degree is lower than the preset threshold, it is determined that there is an unauthorized object. The coordinates of the abnormally high temperature area are correlated with the results of unauthorized object identification to generate a preliminary intrusion detection report. The dynamic protection response unit is configured as follows: Receive the initial intrusion detection report and invoke the preset risk level assessment model; The risk level assessment model calculates the invasion risk coefficient based on the volume parameters, movement speed, and distance parameters of the invading object to the sample. When the risk factor is in the low-risk range, the electromagnetic locking device at the sample entrance and exit is activated, and the audible and visual alarms in the local area are also activated. When the risk factor is in the high-risk range, in addition to implementing low-risk response measures, the main power supply circuit of the reagent refrigerator is simultaneously cut off while maintaining the power supply to the monitoring system, the standby mode of the inert gas fire extinguishing device is activated, and an emergency alarm signal containing a real-time video stream is sent to the security terminal. During the protection response, the location coordinates of the intruding object are updated in real time; The intrusion trajectory tracing unit is configured as follows: A multi-view camera array distributed inside the specimen cabinet is used to capture motion video streams of unauthorized objects. Based on the frame image sequence in the video stream, a moving target tracking algorithm is used to extract the motion trajectory parameters of unauthorized objects, including displacement vector, turning angle and motion acceleration. The motion trajectory parameters are mapped to the three-dimensional model inside the specimen cabinet to generate a visualized invasion path map; By associating timestamp information, a full trajectory dataset is constructed, including the intrusion starting point, the areas traversed, the duration of stay, and the final location.

[0009] Furthermore, a three-axis moving assembly is provided on the top of the specimen cabinet body, and a shovel mechanism is provided on the three-axis moving assembly. A tube-picking robotic arm and a scanning mechanism are provided inside the reagent refrigerator near the sample inlet and outlet.

[0010] Furthermore, the operation behavior tracing module includes: The end-to-end data acquisition unit is configured as follows: It receives sample barcodes output by the scanning mechanism in real time and simultaneously collects sample electronic tag data read by the RFID detection module integrated in the tube-picking robotic arm; Obtain the operator's identity verification information, wherein the identity verification information is an authorization code; Collect real-time coordinate data of the X, Y, and Z axes of the three-axis moving components and the motion status signals of the shovel mechanism to form a mechanical operation trajectory record; By linking and integrating sample barcodes, sample electronic tags, identity verification information, and mechanical operation trajectory records according to timestamps, a full-process dataset containing sample information, operating entities, mechanical actions, and time nodes is constructed. The operation compliance verification unit is configured as follows: The system calls a preset operation rule library, which includes sample authorized access range, mechanical operation path specifications, and sample placement correspondence verification criteria. The entire process dataset is compared item by item with the operation rule library, and violations are identified through logical verification. When the operator's identity information is detected to be outside the authorized list or outside the authorized operation scope, it is determined to be unauthorized access; When the actual placement of the sample deviates from the preset storage column coordinates by more than 5cm, or when the sample label information does not match the target storage area, it is determined that the sample is misplaced. Generate a verification report that includes the type of violation, the time of the violation, related samples, and the operation trajectory.

[0011] Furthermore, the environmental parameter monitoring module also includes: The sample storage risk warning unit is configured as follows: Acquire the data collected by the temperature and humidity sensor group; wherein, the data collected by the temperature and humidity sensor group includes: the measured temperature value corresponding to the position of the storage column, and the measured humidity value corresponding to the position of the storage column; Based on the data collected by the temperature and humidity sensor group, the sample risk value, representing the degree of risk of failure of the samples placed in the corresponding storage column, is calculated in real time using the following formula:

[0012] in, The sample risk value of the stored column, The measured temperature value corresponding to the position of the stored column in the data collected by the temperature and humidity sensor group. The measured humidity value corresponding to the position of the stored column in the data collected by the temperature and humidity sensor group. The preset optimal storage temperature, To achieve the preset optimal storage humidity, The preset temperature critical deviation, This is the preset humidity critical deviation. The temperature and humidity of the storage column locations, as described historically, both exceeded [the limits]. - , + ] Scope and [ - , + The cumulative duration within the range, For the preset time limit, , as well as The preset weight values; When the risk value of the sample in the storage column exceeds a preset threshold, it is determined that the degree of failure risk of the sample placed in the storage column exceeds the standard. The storage column is marked as a high-risk area for sample failure in the three-dimensional model to warn management personnel to take appropriate intervention.

[0013] Furthermore, the comprehensive monitoring system for the intelligent specimen cabinet also includes: The multi-level linkage response module is configured as follows: Establish an abnormal event hierarchical response matrix, which includes: first-level events and their corresponding first event response strategies, and second-level events and their corresponding second event response strategies. The first-level events include: intrusion locking events triggered by the security protection monitoring module; The first event response strategy includes: Perform the following operations simultaneously: Operation 1: Activate the real-time recording function of all cameras inside the reagent refrigerator, with the recording range covering the sample entrance / exit and the panoramic view of the main body of the specimen cabinet; Step 2: Send an encrypted alarm message containing the intrusion coordinates, timestamp, and device lock status to the management terminal; Operation 3: Disconnect the drive power of the three-axis moving assembly and the pipe-picking robotic arm, and only keep the power supply on the environmental control equipment; The secondary events include: unauthorized access or sample misplacement events identified by the operation behavior traceability module; The second event response strategy includes: Before the shovel mechanism moves the sample tray to the target position, the scanning mechanism performs a secondary verification of the matching degree between the sample label and the stored column code; When the verification fails, the control three-axis moving component moves the sample tray to the isolation temporary storage area and marks a red warning mark in the three-dimensional model.

[0014] Furthermore, the sample state association module includes: The status data association unit is configured as follows: The system receives historical change curves of temperature, humidity, and gas concentration for each storage column from the environmental parameter monitoring module in real time, and simultaneously acquires data on sample access frequency, operation duration, and mechanical operation trajectory recorded by the operation behavior traceability module. The three-dimensional model coordinate system of the three-dimensional construction module is invoked to associate the environmental parameter change curves with the sample operation data of the corresponding stored columns according to spatial coordinates, forming a four-dimensional associated dataset containing time dimension, spatial coordinates, environmental parameters and operation behavior; The temporal correlation between changes in environmental parameters and sample operational behaviors in a four-dimensional correlated dataset is identified by a trend extraction algorithm, and event combinations with temporal correlation exceeding a preset threshold are marked. The hidden risk identification unit is configured as follows: A preset sample state influence factor matrix is ​​provided, which includes the sensitivity coefficients of different types of samples to environmental fluctuations, operation frequency thresholds, and tolerance for cumulative changes in environmental parameters. Based on the four-dimensional associated dataset and combined with the sample state influence factor matrix, the comprehensive impact value of environmental fluctuations and operational interference on the samples in each storage column is calculated. When the comprehensive impact value exceeds the preset safety threshold of the corresponding sample, it is determined that there is a hidden risk. The hidden risk includes indirect risks of exceeding the threshold, such as the decrease in sample activity caused by the accumulation of small fluctuations in environmental parameters and the local environmental instability caused by frequent operations. Generate a hidden risk assessment report that includes risk storage column coordinates, associated operation records, and environmental parameter change trends; The intervention guidance unit is configured as follows: Upon receiving the implicit risk assessment report, targeted intervention measures are automatically initiated, including: Combined with the intelligent transfer and scheduling module, sample optimization storage suggestions are generated, including transferring highly sensitive samples to storage columns with less environmental fluctuation and adjusting the storage of similar samples in a concentrated manner to reduce cross-interference. Send operation prompt rules to the operation behavior traceability module to add environmental parameter current status prompts and operation duration limits for operations involving high-risk storage columns; The 3D building module uses gradient colors to mark storage columns with different risk levels in the 3D model, and displays the key environmental parameters and operation records that lead to the risk. The system continuously tracks environmental parameters and operational data in the area where the sample was located after intervention. When the overall impact value returns to the preset safety threshold range, the targeted intervention measures are automatically lifted.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a comprehensive monitoring system that includes environmental parameter monitoring, security protection monitoring, and 3D modeling. This system enables all-round control over the operating status of the specimen cabinet. Through multi-source acquisition and adaptive adjustment, it ensures the stability of the sample storage environment and avoids sample failure due to fluctuations in parameters such as temperature and humidity. Through three-dimensional security and emergency braking, it effectively prevents risks caused by unauthorized intrusion and equipment malfunctions. Through visualization, it allows managers to intuitively grasp the status of the cabinet, forming a closed-loop management system from environment to equipment. This significantly improves the security and precision of sample management and reduces operation and maintenance costs.

[0016] 2. This invention integrates sample information, operating entity, and mechanical trajectory data through a full-process data acquisition unit, and identifies violations by an operation compliance verification unit, achieving full-chain traceability of sample operations, standardizing operator behavior, reducing unauthorized access and sample misplacement issues, and providing a reliable basis for sample quality traceability. In scientific research or medical scenarios, it can quickly locate the flow path of problematic samples, enhancing the credibility of sample management, and providing strong support for quality management system certification, meeting the stringent requirements for sample management in highly standardized scenarios.

[0017] 3. Beyond the limitations of traditional single-point threshold alarms, it transforms discrete environmental parameters into a comprehensive prediction of sample damage potential. It accurately captures instantaneous abnormal fluctuations (such as a sudden temperature rise caused by a cooling failure) and identifies long-term chronic deviations (such as slowly exceeding humidity limits). This drives managers to prioritize intervention in high-risk areas and, combined with 3D visualization, quickly locates samples that need rescue, significantly reducing the probability of batch failures. At the same time, the continuously accumulated risk data provides a basis for optimizing storage strategies (such as adjusting sensor layout or weight allocation), forming a closed-loop optimization from risk warning to strategy iteration.

[0018] 4. Precise security response is achieved through event tiering: Level 1 events focus on physical isolation and evidence preservation to minimize malicious security threats; Level 2 events focus on process correction and partial disruption to maintain operational continuity while eliminating the risk of human error spreading. Encrypted alarms, 3D alerts, and operation logs further constitute a complete chain of evidence for traceability, providing data support for event retrospective and system optimization, ultimately achieving a deep balance between security control and operational efficiency. Attached Figure Description

[0019] Figure 1 This is a schematic diagram showing the location of the main body of the specimen cabinet of the present invention; Figure 2 This is a schematic diagram of the sample inlet and outlet of the present invention; Figure 3 This is a schematic diagram of the main structure of the specimen cabinet of the present invention; Figure 4 This is a side view of the main body of the specimen cabinet of the present invention; Figure 5 This is a schematic diagram of the all-dimensional monitoring system module of the present invention.

[0020] In the diagram: 1. Specimen cabinet body; 2. Reagent refrigerator; 3. Sample inlet / outlet; 4. Sample tray; 5. Three-axis moving assembly; 6. Tray mechanism; 7. Longitudinal partition; 8. Storage column. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1-5 The present invention provides the following technical solutions: The intelligent specimen cabinet has a full-dimensional monitoring system. The full-dimensional monitoring system is set inside the intelligent specimen cabinet. The full-dimensional monitoring system receives the sample access command, generates a movement path based on the location of the access target, and performs access and movement of the access target.

[0023] The all-dimensional monitoring system periodically collects environmental data from the intelligent specimen cabinet, which includes the measured temperature and humidity values ​​at each location within the cabinet. It also monitors the preservation environment inside the cabinet, calculates the sample risk value in real time to indicate the degree of sample failure at each location, identifies high-risk areas for sample failure based on changes in the preservation environment, triggers an early warning mechanism, and intervenes dynamically.

[0024] The comprehensive monitoring system records and verifies the compliance of sample retrieval operations, identifies violations, and identifies hidden risks arising from minor environmental fluctuations or operational interference. The intelligent specimen cabinet includes a main body 1 and a reagent refrigerator 2. The main body 1 is located inside the reagent refrigerator 2. The front of the reagent refrigerator 2 has a sample inlet / outlet 3, which contains an automatic door and a telescopic tray. The interior of the main body 1 houses a sample holder 4. A three-axis moving assembly 5 is located on the top of the main body 1, and a scooping mechanism 6 is mounted on the three-axis moving assembly 5. A tube-picking robotic arm and a scanning mechanism are located inside the reagent refrigerator 2 near the sample inlet / outlet 3.

[0025] The specimen cabinet body 1 has a longitudinal partition 7 inside, which divides the interior of the specimen cabinet body 1 into storage columns 8. The sample holder 4 is placed in the storage column 8. The tube picking robotic arm integrates an RFID detection module, which is used to record sample data when picking tubes.

[0026] In the above embodiments, by setting the specimen cabinet body 1 inside the reagent refrigerator 2 and adopting a dual-body parallel layout, combined with the storage column 8 and the card-mounting platform 9 structure divided by the longitudinal partition 7, the efficient utilization and classified management of sample storage space are realized. The sample tray 4 is stably placed through the card-mounting platform, which not only facilitates the precise picking and placing of the sample by the three-axis moving component 5 driving the shovel mechanism 6, but also avoids shaking or shifting of the sample during storage. The automatic door and telescopic tray design of the sample inlet / outlet 3, combined with the collaborative operation of the tube picking robotic arm and the scanning mechanism, breaks the limitations of manual storage and retrieval in traditional specimen cabinets, reduces direct contact between manual operation and low temperature environment, reduces the risk of sample contamination, and improves the convenience and accuracy of sample storage and retrieval. The integration of the full-dimensional monitoring system forms a closed-loop management from mechanical execution to environmental monitoring, providing an intelligent and automated overall solution for sample storage.

[0027] The all-dimensional monitoring system, applied to the aforementioned intelligent specimen cabinet, includes: The intelligent transfer scheduling module is configured as follows: After receiving the user's instruction to access the sample, the system obtains the coordinates of the target location, generates the optimal movement path, and then moves the sample of the target to access the sample based on the optimal movement path. The environmental parameter monitoring module is configured as follows: Environmental data is collected according to a preset sampling period. The environmental data is compared with a preset threshold range. When the environmental data deviates from the preset threshold range, an early warning mechanism is triggered, and environmental control equipment is activated for dynamic intervention. The security protection and monitoring module is configured as follows: Real-time monitoring of the interior of reagent refrigerator 2 and sample entrance / exit 3 to check for unauthorized objects entering; The operation behavior traceability module is configured as follows: Generate operation records containing time, location, operation object, and execution result; use a rule engine to perform compliance verification on the operation records and identify violations. The 3D building module is configured as follows: A three-dimensional model of the specimen cabinet body 1 is constructed through three-dimensional modeling, and the internal structure, specimen distribution and environmental parameters of the specimen cabinet body 1 are visualized based on the three-dimensional model. The sample state association module is configured as follows: By linking environmental parameters and sample operation data in real time to form a four-dimensional dataset, the hidden risks caused by the accumulation of minor environmental fluctuations and operational interference can be identified, and targeted intervention measures can be initiated.

[0028] In the above embodiments, the all-dimensional monitoring system achieves intelligent management and control of the entire process of intelligent specimen cabinet from sample storage and retrieval to environmental maintenance through the coordinated operation of modules. The cooperation between the mechanical linkage control module and the intelligent transfer scheduling module eliminates the need for manual intervention inside the cabinet during the sample storage and retrieval process, which not only improves operational efficiency but also avoids sample damage or confusion caused by human factors. The environmental parameter monitoring module monitors the environment inside the cabinet in real time to ensure that the samples are in the best storage conditions. The safety protection monitoring module provides multiple safety guarantees for the equipment and samples through a three-dimensional security and emergency braking mechanism. The operation behavior traceability module enables the traceability of every operation, and the three-dimensional construction module allows managers to intuitively grasp the status of the cabinet through visualization, significantly improving the precision of sample management and reducing management costs. It is especially suitable for the efficient operation and maintenance of large-scale sample banks.

[0029] The environmental parameter monitoring module includes: The multi-source data acquisition unit is configured as follows: By deploying temperature and humidity sensor groups, gas concentration detector arrays and air pressure sensors in different areas inside reagent refrigerator 2, environmental data is collected synchronously according to a preset sampling cycle, the collected environmental data is cached and the original dataset of environmental parameters is generated. The dynamic threshold early warning unit is configured as follows: Call the preset environmental parameter threshold matrix, which includes the upper and lower limits of temperature and humidity and the safe threshold of gas concentration for different storage areas; The original dataset of environmental parameters is compared point by point with the threshold matrix of environmental parameters, and the deviation of parameters is obtained by the deviation calculation algorithm. When the deviation exceeds the preset threshold, the early warning mechanism and adjustment signal are triggered according to the degree of deviation, the abnormal information is recorded and the audible and visual alarm device is activated, the early warning signal is sent to the management terminal at the same time, and the three-dimensional coordinates of the abnormal area are marked. The environment adaptive adjustment unit is configured as follows: Upon receiving the adjustment signal, the environmental control equipment in the corresponding area is activated; Temperature regulation is achieved through the coordinated operation of the compressor refrigeration module and the heating wire assembly, which automatically adjusts the output power according to the temperature difference; humidity regulation is achieved through bidirectional control of the dehumidifying fan and the humidifying atomizer, which adjusts the running time according to the humidity deviation. During the adjustment process, environmental parameter changes are collected in real time until the environmental data returns to the threshold range, at which point the adjustment equipment is automatically stopped and the adjustment curve is recorded.

[0030] In the above embodiments, a precise and efficient environmental control system is constructed through the collaborative work of multi-source data acquisition, dynamic threshold early warning, and environmental adaptive adjustment unit. The matrix-distributed sensor array can comprehensively capture changes in temperature, humidity, gas concentration, and air pressure in different areas within the reagent refrigerator 2, ensuring comprehensive data acquisition. Through a preset threshold matrix and deviation calculation algorithm, environmental anomalies can be quickly identified and graded early warnings issued, giving managers more time to handle the situation. The coordinated action of cooling, heating, dehumidification, and humidification equipment achieves dynamic balance of environmental parameters, preventing sample failure due to environmental fluctuations. This not only ensures the stability of sample storage but also reduces manual intervention and energy consumption through automatic adjustment. Meanwhile, anomaly records and adjustment curves provide data support for subsequent optimization of environmental control strategies.

[0031] The security protection and monitoring module includes: The multimodal intrusion detection unit is configured as follows: The infrared thermal imaging sensor array deployed inside the reagent refrigerator 2 captures the temperature field distribution image in real time, and the laser contour scanner integrated in the sample inlet / outlet 3 is activated simultaneously to generate three-dimensional contour data. The temperature field distribution image is compared with the preset environmental temperature field benchmark model to identify abnormally high temperature areas; Feature extraction is performed on the 3D contour data generated by the laser contour scanner, and it is matched with the 3D feature library of authorized objects. When the matching degree is lower than the preset threshold, it is determined that there is an unauthorized object. The coordinates of the abnormally high temperature area are correlated with the results of unauthorized object identification to generate a preliminary intrusion detection report. The dynamic protection response unit is configured as follows: Receive the initial intrusion detection report and invoke the preset risk level assessment model; The risk level assessment model calculates the invasion risk coefficient based on the volume parameters, movement speed, and distance parameters of the invading object to the sample. When the risk factor is in the low-risk range, the electromagnetic locking device of sample entrance / exit 3 is activated, and the audible and visual alarm of the local area is activated at the same time. When the risk factor is in the high-risk range, in addition to implementing low-risk response measures, the main power supply circuit of reagent refrigerator 2 is simultaneously cut off while maintaining the power supply to the monitoring system, the standby mode of the inert gas fire extinguishing device is activated, and an emergency alarm signal containing real-time video stream is sent to the security terminal. During the protection response, the location coordinates of the intruding object are updated in real time; The intrusion trajectory tracing unit is configured as follows: A multi-view camera array distributed inside the main body 1 of the specimen cabinet is used to collect motion video streams of unauthorized objects. Based on the frame image sequence in the video stream, a moving target tracking algorithm is used to extract the motion trajectory parameters of unauthorized objects, including displacement vector, turning angle and motion acceleration. The motion trajectory parameters are mapped to the three-dimensional model inside the specimen cabinet to generate a visualized invasion path map; By associating timestamp information, a full trajectory dataset is constructed, including the intrusion starting point, the areas traversed, the duration of stay, and the final location.

[0032] In the above embodiments, the multimodal intrusion detection unit, combined with an infrared thermal imaging sensor array and a laser contour scanner, can capture abnormally high temperature areas (such as equipment malfunctions or external heat sources) and identify unauthorized objects (such as unauthorized tools, personnel limbs, etc.), achieving three-dimensional monitoring of the inside of the reagent refrigerator and sample entrances and exits, ensuring comprehensive protection without blind spots and preventing sample tampering, theft, or contamination from the source. The dynamic protection response unit, based on a risk level assessment model, calculates the risk coefficient according to the volume, speed, and distance of the intruding object from the sample, distinguishes between low-risk and high-risk scenarios, and implements differentiated measures: in low-risk scenarios, the entrance and exit are locked and a local alarm is triggered; in high-risk scenarios, the main power supply is cut off, the fire extinguishing device is activated and an emergency alarm is sent, which can quickly curb the spread of danger while avoiding excessive response that may affect the normal operation of the equipment. The intrusion trajectory tracing unit collects motion video streams through multi-view cameras, extracts the motion trajectory (displacement, turning, acceleration, etc.) of unauthorized objects, and maps it with a three-dimensional model to generate a visualized path map. Combined with timestamps, a complete trajectory dataset is formed, providing conclusive evidence for tracing the intrusion process and determining responsibility after the fact, while also providing data support for optimizing security strategies.

[0033] The security protection and monitoring module provides a closed-loop mechanism of "detection-evaluation-response-tracing" to ensure the safety of samples and equipment from real-time protection to emergency response. It reduces sample failure or data corruption caused by external intrusion and is especially suitable for scenarios with extremely high requirements for sample safety, such as medical and scientific research, thereby improving the credibility and reliability of sample storage.

[0034] The operation behavior traceability module includes: The end-to-end data acquisition unit is configured as follows: It receives sample barcodes output by the scanning mechanism in real time and simultaneously collects sample electronic tag data read by the RFID detection module integrated in the tube-picking robotic arm; Obtain the operator's identity verification information, which is an authorization code; The real-time coordinate data of the X, Y, and Z axes of the three-axis moving component 5 and the action status signals of the shovel mechanism 6 are collected to form a mechanical operation trajectory record; By linking and integrating sample barcodes, sample electronic tags, identity verification information, and mechanical operation trajectory records according to timestamps, a full-process dataset containing sample information, operating entities, mechanical actions, and time nodes is constructed. The operation compliance verification unit is configured as follows: The system calls a pre-defined operation rule library, which includes verification criteria such as authorized access range for samples, mechanical operation path specifications, and corresponding sample placement relationships. The entire process dataset is compared item by item with the operation rule library, and violations are identified through logical verification. When the operator's identity information is detected to be outside the authorized list or outside the authorized operation scope, it is determined to be unauthorized access; When the actual placement of the sample deviates from the coordinates of the preset storage column 8 by more than 5cm, or when the sample label information does not match the target storage area, it is determined that the sample is misplaced. Generate a verification report that includes the type of violation, the time of the violation, related samples, and the operation trajectory.

[0035] In the above embodiments, through the collaborative operation of the end-to-end data acquisition and operation compliance verification unit, full-chain traceability and compliance control of sample operations are achieved. Sample identification information, operator information, and mechanical movement trajectories are integrated by timestamps to form a complete operation dataset, ensuring that every sample access is traceable. By comparing with a preset rule base, unauthorized access, misplaced samples, and other violations can be automatically identified, operational loopholes can be promptly discovered, operator behavior can be standardized, sample management risks caused by human error can be reduced, and a reliable basis for sample quality traceability can be provided. In scientific research experiments or medical testing scenarios, the flow path of problematic samples can be quickly located through operation records, improving the credibility and accountability of sample management.

[0036] The environmental parameter monitoring module also includes: The sample storage risk warning unit is configured as follows: Acquire the data collected by the temperature and humidity sensor group; wherein, the data collected by the temperature and humidity sensor group includes: the measured temperature value corresponding to the position of the storage column 8, and the measured humidity value corresponding to the position of the storage column 8; Based on the data collected by the temperature and humidity sensor group, the sample risk value, representing the degree of risk of failure of the sample placed in storage column 8, is calculated in real time using the following formula:

[0037] in, For the sample risk value of the stored column 8, The measured temperature value corresponding to the position in storage column 8 of the data collected by the temperature and humidity sensor group. The measured humidity value corresponding to the position in storage column 8 of the data collected by the temperature and humidity sensor group. The preset optimal storage temperature, To achieve the preset optimal storage humidity, The preset temperature critical deviation, This is the preset humidity critical deviation. The temperature and humidity at the location of storage column 8, as described historically, both exceeded […]. - , + ] Scope and [ - , + The cumulative duration within the range, For the preset time limit, , as well as The preset weight values; When the risk value of the sample in storage column 8 exceeds a preset threshold, it is determined that the degree of failure risk of the sample placed in storage column 8 exceeds the standard. In the three-dimensional model, storage column 8 is marked as a high-risk area for sample failure, so as to warn management personnel to take appropriate intervention.

[0038] The sample storage risk warning unit dynamically assesses the risk status of samples in storage column 8 using the aforementioned algorithm. This unit collects the temperature data at the corresponding location within the storage column in real time. ) and humidity ( ) Actual measured value, compared with preset optimal storage parameters ( , Deviation calculation is performed, and a critical deviation threshold is introduced. , The algorithm amplifies instantaneous fluctuations by squared terms, significantly enhancing sensitivity to short-term, drastic environmental changes; simultaneously, it overlays the historical safe duration of simultaneous temperature and humidity exceedances at that location. ) and preset time limit ( The ratio term quantifies the cumulative risk of long-term exposure, and then uses weighting coefficients ( , as well as The contribution weights of each factor are dynamically adjusted, and the final output is a quantified sample risk value. When the risk value of a sample exceeds a set threshold, the system highlights the stored column as a high-risk area in the 3D model in real time.

[0039] This mechanism transcends the limitations of traditional single-point threshold alarms, transforming discrete environmental parameters into a comprehensive prediction of sample damage potential. It accurately captures instantaneous abnormal fluctuations (such as a sudden temperature rise caused by a cooling failure) and identifies long-term chronic deviations (such as slowly exceeding humidity limits), driving managers to prioritize intervention in high-risk areas. Combined with 3D visualization, it quickly locates samples that need rescue, significantly reducing the probability of batch failures. At the same time, the continuously accumulated risk data provides a basis for optimizing storage strategies (such as adjusting sensor layout or weight allocation), forming a closed-loop optimization from risk warning to strategy iteration.

[0040] The intelligent specimen cabinet's comprehensive monitoring system also includes: The multi-level linkage response module is configured as follows: Establish an abnormal event hierarchical response matrix, which includes: first-level events and their corresponding first event response strategies, and second-level events and their corresponding second event response strategies. The first-level events include: intrusion locking events triggered by the security protection monitoring module; The first event response strategy includes: Perform the following operations simultaneously: Operation 1: Activate the real-time recording function of all cameras inside reagent refrigerator 2, and the recording range covers the sample entrance / exit 3 and the panoramic view of the main body of specimen cabinet 1; Step 2: Send an encrypted alarm message containing the intrusion coordinates, timestamp, and device lock status to the management terminal; Operation 3: Disconnect the drive power of the three-axis moving assembly 5 and the pipe-picking robotic arm, and only keep the power supply on the environmental control equipment; The secondary events include: unauthorized access or sample misplacement events identified by the operation behavior traceability module; The second event response strategy includes: Before the shovel mechanism 6 moves the sample tray 4 to the target position, the scanning mechanism performs a secondary verification of the matching degree between the sample label and the code of the storage column 8; When the verification fails, the control three-axis moving component 5 moves the sample holder 4 to the isolation temporary storage area and marks a red warning mark in the three-dimensional model.

[0041] The multi-level linkage response module constructs a graded response matrix based on the severity of events, enabling precise prevention and control of abnormal scenarios and minimizing operational interference. For the highest-risk Level 1 events (such as intrusion locking triggered by the security protection module), the system simultaneously executes a triple rigid response: immediately activating all cameras to record panoramic video to secure the chain of evidence, sending encrypted alarm information containing intrusion coordinates and timestamps to the management terminal, and cutting off the drive power of the three-axis moving component 5 and the pipe-picking robotic arm (only retaining power to environmental equipment), thus completely blocking the intruder's operation path through physical isolation. For Level 2 events (such as unauthorized access or sample misplacement identified by the operation traceability module), a secondary verification process is initiated at the critical node before the pipe-picking robotic arm transfers the sample tray 4 to the target storage column 8. The scanning mechanism compares the matching degree between the label of the sample to be stored and the code of the target storage column 8. If the verification fails, it automatically redirects to the isolation temporary storage area and marks a red warning mark in the 3D model, preventing erroneous samples from entering the formal storage column 8 and causing cross-contamination or management chaos, while also avoiding a global shutdown that would affect the normal access of other samples. This mechanism achieves precise handling of security responses through event grading: Level 1 events focus on physical isolation and evidence preservation to minimize malicious security threats; Level 2 events focus on process correction and partial disruption to maintain operational continuity while eliminating the risk of human error spreading. Encrypted alarms, 3D alerts, and operation logs further constitute a complete chain of evidence for traceability, providing data support for event retrospective and system optimization, ultimately achieving a deep balance between security control and operational efficiency.

[0042] The sample state association module includes: The status data association unit is configured as follows: The system receives historical change curves of temperature, humidity, and gas concentration in each of the eight storage columns from the environmental parameter monitoring module in real time, and simultaneously acquires sample access frequency, operation duration, and mechanical operation trajectory data recorded by the operation behavior traceability module. The three-dimensional model coordinate system of the three-dimensional construction module is invoked to associate the environmental parameter change curve with the sample operation data of the corresponding storage column 8 according to the spatial coordinates, forming a four-dimensional associated dataset containing time dimension, spatial coordinates, environmental parameters and operation behavior. The temporal correlation between changes in environmental parameters and sample operational behaviors in a four-dimensional correlated dataset is identified by a trend extraction algorithm, and event combinations with temporal correlation exceeding a preset threshold are marked. The hidden risk identification unit is configured as follows: A preset sample state influence factor matrix is ​​provided, which includes the sensitivity coefficients of different types of samples to environmental fluctuations, operation frequency thresholds, and tolerance for cumulative changes in environmental parameters. Based on the four-dimensional associated dataset and combined with the sample state influence factor matrix, the comprehensive influence value of environmental fluctuations and operational interference on samples within each storage column of 8 is calculated. When the comprehensive impact value exceeds the preset safety threshold of the corresponding sample, it is determined that there is a hidden risk. The hidden risk includes indirect risks of exceeding the threshold, such as the decrease in sample activity caused by the accumulation of small fluctuations in environmental parameters and the local environmental instability caused by frequent operations. Generate a hidden risk assessment report that includes risk storage column coordinates, associated operation records, and environmental parameter change trends; The intervention guidance unit is configured as follows: Upon receiving the implicit risk assessment report, targeted intervention measures are automatically initiated, including: Combined with the intelligent transfer and scheduling module, sample optimization storage suggestions are generated. These suggestions include transferring highly sensitive samples to storage column 8 where environmental fluctuations are less, and adjusting the centralized storage of similar samples to reduce cross-interference. Send operation prompt rules to the operation behavior traceability module to add environmental parameter current status prompts and operation duration limits for operations involving high-risk storage column 8; The 3D building module marks the storage columns 8 with different risk levels in the 3D model with gradient colors, and displays the key environmental parameters and operation records that lead to the risk. The system continuously tracks environmental parameters and operational data in the area where the sample was located after intervention. When the overall impact value returns to the preset safety threshold range, the targeted intervention measures are automatically lifted.

[0043] In the above embodiments, the state data association unit associates the historical change curves of environmental parameters with sample operation data (access frequency, duration, mechanical trajectory) according to spatial coordinates and time dimensions, forming a four-dimensional dataset containing time, space, environment, and operation. This breaks through the limitations of a single data dimension and can more comprehensively analyze the reasons why the sample state is affected. The hidden risk identification unit combines the sample state influencing factor matrix (sensitivity coefficient, operation frequency threshold, etc.) to calculate the comprehensive impact value of the sample being affected by the accumulation of small environmental fluctuations (such as long-term slight deviations in temperature and humidity) and operational interference (such as frequent access leading to local environmental instability). It accurately identifies hidden risks that do not directly exceed the threshold (such as decreased sample activity) and avoids sample failure due to the lag of traditional threshold alarms. The intervention guidance unit automatically initiates optimization measures based on the hidden risk assessment report, such as moving highly sensitive samples to areas with more stable environments, limiting the operation time in high-risk areas, and marking risk levels in the three-dimensional model. By actively adjusting storage strategies and operating procedures, the impact of risks on samples is fundamentally reduced, while guiding managers to prioritize high-risk areas and improve management efficiency.

[0044] The sample status correlation module continuously tracks environmental parameters and operational data after intervention, automatically lifting the intervention once the risk returns to a safe range, forming a closed loop of "identification-intervention-tracking-optimization". This dynamic management model not only reduces sample loss due to latent risks, but also optimizes storage layout and operational processes through accumulated correlation data, significantly improving the refined management level of large-scale sample banks and reducing long-term operating costs.

[0045] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A comprehensive monitoring system for intelligent specimen cabinets, characterized in that: The all-dimensional monitoring system is installed inside the intelligent specimen cabinet. The all-dimensional monitoring system receives the sample access command, generates a movement path based on the location of the access target, and performs access and movement of the access target. The all-dimensional monitoring system periodically collects environmental data in the intelligent specimen cabinet, which includes the measured temperature and humidity values ​​at each location in the intelligent specimen cabinet. It also monitors the preservation environment inside the intelligent specimen cabinet, calculates the sample risk value in real time to indicate the degree of failure of the samples placed at each location, identifies high-risk areas for sample failure based on changes in the preservation environment, triggers an early warning mechanism, and intervenes dynamically. The full-dimensional monitoring system records the operation records of storing and retrieving samples and verifies whether they are compliant, identifies violations and hidden risks caused by the accumulation of minor environmental fluctuations or operational interference.

2. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 1, characterized in that, The intelligent specimen cabinet includes a specimen cabinet body (1) and a reagent refrigerator (2). The specimen cabinet body (1) is located inside the reagent refrigerator (2). The front of the reagent refrigerator (2) is provided with a sample inlet / outlet (3). An automatic door and a telescopic tray are provided inside the sample inlet / outlet (3). The interior of the specimen cabinet body (1) is divided into storage columns (8) by a longitudinal partition (7). Sample trays (4) are placed in the storage columns (8).

3. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 2, characterized in that, The comprehensive monitoring system includes: The intelligent transfer scheduling module is configured as follows: After receiving the user's instruction to access the sample, the system obtains the coordinates of the target location, generates the optimal movement path, and then moves the sample of the target to access the sample based on the optimal movement path. The environmental parameter monitoring module is configured as follows: Environmental data is collected according to a preset sampling period. The environmental data is compared with a preset threshold range. When the environmental data deviates from the preset threshold range, an early warning mechanism is triggered, and environmental control equipment is activated for dynamic intervention. The security protection and monitoring module is configured as follows: Real-time monitoring of the reagent refrigerator (2) and sample inlet / outlet (3) to check for unauthorized objects entering; The operation behavior traceability module is configured as follows: Generate operation records containing time, location, operation object, and execution result; use a rule engine to perform compliance verification on the operation records and identify violations. The 3D building module is configured as follows: A three-dimensional model of the specimen cabinet body (1) is constructed by three-dimensional modeling, and the internal structure, specimen distribution and environmental parameters of the specimen cabinet body (1) are visualized based on the three-dimensional model. The sample state association module is configured as follows: By linking environmental parameters and sample operation data in real time to form a four-dimensional dataset, the hidden risks caused by the accumulation of minor environmental fluctuations and operational interference can be identified, and targeted intervention measures can be initiated.

4. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 3, characterized in that, The environmental parameter monitoring module includes: The multi-source data acquisition unit is configured as follows: By deploying temperature and humidity sensor groups, gas concentration detector arrays and pressure sensors in different areas inside the reagent refrigerator (2), environmental data is collected synchronously according to a preset sampling cycle, the collected environmental data is cached and the original dataset of environmental parameters is generated. The dynamic threshold early warning unit is configured as follows: Call the preset environmental parameter threshold matrix, which includes the upper and lower limits of temperature and humidity and the safe threshold of gas concentration for different storage areas; The original dataset of environmental parameters is compared point by point with the threshold matrix of environmental parameters, and the deviation of parameters is obtained by the deviation calculation algorithm. When the deviation exceeds the preset threshold, the early warning mechanism and adjustment signal are triggered according to the degree of deviation, the abnormal information is recorded and the audible and visual alarm device is activated, the early warning signal is sent to the management terminal at the same time, and the three-dimensional coordinates of the abnormal area are marked. The environment adaptive adjustment unit is configured as follows: Upon receiving the adjustment signal, the environmental control equipment in the corresponding area is activated; Temperature regulation is achieved through the coordinated operation of the compressor refrigeration module and the heating wire assembly, which automatically adjusts the output power according to the temperature difference; humidity regulation is achieved through bidirectional control of the dehumidifying fan and the humidifying atomizer, which adjusts the running time according to the humidity deviation. During the adjustment process, environmental parameter changes are collected in real time until the environmental data returns to the threshold range, at which point the adjustment equipment is automatically stopped and the adjustment curve is recorded.

5. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 3, characterized in that, The security protection and monitoring module includes: The multimodal intrusion detection unit is configured as follows: The infrared thermal imaging sensor array deployed inside the reagent refrigerator (2) captures the temperature field distribution image in real time, and the laser contour scanner integrated in the sample inlet / outlet (3) is activated simultaneously to generate three-dimensional contour data. The temperature field distribution image is compared with a preset environmental temperature field benchmark model to identify abnormally high temperature areas; Feature extraction is performed on the 3D contour data generated by the laser contour scanner, and it is matched with the 3D feature library of authorized objects. When the matching degree is lower than the preset threshold, it is determined that there is an unauthorized object. The coordinates of the abnormally high temperature area are correlated with the results of unauthorized object identification to generate a preliminary intrusion detection report. The dynamic protection response unit is configured as follows: Receive the initial intrusion detection report and invoke the preset risk level assessment model; The risk level assessment model calculates the invasion risk coefficient based on the volume parameters, movement speed, and distance parameters of the invading object from the sample. When the risk coefficient is in the low-risk range, the electromagnetic locking device of the sample entrance (3) is activated, and the audible and visual alarm of the local area is activated at the same time. When the risk factor is in the high-risk range, in addition to implementing low-risk response measures, the main power supply circuit of the reagent refrigerator (2) is simultaneously cut off while the power supply of the monitoring system is retained, the standby mode of the inert gas fire extinguishing device is activated, and an emergency alarm signal containing real-time video stream is sent to the security terminal. During the protection response, the location coordinates of the intruding object are updated in real time; The intrusion trajectory tracing unit is configured as follows: The motion video stream of unauthorized objects is collected by a multi-view camera array distributed inside the specimen cabinet (1); Based on the frame image sequence in the video stream, a moving target tracking algorithm is used to extract the motion trajectory parameters of unauthorized objects, including displacement vector, turning angle and motion acceleration. The motion trajectory parameters are mapped to the three-dimensional model inside the specimen cabinet to generate a visualized invasion path map; By associating timestamp information, a full trajectory dataset is constructed, including the intrusion starting point, the areas traversed, the duration of stay, and the final location.

6. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 3, characterized in that, The specimen cabinet body (1) is equipped with a three-axis moving assembly (5) on top, and a shovel mechanism (6) is provided on the three-axis moving assembly (5). A tube picking robot and a scanning mechanism are provided in the reagent refrigerator (2) near the sample inlet / outlet (3).

7. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 6, characterized in that, The operation behavior tracing module includes: The end-to-end data acquisition unit is configured as follows: It receives sample barcodes output by the scanning mechanism in real time and simultaneously collects sample electronic tag data read by the RFID detection module integrated in the tube-picking robotic arm; Obtain the operator's identity verification information, wherein the identity verification information is an authorization code; Collect real-time coordinate data of the X, Y, and Z axes of the three-axis moving component (5) and the action status signal of the shovel mechanism (6) to form a mechanical operation trajectory record; By linking and integrating sample barcodes, sample electronic tags, identity verification information, and mechanical operation trajectory records according to timestamps, a full-process dataset containing sample information, operating entities, mechanical actions, and time nodes is constructed. The operation compliance verification unit is configured as follows: The system calls a preset operation rule library, which includes sample authorized access range, mechanical operation path specifications, and sample placement correspondence verification criteria. The system compares the entire process dataset with the operation rule library item by item and identifies violations through logical verification. When the operator's identity information is detected to be outside the authorized list or outside the authorized operation scope, it is determined to be unauthorized access; When the actual placement of the sample deviates from the coordinates of the preset storage column (8) by more than 5cm, or when the sample label information does not match the target storage area, it is determined that the sample is misplaced. Generate a verification report that includes the type of violation, the time of the violation, related samples, and the operation trajectory.

8. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 4, characterized in that, The environmental parameter monitoring module also includes: The sample storage risk warning unit is configured as follows: Acquire the data collected by the temperature and humidity sensor group; wherein, the data collected by the temperature and humidity sensor group includes: the measured temperature value corresponding to the position of the storage column (8) and the measured humidity value corresponding to the position of the storage column (8); Based on the data collected by the temperature and humidity sensor group, the sample risk value, representing the degree of failure risk of the samples placed in the storage column (8), is calculated in real time using the following formula: in, The sample risk value of the stored column (8), The measured temperature value corresponding to the position of the storage column (8) in the data collected by the temperature and humidity sensor group. The measured humidity value corresponding to the position of the storage column (8) in the data collected by the temperature and humidity sensor group. The preset optimal storage temperature, To achieve the preset optimal storage humidity, The preset temperature critical deviation, This is the preset humidity critical deviation. The temperature and humidity at the location of the storage column (8) mentioned in history both exceeded [ - , + ] Scope and [ - , + The cumulative duration within the range, For the preset time limit, , as well as The preset weight values; When the sample risk value of the storage column (8) exceeds the preset threshold, it is determined that the degree of failure risk of the sample placed in the storage column (8) exceeds the standard, and the storage column (8) is marked as a high-risk area for sample failure in the three-dimensional model to warn the management personnel to take corresponding intervention.

9. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 3, characterized in that, Also includes: The multi-level linkage response module is configured as follows: Establish an abnormal event hierarchical response matrix, which includes: first-level events and their corresponding first event response strategies, and second-level events and their corresponding second event response strategies. The first-level events include: intrusion locking events triggered by the security protection monitoring module; The first event response strategy includes: Perform the following operations simultaneously: Operation 1: Activate the real-time recording function of all cameras in the reagent refrigerator (2), and the recording range covers the sample entrance (3) and the panoramic view of the specimen cabinet (1); Step 2: Send an encrypted alarm message containing the intrusion coordinates, timestamp, and device lock status to the management terminal; Operation 3: Disconnect the drive power of the three-axis moving assembly (5) and the pipe-picking robot arm, and only keep the power supply of the environmental control equipment on. The secondary events include: unauthorized access or sample misplacement events identified by the operation behavior traceability module; The second event response strategy includes: Before the shovel mechanism (6) moves the sample tray (4) to the target position, the matching degree between the sample label and the code of the storage column (8) is verified twice by the scanning mechanism; When the verification fails, the control three-axis moving component (5) moves the sample holder (4) to the isolation temporary storage area and marks a red warning mark in the three-dimensional model.

10. The all-dimensional monitoring system for the intelligent specimen cabinet as described in claim 3, characterized in that, The sample state association module includes: The status data association unit is configured as follows: Real-time reception of the temperature, humidity and gas concentration historical change curves of each storage column (8) output by the environmental parameter monitoring module, and synchronous acquisition of sample access frequency, operation duration and mechanical operation trajectory data recorded by the operation behavior traceability module; The three-dimensional model coordinate system of the three-dimensional construction module is called to associate the environmental parameter change curve with the sample operation data of the corresponding storage column (8) according to the spatial coordinates, forming a four-dimensional associated dataset containing time dimension, spatial coordinates, environmental parameters and operation behavior; The temporal correlation between changes in environmental parameters and sample operational behaviors in a four-dimensional correlated dataset is identified by a trend extraction algorithm, and event combinations with temporal correlation exceeding a preset threshold are marked. The hidden risk identification unit is configured as follows: A preset sample state influence factor matrix is ​​provided, which includes the sensitivity coefficients of different types of samples to environmental fluctuations, operation frequency thresholds, and tolerance for cumulative changes in environmental parameters. Based on the four-dimensional associated dataset and combined with the sample state influence factor matrix, the comprehensive influence value of environmental fluctuations and operational interference on the samples in each storage column (8) is calculated. When the comprehensive impact value exceeds the preset safety threshold of the corresponding sample, it is determined that there is a hidden risk. The hidden risk includes indirect risks of exceeding the threshold, such as the decrease in sample activity caused by the accumulation of small fluctuations in environmental parameters and the local environmental instability caused by frequent operations. Generate a hidden risk assessment report that includes risk storage column coordinates, associated operation records, and environmental parameter change trends; The intervention guidance unit is configured as follows: Upon receiving the implicit risk assessment report, targeted intervention measures are automatically initiated, including: By combining the intelligent transfer and scheduling module, suggestions for optimal sample storage are generated; Send operation prompt rules to the operation behavior traceability module, and add environmental parameter current status prompts and operation duration limits for operations involving high-risk storage column (8); The storage columns with different risk levels are marked with gradient colors in the 3D model using the 3D building module (8), and the key environmental parameters and operation records that lead to the risk are displayed in association. The system continuously tracks environmental parameters and operational data in the area where the sample was located after intervention. When the overall impact value returns to the preset safety threshold range, the targeted intervention measures are automatically lifted.

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