Biological laboratory abnormal event traceability method based on unified space-time data

Abstract

This application relates to a method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data, aiming to improve laboratory safety and avoid potential biohazard risks. The method includes: deploying multiple aerosol monitoring points and location monitoring devices within the laboratory to acquire aerosol concentration and staff behavior trajectory data; constructing a health status model based on aerosol concentration data under normal operating conditions, and comparing it in real time to determine whether there is a leakage risk; if a leakage risk exists, determining the key area and propagation path of the aerosol leak using monitoring data, and identifying staff whose time and area of ​​contact with the leak overlap spatiotemporally. Through multi-point monitoring and deep fusion of spatiotemporal data, this method can accurately, efficiently, and in real time trace leakage events, especially in high-level biosafety laboratories, effectively improving safety protection capabilities.

Description

Technical Field

[0001] This application relates to the field of biosafety technology, and in particular to a method, device and medium for tracing the source of abnormal events in biosafety laboratories based on unified spatiotemporal data. Background Technology

[0002] In biosafety laboratories, aerosols are considered one of the main carriers of virus leakage and spread. To prevent viruses from escaping via aerosols, existing laboratories generally deploy safety facilities such as negative pressure systems, HEPA filters, video surveillance, and access control systems to maintain environmental isolation and enable post-event traceability. However, these systems focus more on macro-level engineering protection and personnel access control, and are difficult to detect in a timely manner the risk of microscopic leakage during experimental operations.

[0003] Under the existing system, when a suspected virus leak or aerosol diffusion event occurs, managers often have to rely on video playback, access control records, and equipment alarm logs for manual comparison to determine if any abnormal operations occurred. Video data is lengthy and makes it difficult to pinpoint the exact moment of the anomaly; access control or location information only indicates whether personnel were present, but cannot link it to specific actions; and while aerosol monitoring equipment can output concentration change curves in real time, it can only indicate "whether there is an increase in abnormal particles," but cannot determine the specific source or leakage point. Therefore, once an aerosol concentration exceeds the limit alarm, managers often have to rely on experience to speculate on the location and cause of the leak afterward, lacking a rapid and accurate event tracing mechanism.

[0004] Therefore, there is an urgent need for a new technology for tracing the source of viral aerosol leaks, which can integrate and correlate aerosol concentration changes with personnel behavior, equipment operating status and experimental environment information under a unified spatiotemporal data model, and reverse the leakage source from the moment the concentration anomaly occurred, so as to achieve rapid identification, location and review of viral leakage events. Summary of the Invention

[0005] The purpose of this application is to provide a new technology for tracing the source of viral aerosol leaks. Under a unified spatiotemporal data model, it can integrate and correlate aerosol concentration changes with personnel behavior, equipment operating status, and experimental environment information, and reverse the leak source from the moment the concentration anomaly occurred, so as to achieve rapid identification, location, and review of viral leak events.

[0006] According to one aspect of this application, a method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data is provided. S10 deploys multiple aerosol monitoring points in the laboratory that are bound to key zones, and acquires aerosol concentration monitoring data of the multiple aerosol monitoring points on a unified time axis, and deploys positioning monitoring equipment to track the behavior trajectory of staff, and acquires positioning monitoring data in a unified spatial coordinate system. S20 constructs a health status model based on multiple aerosol concentration monitoring data under normal operating conditions, and compares the real-time collected aerosol concentration monitoring data with the health status model to determine whether there is a risk of leakage. If S30 is true, then the key zone where the aerosol leak is located and the propagation path are determined based on the aerosol concentration values ​​of multiple aerosol monitoring points on the same time axis. Based on the activity trajectory of the staff in the unified spatial coordinate system in the location monitoring data, the staff who have spatiotemporal intersection with the key zone where the leak is located during the leak period are selected.

[0007] In at least one embodiment of this application, the number of aerosol monitoring points deployed in each critical zone is at least one, wherein the critical zone includes at least: a high-risk operation zone, a boundary passage zone, and a ventilation collection zone. Each of the aforementioned high-risk operational areas is equipped with at least one biological experimental device, or the high-risk operational area is located within any of the aforementioned biological experimental devices; The boundary passage area is the only passage connecting the high-risk operation area with the external area; The ventilation collection area is a common channel in the laboratory's internal ventilation system used to collect exhaust gases from various areas, or the area where the main exhaust duct or filtration unit is located in the ventilation system, or the negative pressure chamber or high-efficiency filter installation area in the ventilation system with centralized aerosol treatment function, or the functional area in the ventilation system that enables the convergence of airflow from multiple areas for centralized filtration or inactivation treatment, or the door or window gap area connecting the laboratory to the outside world.

[0008] In at least one embodiment of this application, the biological experimental equipment is one or more of the following: a biosafety cabinet, a centrifuge, an animal infection control table, an animal infection isolator, a shaker, an ultrasonic homogenizer, or an autoclave. The aerosol monitoring points are located inside the operating area of ​​the biosafety cabinet, or inside the centrifuge wall or exhaust port, or inside the animal infection operating table, or in the exhaust pipe of the animal infection isolator, or in the local exhaust hood of the operating area where the oscillator or ultrasonic disruptor is located, or at the intersection of the exhaust pipe of the autoclave and the main exhaust system. The necessary passage connecting the high-risk operation area with the external area is one or more of the following: the front window grille of the biosafety cabinet, the transfer window of the animal infection isolator, the gap of the transfer window, or the two side doors of the autoclave.

[0009] In at least one embodiment of this application, the positioning monitoring device includes: a personnel positioning beacon carried by staff, and a positioning base station deployed in the laboratory; The personnel positioning beacon and positioning base station achieve sub-meter level spatial positioning through ultra-wideband or Bluetooth AOA technology; The personnel positioning beacon is one or more or a combination of miniature wireless transmitters integrated into work permits, wristbands, or protective clothing; The positioning base station is a receiving terminal that is fixedly installed in the laboratory.

[0010] In at least one embodiment of this application, the positioning monitoring device further includes: a device positioning beacon bound to the biological experimental equipment; when the personnel positioning beacon and the device positioning beacon coincide in time and space, the system automatically associates the operation relationship between the personnel and the biological experimental equipment and generates a human-machine operation mapping record; When a leakage risk is determined, the leakage period should be identified; Based on the positioning monitoring data, the activity trajectories of each staff member in a unified spatial coordinate system are obtained, and the human-machine operation mapping records corresponding to the biological experimental equipment are acquired. During the leakage period, based on the position of the biological experimental equipment in a unified spatial coordinate system, it is determined whether the activity trajectory of the staff and the biological experimental equipment meet the preset spatiotemporal intersection criteria, and candidate staff are obtained by combining the human-machine operation mapping record. Output the trajectory segments of the candidate staff and their associated human-machine operation record index.

[0011] In at least one embodiment of this application, the preset spatiotemporal criterion is that a worker enters the area within a preset radius of the biological experimental equipment for more than a preset duration. Or, during the operation of the biological experimental equipment, it maintains a continuous spatial overlap with the equipment and its operational behavior conforms to the dynamic characteristics of the equipment's operating rhythm; The dynamic characteristics include the duration of stay of staff during operation of biological experimental equipment, the frequency of movement trajectory, and the coupling degree between the equipment start-up and shutdown cycle.

[0012] In at least one embodiment of this application, in the step of determining the key area where the aerosol leak occurs and the propagation path based on the aerosol concentration values ​​of multiple aerosol monitoring points on the same time axis, The number of aerosol monitoring points is n, and the concentration value of the i-th aerosol monitoring point at sampling time t_i is denoted as T_i(t_i), where i=1…n; in determining the propagation path, a spatiotemporal interpolation algorithm is used to reconstruct the continuous field of the concentration values ​​of each concentration monitoring point, and the propagation path is determined based on the change of the spatial distribution of the continuous field over time. The continuous field is denoted as C(x,t), and the algorithm expression is: C(x,t)=sum_{i=1..n}[w_i(x,t)*T_i(t_i)], Wherein, w_i(x,t) is determined based on the spatial distance between x and the location of the i-th concentration monitoring point and the time difference between t and the sampling time t_i, and satisfies the normalization condition: sum_{i=1..n}w_i(x,t)=1.

[0013] In at least one embodiment of this application, the spatial trajectory of the propagation path is denoted as... P(t) = (x(t), y(t), z(t)); Based on the region extent of the key partitions in a unified spatial coordinate system, define the partition mapping: K(t) = Map(P(t)), Wherein, K(t) is the identifier of the key partition or the identifier of the biological experimental device; the propagation path is characterized by the time series of K(t) as a transfer chain between the key partition or the biological experimental device.

[0014] This application provides a computer device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any step of a method for tracing the source of anomalous events in a biological laboratory based on unified spatiotemporal data.

[0015] This application provides a computer storage medium storing a computer program that, when executed by a processor, implements any step in a method for tracing the source of abnormal events in a biological laboratory based on unified spatiotemporal data.

[0016] This application has the following beneficial effects: This application demonstrates the innovativeness of a comprehensive monitoring and tracing method based on unified spatiotemporal data in the field of biosafety protection in biological laboratories, particularly in aerosol leak detection and personnel behavior tracing. Through deep integration of multi-point monitoring and spatiotemporal data, it provides a precise, efficient, and real-time tracing method. These innovations can effectively improve laboratory safety and avoid potential biohazard risks, and are of significant application value, especially for high-level biosafety laboratories. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1This is a flowchart illustrating the method steps described in one embodiment of this application; Figure 2 This is a block diagram of the layout structure of the laboratory described in one embodiment of this application; Explanation of icon numbers: 100. Laboratory; 200. Critical Zone; 300. Aerosol Monitoring Point; 400. Positioning Monitoring Equipment; 210. High-Risk Operational Zone; 220. Boundary Passage Zone; 230. Ventilation Collection Zone; 410. Personnel Positioning Beacon; 420. Positioning Base Station; 430. Equipment Positioning Beacon. Detailed Implementation

[0019] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0020] Please refer to Figures 1-2 This embodiment provides a method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data. In step S10, by deploying multiple aerosol monitoring points 300 within the laboratory 100 and binding them to key zones 200 within the laboratory 100, the concentration of aerosols can be collected and monitored in real time. The locations of these aerosol monitoring points 300 are closely related to the zones of the laboratory 100, ensuring coverage of aerosol changes in key areas and enabling timely detection of potential leakage risks. Simultaneously, positioning monitoring devices 400 deployed within the laboratory 100 are responsible for tracking the movement of personnel and recording their locations in real time. By combining the monitoring data with a unified spatial coordinate system, it is ensured that all data is analyzed within the same spatiotemporal framework, thereby guaranteeing the accuracy and consistency of the data.

[0021] In step S20, a health status model based on aerosol concentrations under normal operating conditions is constructed to define the range and fluctuations of aerosol concentrations under normal laboratory conditions. Real-time aerosol concentration monitoring data is compared with this health status model. If the difference between the real-time data and the health status model exceeds the preset normal fluctuation range, a potential leakage risk is identified. This comparison process efficiently and promptly identifies abnormal changes in aerosol concentrations, thereby rapidly triggering subsequent risk assessments and emergency responses.

[0022] In step S30, once a leak risk is detected, the system analyzes the concentration values ​​of multiple aerosol monitoring points 300 on the same time axis to further determine the critical zone 200 where the leak occurred and its propagation path. This process uses spatiotemporal interpolation algorithms to reconstruct the trend of aerosol concentration changes, depicting the spatial distribution and temporal progression of the aerosol leak. Furthermore, by combining personnel location monitoring data, the system can identify personnel whose activity trajectories intersect with the critical zone 200 where the leak occurred during the leak period. This screening process not only accurately identifies the personnel involved but also provides crucial information for further investigation and preventative measures.

[0023] This embodiment effectively enhances the ability to trace the source of abnormal events in Biological Laboratory 100. By comprehensively utilizing aerosol monitoring data and personnel location monitoring data, it tracks potential leakage events within Laboratory 100 in real time and accurately locates the leakage source and related personnel. This solution, through the construction of a health status model, can promptly detect abnormal changes in aerosol concentration and, combined with spatiotemporal data, determine the leakage path and risk source, significantly improving the timeliness and accuracy of event response. Furthermore, by incorporating personnel spatiotemporal trajectory data, it ensures comprehensive monitoring of potential leakage events and precise tracing of personnel behavior, thus providing Biological Laboratory 100 with an efficient and safe solution for the prevention and tracing of abnormal events.

[0024] In a specific embodiment of this application, the method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data covers the zoning layout of the laboratory 100, the configuration of aerosol monitoring points 300, and how to monitor and trace leakage risks through these facilities. The key zones 200 within the laboratory 100 include high-risk operational zones 210, boundary passage zones 220, and ventilation collection zones 230. Each zone is equipped with corresponding aerosol monitoring points 300 according to its function and the potential risk of aerosol generation. In high-risk operational zones 210, these areas typically involve biological experimental equipment such as biosafety cabinets, centrifuges, or other equipment that may generate aerosols. At least one aerosol monitoring point 300 is deployed in each high-risk operational zone 210, and the deployment location should be selected near the equipment or near the exhaust vent where aerosol leakage may occur to ensure timely monitoring of changes in aerosol concentration. Boundary passageway 220 is the essential passage connecting the high-risk operational area 210 with the external area. Deploying aerosol monitoring points 300 in these areas helps to detect whether aerosols will leak from the high-risk area to other areas or the external environment. In the ventilation collection area 230, aerosol monitoring points 300 should be located in key positions in the ventilation system, such as main exhaust ducts, filtration units, or negative pressure chambers with centralized aerosol treatment functions, to ensure effective monitoring of aerosol concentrations in these areas and timely handling and response. The deployment of aerosol monitoring equipment should adhere to accuracy requirements, ensuring real-time monitoring of aerosol concentrations and timely reflection of leaks within laboratory 100. Parameters such as the equipment's response speed, sensitivity, and data acquisition frequency must meet laboratory 100 safety standards.

[0025] To facilitate the tracing and localization of abnormal events, aerosol monitoring data needs to be combined with personnel location data and operational information from experimental equipment. The movement trajectories of personnel are monitored in real time via location beacon devices. These devices work in conjunction with the aerosol monitoring equipment to form a unified spatiotemporal data model. When an abnormal aerosol concentration is detected, the system combines personnel activity trajectories and the operational status of experimental equipment to identify personnel potentially associated with the leak and trace the leak source based on the spatiotemporal data. Within Laboratory 100, the aerosol monitoring equipment, personnel location beacon 410, and equipment location beacon 430 use ultra-wideband or Bluetooth technology for spatial positioning, ensuring accurate recording of personnel-equipment interactions during anomalies. This data is then used for correlation analysis by the data processing system to support rapid identification and localization of leak events.

[0026] The location and number of each aerosol monitoring point 300 should be determined based on the actual conditions of Laboratory 100, taking into account airflow distribution, equipment layout, and areas where aerosols may be generated during experiments. The configuration of the aerosol monitoring points 300 should be integrated with Laboratory 100's ventilation system, aerosol handling unit, and personnel positioning system. Through spatiotemporal interpolation algorithms, the spatial distribution and trends of aerosol concentration can be reconstructed, thereby calculating the path and location of aerosol leaks. Through this series of technical means, aerosol leak events can be monitored in real time and quickly identified during experiments, providing an effective tracing and protection mechanism to ensure the safe operation of Biosafety Laboratory 100.

[0027] In a specific embodiment of this application, the method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail the deployment of different biological experimental equipment and their coordination with aerosol monitoring points 300, as well as how to trace the source of abnormal events and determine the risk of leakage through the mutual cooperation of these devices and monitoring points.

[0028] During implementation, it is first necessary to clarify the function and working principle of each type of biological experimental equipment, and, based on the layout and workflow of Laboratory 100, to deploy appropriate aerosol monitoring points 300 for each type of equipment. For example, aerosol monitoring points 300 should be deployed within the operating area of ​​a biosafety cabinet. These monitoring points should be selected inside the cabinet's working area, especially in areas where airflow may be affected, such as around exhaust vents and workbenches, to ensure timely detection of any abnormal changes in aerosol leakage. For centrifuges, aerosol monitoring points 300 should be deployed inside the centrifuge walls or at the exhaust vents. These locations are typically critical areas for aerosol release and can effectively monitor aerosols that may be released during centrifugation. If Laboratory 100 has animal infection workbenches or animal infection isolators, aerosol monitoring points 300 should be installed in the exhaust ducts of these devices to capture aerosols that may leak through the exhaust system. For equipment such as shakers and ultrasonic disruptors, aerosol monitoring points 300 can be deployed within the local exhaust hoods of their operating areas to capture aerosols that may be generated during shaking or ultrasonic disruption.

[0029] Furthermore, for autoclaves, aerosol monitoring points 300 should be installed at the intersection of their exhaust ducts and the main exhaust system, especially during high-temperature and high-pressure operation, where aerosol emissions from the equipment need to be monitored and addressed promptly. Deploying aerosol monitoring points 300 near these devices helps to capture leaked aerosols and respond promptly, ensuring the safety of the internal environment of Laboratory 100.

[0030] Within laboratory 100, the essential passageway connecting the high-risk operational area 210 to the external area is also a critical area for aerosol monitoring. Potential pathways for aerosol leakage to the outside or other areas include the front grille of biosafety cabinets, the pass-through windows of animal infection isolators, gaps in pass-through windows, and the double doors of autoclaves. Deploying aerosol monitoring points 300 in these areas allows for real-time monitoring and timely alarms during aerosol leakage from the high-risk area to the external area.

[0031] Through the detailed equipment deployment and monitoring point configuration described above, it can be ensured that changes in aerosol concentration within the laboratory 100 can be accurately captured, and by combining the spatiotemporal data of personnel and equipment, abnormal events can be quickly traced and located.

[0032] In a specific embodiment of this application, the method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail the working principle and configuration of the positioning monitoring device 400, and how to achieve high-precision personnel location tracking through positioning beacons and base stations, and combine it with the data of aerosol monitoring points 300 to trace the source of leakage events.

[0033] First, the positioning and monitoring equipment 400 within Laboratory 100 consists of two parts: personnel positioning beacons 410 and positioning base stations 420. The personnel positioning beacons 410 are miniature wireless transmitters carried by staff, typically integrated into work badges, wristbands, or protective clothing. These beacons achieve sub-meter level spatial positioning using ultra-wideband (UWB) or Bluetooth AOA (Angle of Arrival) technology. Each staff member wears such a small beacon, allowing for real-time acquisition of their precise location within Laboratory 100. The wireless transmission technology used by the beacons offers advantages such as low power consumption, high precision, and long-distance transmission, providing stable positioning services in the complex environment of Laboratory 100. The beacon's location data is transmitted to the positioning base station 420 in real time. By receiving the beacon signals, the base station calculates the staff member's three-dimensional spatial coordinates, ensuring that their movement trajectory within Laboratory 100 is accurately recorded.

[0034] Secondly, the positioning base station 420 is a fixed receiving terminal deployed within laboratory 100, typically working in conjunction with the personnel positioning beacon 410. The base station receives signals from the personnel positioning beacon 410 and performs calculations to obtain the precise location of the personnel. The positioning base station 420 can employ ultra-wideband (UWB) or Bluetooth AOA technology, which provides sub-meter level positioning accuracy, ensuring that the activity location and path of each personnel within laboratory 100 can be accurately tracked. The base stations are typically distributed in key areas of laboratory 100, such as the high-risk operation area 210, the ventilation collection area 230, and areas closely related to aerosol monitoring equipment. These base stations ensure coverage of the entire laboratory 100 space, enabling full-process tracking of personnel.

[0035] Personnel positioning beacon 410 and positioning base station 420 are connected wirelessly to ensure that the beacon's location data can be transmitted to the central data processing system in real time. During the experiment, the system will update the spatial coordinates of the personnel in real time and integrate them with aerosol monitoring data, equipment operation data, etc., so that in the event of an aerosol leak, the source of the leak and the potentially affected areas can be quickly identified through spatiotemporal data correlation.

[0036] Furthermore, the choice of beacon and base station technologies (such as ultra-wideband or Bluetooth AOA) can effectively avoid interference from metal equipment or other electronic devices within the laboratory, ensuring positioning accuracy in complex environments. The personnel positioning beacon 410 can be miniaturized to reduce the burden on staff and can be integrated with other personal protective equipment (such as work badges, wristbands, or protective clothing) for easy wear by staff.

[0037] Through the configuration and working principle of these positioning and monitoring devices 400, it is possible to accurately locate personnel within the laboratory 100 and coordinate with the data from aerosol monitoring devices in real time to provide accurate spatiotemporal data support for tracing the source of leakage events.

[0038] In a specific embodiment of this application, the method for tracing abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail how the operation relationship between staff and experimental equipment is established through the cooperation of equipment positioning beacons 430 and personnel positioning beacons 410, and how, when a leakage event occurs, staff related to the leakage event are screened out through spatiotemporal data analysis.

[0039] First, in laboratory 100, the positioning monitoring device 400 includes device positioning beacons 430, which are linked to biological experimental equipment. For example, biosafety cabinets, centrifuges, and animal infection control tables are all equipped with device positioning beacons 430. These device positioning beacons 430, combined with personnel positioning beacons 410, can capture the relative positions of the equipment and personnel in real time. When the personnel positioning beacon 410 carried by a personnel coincides with the device positioning beacon 430 in time and space, the system automatically associates the personnel's operational relationship with the biological experimental equipment and generates a human-machine operation mapping record. This record will record the interaction between the personnel and the equipment, such as whether the personnel are operating the equipment, the duration of the operation, and the specific content of the operation.

[0040] When the system determines that there is a leakage risk, it will use aerosol concentration data and a health status model to determine the time period of the leak and define the time frame of the leak event. Determining this time frame is crucial for subsequent personnel screening. Based on location monitoring data, the system will obtain the activity trajectories of each worker within a unified spatial coordinate system and combine this with the human-machine interface mapping records of the equipment to further screen out workers associated with the leak event.

[0041] After determining the leakage period, the system analyzes the spatiotemporal trajectory of personnel based on the spatial location of the biological experimental equipment to determine whether the personnel's trajectory meets preset spatiotemporal intersection criteria with the equipment's spatial location. Specifically, the preset spatiotemporal intersection criteria may include whether the personnel entered the equipment's operating area, maintained continuous spatial overlap with the equipment during its operation, and whether their operational behavior conforms to the dynamic characteristics of the equipment's operating rhythm (such as the equipment's start-stop cycle and operation duration). When the personnel's trajectory meets these conditions, the system considers that the personnel may be associated with the leakage event.

[0042] By combining human-machine interaction mapping records, the system will identify candidate personnel—those whose work was closely related to the operation of the experimental equipment during the leakage period. The system will output activity trajectory fragments of the candidate personnel, presented along with their corresponding human-machine interaction record index. This information provides crucial clues for subsequent investigations, helping laboratory 100 managers accurately identify the potential source of the leak and possible responsible personnel.

[0043] The core of this method lies in combining equipment location beacon 430, personnel location beacon 410, and aerosol monitoring data to achieve precise tracing of leak events using spatiotemporal data analysis technology. By establishing a close connection between personnel and equipment operation, the system can not only identify the spatiotemporal context of the leak event but also help managers quickly locate personnel related to the event, thereby improving the efficiency and accuracy of event response.

[0044] In a specific embodiment of this application, the method for tracing abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail how to use spatiotemporal criterion to determine whether there is a spatiotemporal intersection between the operation of personnel and biological experimental equipment, and further screen out personnel related to the leakage event, by combining the spatial and temporal relationship between personnel and biological experimental equipment.

[0045] During implementation, it is first necessary to establish a preset spatiotemporal criterion for determining whether the interaction between personnel and biological experimental equipment is relevant within the timeframe of the leak event. Specifically, the spatiotemporal criterion has two possible scenarios: First, the criteria for determining eligibility is that personnel enter the area surrounding the biological experimental equipment within a preset radius and remain there for a preset duration. This preset duration can be set based on the equipment's operational requirements, experimental safety standards, and operating cycle. This criterion applies to situations where personnel enter the equipment's operating area and remain there for a certain period before or during equipment operation. The system tracks the personnel's location beacons to detect whether they have entered the designated area around the biological experimental equipment and determines whether they meet the spatiotemporal intersection criteria based on the duration of their stay in that area.

[0046] Second, staff maintain continuous spatial overlap with the biological experimental equipment during its operation, and their operational behavior conforms to the dynamic characteristics of the equipment's operating rhythm. The equipment's operating rhythm includes its start-up and shutdown cycle, operation duration, and operation frequency. Whether the staff's operational behavior matches the equipment's operating cycle can be determined through the following dynamic characteristics: Dwell time: This refers to the amount of time a worker spends in the area surrounding the equipment. If a worker remains in the operating area of ​​the equipment for an extended period during startup or operation, it indicates a strong correlation between the worker's actions and the equipment's operation.

[0047] Movement frequency: This refers to the frequency of worker movement during equipment operation. Frequent movement around the equipment may indicate that the worker has made some manual adjustments or interventions during equipment operation.

[0048] The coupling degree of equipment start-up and shutdown cycles: This refers to the correlation between the operator's operational trajectory and the equipment start-up and shutdown cycles. For example, whether the operator's actions are synchronized with the equipment's start-up, shutdown, and adjustment actions reflects whether the operator is performing relevant operations or maintenance during equipment operation.

[0049] By utilizing these dynamic characteristics, the system can determine whether the activities of personnel are closely related to the operation of the equipment, thereby identifying whether their activities intersected with the equipment operation in time during the period of the leak. If the personnel's activity trajectory matches the dynamic characteristics of the equipment operation, it indicates that the personnel may have a direct relationship with the occurrence of the leak.

[0050] In practice, the system collects personnel location data and equipment operation data in real time, and analyzes them in conjunction with spatiotemporal conditional criteria. Through this method, the system can accurately identify personnel associated with leaks, ensuring that leaks can be tracked and located in a timely manner.

[0051] The implementation of the air-to-machine criterion at this time allows the system to consider not only the spatial location of personnel when tracing the source of leakage events, but also the operating cycle of the equipment and the dynamics of the personnel's operating behavior, further improving the accuracy of the source tracing and the accuracy of the event tracking.

[0052] In a specific embodiment of this application, the method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail how to use a spatiotemporal interpolation algorithm to reconstruct the data of aerosol monitoring points 300, and based on the reconstruction result, determine the key partition 200 where the aerosol leak is located and its propagation path.

[0053] In the implementation process, firstly, the number of aerosol monitoring points 300 is n, meaning that multiple aerosol monitoring points 300 are deployed within laboratory 100. These monitoring points collect aerosol concentration data at different locations and times. At each aerosol monitoring point 300i, its concentration value at sampling time t_i is denoted as T_i(t_i), where T_i(t_i) is the specific data on the change of aerosol concentration over time. Aerosol monitoring points 300 can be deployed in various key areas of laboratory 100, such as high-risk operational area 210, boundary passage area 220, and ventilation collection area 230, etc. Each monitoring point can provide real-time feedback on the aerosol concentration changes within its corresponding area.

[0054] Determining the critical zone 200 of the aerosol leak and its propagation path requires the use of a spatiotemporal interpolation algorithms. The purpose of these algorithms is to reconstruct a continuous field of aerosol concentration throughout the entire laboratory 100 using collected aerosol concentration data (T_i(t_i)) based on spatial location and temporal variations. This continuous field helps determine the aerosol propagation path and analyze the temporal and spatial characteristics of the leak event.

[0055] The core idea of ​​the spatiotemporal interpolation algorithm is to combine data from each aerosol monitoring point (300) with data from other monitoring points, and generate a continuous aerosol concentration distribution model through spatial and temporal interpolation. The specific algorithm expression is as follows: C(x,t)=sum_{i=1..n}[w_i(x,t)*T_i(t_i)] Where C(x,t) represents the aerosol concentration at any spatiotemporal coordinate (x,t), w_i(x,t) is a weighting coefficient representing the influence of the i-th aerosol monitoring point 300 at spatiotemporal coordinate (x,t), and T_i(t_i) is the concentration value of the i-th aerosol monitoring point 300 at sampling time t_i. The weighting coefficient w_i(x,t) is determined by both spatial distance and time difference. Specifically, the weight w_i(x,t) decreases as the distance between the aerosol monitoring point 300 and the spatiotemporal point (x,t) increases, and also decreases as the time difference increases. This ensures that closer monitoring points and closer time sampling data have a greater impact on the reconstruction of the continuous field.

[0056] At the same time, the weighting coefficients w_i(x,t) must satisfy the normalization condition, that is: sum_{i=1..n}w_i(x,t)=1 This condition ensures that the aerosol concentration at each spatiotemporal point is obtained by weighted averaging of the concentration data from all monitoring points, thus avoiding deviations in the calculation results.

[0057] The continuous field C(x,t) calculated using a spatiotemporal interpolation algorithm can represent the aerosol concentration distribution at different times and spatial points within Laboratory 100. Based on this continuous field data, the aerosol propagation path can be further analyzed. The propagation path is determined by observing the changes in spatial distribution over time, i.e., by observing the changes in aerosol concentration at different time points, thereby inferring the aerosol propagation trajectory and leakage source.

[0058] During implementation, spatiotemporal interpolation algorithms can be implemented using numerical simulation methods or interpolation software tools based on existing aerosol monitoring data. These tools will automatically calculate the spatial distribution of aerosol concentration based on the specific layout of laboratory 100 and the location of aerosol monitoring points 300, and further estimate the leakage path.

[0059] Using the above spatiotemporal interpolation algorithm, the system can accurately determine the leakage source and propagation path of aerosols within 100 laboratory hours, providing strong data support for rapid response and source tracing of leakage events.

[0060] In a specific embodiment of this application, the method for tracing the source of abnormal events in a biological laboratory 100 based on unified spatiotemporal data describes in detail how to trace and track aerosol leakage events by mapping the spatial trajectory of the propagation path and the key partition 200.

[0061] First, the spatial trajectory P(t) of the propagation path is defined as three-dimensional spatial coordinates (x(t), y(t), z(t)), representing the change of the aerosol propagation trajectory over time. Specifically, P(t) is the spatial distribution of aerosol concentration over time, recording the propagation trajectory of the aerosol within laboratory 100 over time. This trajectory reflects the diffusion path of the aerosol within laboratory 100 and can help determine the leak source and the aerosol diffusion process. The continuous field C(x,t) obtained through spatiotemporal interpolation can be used to calculate the spatial trajectory P(t) of the aerosol, thereby determining the position of the aerosol at different time points.

[0062] Next, based on a unified spatial coordinate system, each key zone 200 within laboratory 100 (such as the high-risk operational zone 210, boundary passage zone 220, and ventilation collection zone 230) has a clearly defined spatial extent. During implementation, the area extent of each key zone 200 needs to be defined within the unified spatial coordinate system. The extent of each zone can be determined by aerosol monitoring points 300 within that area, and based on the data from these monitoring points, it can be determined whether the aerosol propagation path passes through these areas.

[0063] For ease of analysis, the partition mapping K(t) is defined as Map(P(t)), representing the correspondence between aerosol propagation paths and key partitions 200 within laboratory 100. K(t) is a dynamic mapping that associates aerosol propagation paths with key partitions 200 or biological experimental equipment within laboratory 100. In this mapping, K(t) may be an identifier for a key partition 200 or an identifier for a biological experimental equipment, depending on whether the aerosol propagation path passes through a specific device or area.

[0064] The time series of the K(t) mapping can be used to describe how aerosols migrate over time from one critical partition 200 to another, or from one biological experimental device to another. This process essentially tracks the transfer of aerosols from one area or device to another. By analyzing the K(t) time series, the system can determine whether aerosols leaked from a specific device or area and can clarify the propagation path of aerosols within laboratory 100.

[0065] Specifically, the time series of K(t) forms a "transfer chain," meaning that aerosols can move from one area to another, or from one device to another, within the laboratory, until they are eventually treated or eliminated. By observing this transfer chain, managers can monitor the aerosol propagation process in real time, identify the source of the leak, and quickly locate the affected area or device when a leak occurs.

[0066] To achieve this, the system needs to use spatial positioning technology and spatiotemporal interpolation algorithms to correlate the spatial distribution of aerosol concentration with the area range of each key partition 200 in the laboratory. By monitoring the aerosol propagation path, a dynamic K(t) mapping record is formed. This mapping not only reflects the dynamics of aerosol propagation in real time but also provides rich spatiotemporal data support for the analysis of leak events.

[0067] Using the methods described above, the system can accurately track the propagation path of aerosols within laboratory 100, and through the mapping of key zones 200 and the analysis of transfer chains, it can help laboratory 100 managers detect leaks in a timely manner and ensure the biosafety of laboratory 100.

[0068] This specific embodiment also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0069] This specific embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0070] The computer device can be a terminal or a server. It includes a processor, memory, and a network interface connected via a system bus. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and may also store computer programs, which, when executed by the processor, enable the processor to implement methods. The internal memory may also store computer programs, which, when executed by the processor, enable the processor to perform methods. Those skilled in the art will understand that the structures shown in the figures are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0071] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0072] Therefore, this application demonstrates the innovation of a comprehensive monitoring and tracing method based on unified spatiotemporal data in the field of biosafety laboratory 100, particularly in aerosol leak detection and personnel behavior tracing. Through deep integration of multi-point monitoring and spatiotemporal data, it provides a precise, efficient, and real-time tracing method. These innovations can effectively improve the safety of laboratory 100 and avoid potential biohazard risks, especially for high-level biosafety laboratories 100, which have significant application value.

[0073] The embodiments described above are merely examples of several implementations of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data, characterized in that, S10 deploys multiple aerosol monitoring points in the laboratory that are bound to key zones, and acquires aerosol concentration monitoring data of the multiple aerosol monitoring points on a unified time axis, and deploys positioning monitoring equipment to track the behavior trajectory of staff, and acquires positioning monitoring data in a unified spatial coordinate system. S20 constructs a health status model based on multiple aerosol concentration monitoring data under normal operating conditions, and compares the real-time collected aerosol concentration monitoring data with the health status model to determine whether there is a risk of leakage. If S30 is true, then the key zone where the aerosol leak is located and the propagation path are determined based on the aerosol concentration values ​​of multiple aerosol monitoring points on the same time axis. Based on the activity trajectory of the staff in the unified spatial coordinate system in the location monitoring data, the staff who have spatiotemporal intersection with the key zone where the leak is located during the leak period are selected.

2. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 1, characterized in that, The number of aerosol monitoring points deployed in each key zone is at least one, wherein the key zone includes at least: a high-risk operation zone, a boundary passage zone, and a ventilation collection zone; Each of the aforementioned high-risk operational areas is equipped with at least one biological experimental device, or the high-risk operational area is located within any of the aforementioned biological experimental devices; The boundary passage area is the only passage connecting the high-risk operation area with the external area; The ventilation collection area is a common channel in the laboratory's internal ventilation system used to collect exhaust gases from various areas, or the area where the main exhaust duct or filtration unit is located in the ventilation system, or the negative pressure chamber or high-efficiency filter installation area in the ventilation system with centralized aerosol treatment function, or the functional area in the ventilation system that enables the convergence of airflow from multiple areas for centralized filtration or inactivation treatment, or the door or window gap area connecting the laboratory to the outside world.

3. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 2, characterized in that, The biological experimental equipment is one or more of the following: biosafety cabinet, centrifuge, animal infection operating table, animal infection isolator, oscillator, ultrasonic homogenizer or autoclave. The aerosol monitoring points are located inside the operating area of ​​the biosafety cabinet, or inside the centrifuge wall or exhaust port, or inside the animal infection operating table, or in the exhaust pipe of the animal infection isolator, or in the local exhaust hood of the operating area where the oscillator or ultrasonic disruptor is located, or at the intersection of the exhaust pipe of the autoclave and the main exhaust system. The necessary passage connecting the high-risk operation area with the external area is one or more of the following: the front window grille of the biosafety cabinet, the transfer window of the animal infection isolator, the gap of the transfer window, or the two side doors of the autoclave.

4. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 3, characterized in that, The positioning and monitoring equipment includes: personnel positioning beacons carried by staff and positioning base stations deployed in the laboratory; The personnel positioning beacon and positioning base station achieve sub-meter level spatial positioning through ultra-wideband or Bluetooth AOA technology; The personnel positioning beacon is one or more or a combination of miniature wireless transmitters integrated into work permits, wristbands, or protective clothing; The positioning base station is a receiving terminal that is fixedly installed in the laboratory.

5. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 4, characterized in that, The positioning and monitoring equipment also includes: an equipment positioning beacon bound to the biological experimental equipment; when the personnel positioning beacon and the equipment positioning beacon coincide in time and space, the system automatically associates the operation relationship between the personnel and the biological experimental equipment and generates a human-machine operation mapping record; When a leakage risk is determined, the leakage period should be identified; Based on the positioning monitoring data, the activity trajectories of each staff member in a unified spatial coordinate system are obtained, and the human-machine operation mapping records corresponding to the biological experimental equipment are acquired. During the leakage period, based on the position of the biological experimental equipment in a unified spatial coordinate system, it is determined whether the activity trajectory of the staff and the biological experimental equipment meet the preset spatiotemporal intersection criteria, and candidate staff are obtained by combining the human-machine operation mapping record. Output the trajectory segments of the candidate staff and their associated human-machine operation record index.

6. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 5, characterized in that, The preset spatiotemporal condition criterion is that the staff member enters the area within a preset radius of the biological experimental equipment for a preset duration. Or, during the operation of the biological experimental equipment, it maintains a continuous spatial overlap with the equipment and its operational behavior conforms to the dynamic characteristics of the equipment's operating rhythm; The dynamic characteristics include the duration of stay of staff during operation of biological experimental equipment, the frequency of movement trajectory, and the coupling degree between the equipment start-up and shutdown cycle.

7. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 6, characterized in that, In the step of determining the key area where the aerosol leak occurred and the propagation path based on the aerosol concentration values ​​of multiple aerosol monitoring points on the same time axis, The number of aerosol monitoring points is n, and the concentration value of the i-th aerosol monitoring point at sampling time t_i is denoted as T_i(t_i), where i=1…n; in determining the propagation path, a spatiotemporal interpolation algorithm is used to reconstruct the continuous field of the concentration values ​​of each concentration monitoring point, and the propagation path is determined based on the change of the spatial distribution of the continuous field over time. The continuous field is denoted as C(x,t), and the algorithm expression is: C(x,t)=sum_{i=1..n}[w_i(x,t)*T_i(t_i)], Wherein, w_i(x,t) is determined based on the spatial distance between x and the location of the i-th concentration monitoring point and the time difference between t and the sampling time t_i, and satisfies the normalization condition: sum_{i=1..n}w_i(x,t)=1.

8. The method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data according to claim 7, characterized in that, The spatial trajectory of the propagation path is denoted as P(t)=(x(t),y(t),z(t)); Based on the region extent of the key partitions in a unified spatial coordinate system, define the partition mapping: K(t) = Map(P(t)), Wherein, K(t) is the identifier of the key partition or the identifier of the biological experimental device; the propagation path is characterized by the time series of K(t) as a transfer chain between the key partition or the biological experimental device.

9. A computer device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as described in any one of claims 1 to 8.

10. A computer storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 8.

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