38 results about "Lab management" patented technology

The invention provides a laboratory detection task intelligent allocation method and system based on big data, and relates to the technical field of laboratory management, and the method comprises the steps: collecting detection task data, carrying out the detachable analysis to construct a collaborative flow chart, calculating a collaborative efficiency index and a task priority, and extracting personnel collaboration features to generate an association weight matrix; and allocating task queues by adopting a double-layer adaptive task allocation algorithm, performing density peak clustering on the first layer to divide task clusters, and optimizing an allocation scheme in combination with personnel ability and cooperative affinity on the second layer. According to the invention, the distribution efficiency and cooperation quality of complex laboratory detection tasks are improved.

The invention discloses a laboratory intelligent management and remote review system, and relates to the field of laboratory management, and the system comprises a standard atlas database construction module which is used for generating a standard process atlas of various sample detection tasks; the sample process map generation module is used for collecting actual operation processes of experimenters and generating map representation; the anomaly detection module is used for carrying out structure comparison on the actual process map and the standard process map and identifying an abnormal process path; the abnormal graph learning module is used for classifying the abnormal process graph into an abnormal graph library and carrying out clustering and labeling processing; the abnormal evolution prediction and early warning module is used for predicting a process evolution trend based on a graph neural network model and giving out an early warning when the process evolution trend deviates from a standard; and the remote review intelligent auxiliary module is used for generating a structured review report. According to the method, structured modeling of the laboratory process, inductive precipitation of the abnormal mode and prospective early warning of the process risk are realized.

The invention discloses a laboratory management and control scheduling system and method, and belongs to the field of laboratory management, and the system comprises an Internet of Things equipment monitoring module, a cloud computing resource scheduling module, an experiment task distribution and progress monitoring module, a data analysis and report generation module, an early warning and exception handling module, and a data security and privacy protection module. Through linkage of the cloud computing resource scheduling module and the experiment task allocation module, accurate matching of equipment, personnel and tasks is realized through an intelligent algorithm, the tasks are automatically allocated based on equipment loads and personnel skills, a scheduling plan can be dynamically adjusted according to real-time progress, the problems of resource idleness and task backlog are solved from the source, and the task scheduling efficiency is improved. The cooperative effects of efficient equipment operation, personnel load balance and ordered task promotion are achieved; equipment and environment data are collected in real time through the Internet of Things equipment monitoring module, and the early warning and exception handling module synchronously monitors and responds to exceptions.

A wireless environment parameter monitoring node system based on Bluetooth MESH networking belongs to the technical field of wireless self-organizing sensor network structures, and comprises a laboratory environment monitoring network formed by a plurality of nodes through a Bluetooth MESH self-organizing network; each node is composed of a digital environment parameter sensor module, an electronic paper display module, a lithium battery module, a power management module, a Bluetooth MESH communication module and a master control module, and the master control module is in bidirectional communication connection with the digital environment parameter sensor module, the electronic paper display module, the power management module and the Bluetooth MESH communication module. The lithium battery module is bidirectionally connected with the power management module, and the power management module is connected with the digital environment parameter sensor module. The laboratory environment monitoring system has the characteristics of low cost, small size, low power consumption and the like, can complete large-area multi-laboratory environment monitoring tasks through multi-node networking, is an effective supplement for existing manual reading and single-machine environment monitoring equipment, and conforms to digital scene application of laboratory management system authentication.

1. The name of the design product: electronic device research and development experiment management graphical user interface. 2. The use of the design product: an electronic device. 3. The design points of the design product: the interface content in the graphical user interface. 4. The picture or photo that best shows the design points: front view. 5. The product carrier is the conventional design, and the rear view, left view, right view, top view, and bottom view are omitted. 6. The use of the graphical user interface: graphical user interface for research and development experiment management system. 7. Other circumstances that need to be explained: the front view is the task list interface of the research and development experiment management system. Clicking "+" experiment design" in the interface enters the change state diagram 1 task addition interface. The interface pops up the task information setting pop-up window. Fill in the relevant information in the pop-up window. Click the "experiment template" addition icon (the icon with a magnifying glass on the right side of the experiment template input box) to enter the change state diagram 2 task template addition interface. The interface pops up the experiment template selection pop-up window. The left side of the pop-up window is the template display area, and the middle is the process node display area. After selecting the required template in the template display area, the corresponding task node is generated in the process node display area. Click any node in the process node display area to enter the change state diagram 3 node information interface. The right side of the interface is the node editing area. Click "add group" in the area to enter the change state diagram 4 group setting interface. The interface pops up the "edit group" pop-up window. After setting the relevant parameters in the pop-up window, click "OK" to enter the change state diagram 5 complete group setting. Click "group design" in the change state diagram 5 under the three small dot icons on the right side of the group design bar to enter the change state diagram 6. The interface pops up the "material calculation" pop-up window. After setting the relevant parameters in the pop-up window, click "generate data" to enter the change state diagram 7. Click "preference settings" in the change state diagram 7 to enter the change state diagram 8. The interface pops up the execution mode setting pop-up window. Click "OK" after selecting "detailed view" in the pop-up window to enter the change state diagram 9 detailed mode experiment execution.

The invention discloses a data analyzer for intelligent laboratory data analysis, and relates to the technical field of intelligent laboratory analysis, the data analyzer comprises an experiment box body, an experiment data acquisition module is arranged in the experiment box body, an experiment platform is arranged at the front end of the experiment data acquisition module, and a data interaction platform is arranged outside the experiment box body; a data processing system is arranged between the experimental data acquisition module and the data interaction platform; according to the data analyzer for intelligent laboratory data analysis, a desktop six-axis AI visual robot is used for autonomously recognizing an original instrument display window and preprocessing collected image data, and the robot can obtain feedback information in real time and adjust and optimize the feedback information according to needs until variable data become static data; data information is read, data interconnection with a laboratory management system can be carried out through a modem, collected data are uploaded in real time, and data are archived and analyzed.

The invention discloses a shipborne laboratory information management method and system supporting marine geological scientific investigation, and relates to the field of ship digital design. The shipborne experimental method supporting marine geological scientific investigation comprises the steps of core and sample management, voyage number and experimental business process management, experimental resource and environment management, experimental data acquisition and management, and comprehensive data and file management visualization. Scientific and intelligent management and application of shipborne core library and laboratory management are realized by using a modern informatization technology. According to the shipborne experimental method supporting marine geological scientific investigation, management and application such as warehousing, ex-warehouse, borrowing, observation, sampling and gathering of physical samples are more scientific and normative, and integration of laboratory analysis business process, resource and personnel management is realized; the problems of confusion of rock core samples, separation of samples and data, disordered rock core detection progress, incapability of tracking working rock core positions and difficulty in searching archived rock cores which are easily caused by adopting a manual recording mode are solved.

1. Name of the product in this design: Graphical User Interface for Laboratory Intelligent Management Platform of Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key points: Design 2 main view. 5. Design 2 is designated as the basic design. 6. Purpose of the graphical user interface: It is used by users to view and operate equipment, environment, and safety management in the laboratory management platform. 7. Human-computer interaction method of graphical user interface: The main view of Design 1 is the main interface of the equipment management platform. Clicking "VAV" (variable air volume) (control cabinet) in the main view of Design 1 will enter the change status diagram of the Design 1 interface; The main view of Design 2 is the main interface of the environmental management platform. Clicking any air pressure value in the middle of the interface in the main view of Design 2 will enter the change status diagram of the Design 2 interface; The main view of Design 3 is the main interface of the safety management platform. Different floors can be selected to view equipment, and the equipment name can be entered to click to query the equipment. 8. Other situations requiring explanation: Other explanation: "X" in the interface represents text.

The invention discloses an intelligent laboratory management system for fusion graph machine learning, and the system comprises a data layer which is configured to store data related to laboratory management and comprises a business database, a process database, an instrument state database and a knowledge graph database; the AI middle table layer is connected with the data layer and comprises a graph machine learning engine and a reinforcement learning engine; the application layer is connected with the AI middle table layer and is used for calling the service of the AI middle table layer to realize a laboratory service function; and the user layer is connected with the application layer and is used for providing an interactive interface for users of different roles. According to the invention, the AI capability is embedded into the laboratory management process by constructing the machine learning and reinforcement learning of the intelligent platform fusion graph, so that the multi-source data integration and mining are realized, and the information isolated island is effectively broken; resource configuration is optimized through dynamic scheduling, and the operation efficiency is improved; by means of active risk prediction and propagation analysis, early risk identification and intelligent management and control are realized, and automation, intelligence and optimization levels of laboratory management are further improved.

The present invention discloses a laboratory safety anomaly prediction system based on big data, comprising a raw data acquisition module, a data optimization module, an abnormal sample compensation module, a safety anomaly prediction model construction module, and a laboratory safety anomaly prediction module. The present invention relates to the field of laboratory management data processing technology, and specifically to a laboratory safety anomaly prediction system based on big data. This solution innovatively designs an abnormal sample compensation module, achieving structured and conditional supplementation of scarce abnormal samples; innovatively introduces laboratory identity feature vectors, achieving personalized risk identification and accurate prediction at the laboratory personnel level; innovatively designs a conditional Wasserstein distance adversarial objective function based on laboratory identity feature vectors, significantly improving the authenticity and diversity of synthetic abnormal samples; and innovatively designs an identity safety risk prediction loss function, improving the model's prediction accuracy in complex dynamic laboratory environments.

The invention relates to the field of artificial intelligence engineering, in particular to a laboratory equipment management method based on artificial intelligence, and the method comprises the steps: obtaining course plan data and equipment historical task record data through collection, and generating an equipment use feature vector table according to the course plan data and the equipment historical task record data; according to the method, course planning data are collected to extract course features, equipment state indexes are analyzed in combination with equipment historical records, and a multi-dimensional feature vector table is constructed to realize accurate equipment scheduling; a dynamic scheduling graph is constructed based on equipment performance, time concurrency and cost risk constraints, and a genetic algorithm is adopted to optimize and generate an optimal scheduling strategy; the equipment state is monitored through real-time sensor data, the strategy is dynamically adjusted according to the abnormal index, efficient utilization and risk management and control of equipment resources are achieved, laboratory management is promoted to be converted from a traditional manual mode to intelligent and digital modes, the equipment utilization rate and management efficiency are remarkably improved, and the operation cost is reduced.

The invention discloses an intelligent filling laboratory management method and system, electronic equipment and a medium, and aims to quantitatively evaluate the pollution risk between filling tasks through a preset filling equipment pollution risk evaluation model, so as to provide a reliable reference for the sorting of the filling tasks and the selection of a cleaning strategy during the switching of the filling tasks. For a multi-task situation, dynamic prediction of a long-term pollution risk and influence of chain transmission of pollution are realized, improvement of the operation efficiency of a filling laboratory is facilitated, a scheduling target is expanded from a single time dimension to a double dimension of time efficiency and pollution risk control, and the scheduling efficiency of the filling laboratory is improved. And a comprehensive technical solution is provided for intelligent management of the liquid food filling laboratory.

This invention discloses a laboratory anomaly identification and autonomous response system based on machine vision, belonging to the field of intelligent laboratory monitoring technology. The system includes a data acquisition layer, a feature extraction layer, an intelligent analysis layer, a decision execution layer, and a digital twin layer. The data acquisition layer collects laboratory video streams and physical sensor data; the feature extraction layer uses a multi-task learning framework to extract multimodal features; the intelligent analysis layer identifies anomalies based on multimodal features and generates handling strategies, incorporating a causal structure learning mechanism and an anomaly hierarchical handling mechanism; the decision execution layer executes corresponding remedial operations; and the digital twin layer constructs a digital twin model corresponding to the physical laboratory and synchronizes status information in real time. This invention achieves accurate identification and autonomous response to laboratory anomalies, improving the intelligence level and operational safety of laboratory management.

The invention provides an intelligent control and decision-making method based on an intelligent laboratory data cockpit. The intelligent control and decision-making method comprises the following sub-steps: S1, constructing a visual three-dimensional laboratory model based on digital twinning; s2, collection, storage, preprocessing and semantic modeling of laboratory full-dimension data; s3, deploying and training a large language model LLM adaptive to a laboratory scene, generating a decision and replying by using a natural language; on the basis of technologies such as digital twinning, a large language model and AI-agent, the efficiency and the intelligent level of laboratory management are greatly improved through an intelligent control and decision-making method; seamless butt joint of the subsystems is realized by constructing a unified data middle station; information in the laboratory can be collected in real time and concentrated to the data platform, so that the operation of the laboratory is more efficient and transparent; based on introduction of a large language model LLM and an AI-agent technology, interaction with a user is carried out, and an intelligent decision is generated according to real-time data.

The invention provides an experimental result automatic generation management system comprising an MES system module used for managing the whole experimental process and automatically generating an experimental result; the file management module is used for selecting a file storage path before an experiment and storing the physical property data in a specified path for subsequent experiments; the experimental information input module is used for inputting experimental information into a computer after the tensile test is finished and storing the experimental information into a database; the experiment result generation module is used for automatically generating an experiment result according to the experiment data and the input experiment information; and the experiment result uploading module is used for uploading the experiment result to the laboratory management board in real time to ensure the timeliness and accuracy of the data. The invention provides an experiment result automatic generation management system, and solves the problems that the process of selecting a file storage path and inputting experiment information before an experiment is tedious, the file storage path needs to be manually stored in a folder, and data management and updating are not facilitated.

The application provides a kind of wisdom campus management method and system, belong to wisdom campus technical field, method includes: through acquisition module, cumulative boot duration and single continuous running duration are obtained from laboratory equipment, and project switching frequency is obtained from registration terminal, time period is divided according to equipment start-stop time node, and equipment running cycle list is obtained;For the equipment number belonging to the abnormal high value cluster, obtain the historical experiment time period record from the registration terminal, rearrange the record using the time period reorganization method, and determine the optimized experiment time period arrangement table;Update the dispatch table of laboratory management system through the experiment time period arrangement table, obtain the updated dispatch table content, evaluate the improvement of effective experiment time, and obtain the final evaluation result of the all-day available duration of the equipment. Significantly improve the all-day available duration of the equipment, reduce unnecessary loss.

The invention provides an intelligent campus management method and system, and belongs to the technical field of intelligent campuses, and the method comprises the steps: obtaining an accumulated starting time length and a single continuous operation time length from laboratory equipment through an acquisition module, obtaining the number of project switching times from a registration terminal, carrying out the time division according to the starting and stopping time nodes of the equipment, and carrying out the time division; obtaining an equipment operation cycle list; acquiring historical experiment time period records from a registration terminal according to the device number to which the abnormal high-value cluster belongs, rearranging the records by adopting a time period recombination mode, and determining an optimized experiment time period arrangement table; and updating the scheduling table of the laboratory management system through the experiment period arrangement table, obtaining the updated scheduling table content, evaluating the improvement amount of the effective experiment time, and obtaining a final evaluation result of the all-day available duration of the equipment. And the all-day available time of equipment is obviously prolonged, and unnecessary loss is reduced.

This invention discloses a control method for an intelligent management cabinet for laboratory instruments and equipment in universities. The steps include: acquiring the current user's height information; determining the corresponding target grid layer from a preset height-grid mapping relationship based on the height information, where users with larger height values ​​correspond to higher-level grids, and users with smaller height values ​​correspond to lower-level grids; within the target grid layer, selecting and opening a target grid from the currently available grids. Preferably, a random selection method is used to achieve grid load balancing within the layer; when there are no available grids in the target layer, the search is automatically expanded to adjacent layers, and the user is prompted before allocation. At least one layer of the cabinet is designated as a dedicated layer for management personnel and is not involved in allocation for ordinary users. When all available layers are full, the system prompts the user to contact laboratory management personnel to borrow backup equipment, supplemented by manual management procedures. This invention simultaneously solves the operational inconvenience and safety hazards caused by neglecting user height differences in existing laboratory equipment management cabinets, as well as the problem of premature aging of some grids due to neglecting grid wear balance. It is particularly suitable for the borrowing and returning management of instruments and equipment in shared scenarios such as university laboratories, research institutions, and vocational training institutions.

The invention provides an AI artificial intelligence training room intelligent safety management method and system, and relates to the technical field of training room safety management, and the method comprises the steps: building a three-dimensional safety perception matrix which comprises a data flow dimension, an energy flow dimension and a personnel flow dimension, performing entropy weight method weighting on elements of the three-dimensional security perception matrix to calculate an initial risk value, inputting the three-dimensional security perception matrix into a space-time causal inference engine, and correcting the initial risk value to obtain a risk entropy value; when the risk entropy value breaks through the dynamic threshold value, an alarm signal is sent out, and prevention and control measures are started. The intelligent level of the training room management process can be improved.

The invention discloses a medical intelligent laboratory management system, which belongs to the technical field of laboratory management and comprises a sample receiving unit, a sample information registration unit, a sample inspection registration unit, a sample inspection prompt unit, a server, a sample inspection judgment unit, an operation information analysis unit and a message queue unit. The sample receiving unit collects sample information by using an optical identification module; the sample information registration unit registers the sample information and feeds back a result whether the sample information is qualified or not; the sample inspection registration unit receives information through the message queue unit according to a registration result, and the sample inspection prompt unit generates different types of prompt signals according to receipt information of the medical terminal; the sample inspection judgment unit decides sample reissuing according to the judgment result; the operation information analysis unit calculates a plurality of indexes and generates a control signal. According to the system, the sample inspection prompting unit distinguishes two abnormal types, a server root cause analysis engine is combined, a sample abnormal root is quickly positioned, and differentiated reissuing suggestions are given, so that the sample quality is effectively guaranteed.

The application relates to a laboratory area division method and device using a decision tree model, which uses a decision tree model to calibrate corresponding laboratory area units for laboratory equipment data and laboratory personnel data. A region classification model is trained. The latest laboratory equipment data and laboratory personnel data are acquired and input into the region classification model, and laboratory area unit data is output. A laboratory area map is generated according to a similarity matrix and by analyzing the similarity of the laboratory area unit data; spatial optimization is carried out based on the laboratory area map, and a laboratory area division map used for representing laboratory area division is obtained. Based on this, the laboratory equipment data and the laboratory personnel data are subjected to laboratory area division by means of a data model and incorporation into a computer system, the data comprehensiveness of a laboratory management data model is improved, and a data processing technical means for laboratory area division is provided.

The invention relates to the technical field of Internet of Things, in particular to a laboratory monitoring system and method based on IoT and digital twinning, the system comprises a sensing module, a communication module and an application module, the communication module is used for connecting data transmission between the sensing module and the application module; the application module is used for mapping the state of a to-be-monitored laboratory based on a preset digital twinborn model, displaying the state of the to-be-monitored laboratory, receiving a user instruction based on the man-machine interaction module, and issuing the user instruction to the sensing module, so that the sensing module adjusts sensing parameters based on the user instruction; the sensing module is used for collecting environment data of the laboratory to be monitored and carrying out early warning when the environment data meets a preset early warning condition. Therefore, the problems of tedious manual operation, high management difficulty, resource waste and the like in the existing laboratory management are solved, and intelligent and real-time monitoring and management of the laboratory environment are realized.

The application discloses an intelligent computer laboratory management method and system based on Internet of Things, and relates to the technical field of computing power resource supervision and management. The method obtains terminal workstation space coordinates, physical network card addresses and cold aisle air supply characteristics based on digital mapping, converts computing power peaks into estimated heat equivalent, and collects personnel trajectory coordinates; the heat equivalent is mapped to generate an estimated heat island boundary, and the air supply characteristics are topologically compared to extract a heat dissipation margin, and the terminal with a positive remaining margin is reserved as a candidate node; target terminals are determined by comprehensively supervising business and security continuity, and an authorized code, a network card address and a trajectory coordinate are associated to generate a hardware-level access control list and distribute tasks; during the task running period, real-time heat island boundaries are reconstructed relying on digital twinning to extract heat dissipation attenuation gradients, and personnel dynamic deviation distances are calculated, and when heat penetration or off-line is indicated, the port is blocked and task live migration is scheduled. The system is used for realizing the above method.

To provide a system and a method for sharing consumable inventory in a novel laboratory management system.SOLUTION: A middleware system 300 includes a middleware software component controlled by a processor, a plurality of instruments 204 and 302 operatively coupled to the middleware software component by a communications network, and a consumable item configured to be removably installed in a first selected instrument of the plurality of instruments. The first selected instrument uses the consumable item to perform tests specified by a laboratory management system, and partially depletes the consumable item. The first selected instrument is configured to update status and usage information regarding the consumable item.SELECTED DRAWING: Figure 3

The invention relates to the technical field of climate environment evaluation, in particular to a climate environment reliability platform quality evaluation method and system based on multi-dimensional indexes. According to the technical scheme, real-time dynamic quality evaluation is carried out by adopting big data analysis based on temperature operation, humidity operation, temperature metering performance, humidity metering performance and equipment function multi-dimensional indexes aiming at independent equipment in a climate environment reliability platform, so that the laboratory management cost can be remarkably reduced, the working efficiency is improved, and the working efficiency is improved. The platform operation capability and the test data accuracy and reliability are accurately judged in real time, emergencies are handled in time, a key means is provided for long-term stability study and judgment, fine management and proper maintenance of equipment, a traditional manual monitoring mode is replaced, deep operation data of the equipment can be obtained in real time, manual one-by-one routing inspection and data recording are not needed, and the working efficiency is improved. And meanwhile, data errors caused by manual operation are avoided, and the digital intelligent management level and the overall working efficiency of a laboratory are improved.

The application discloses a numerical control gateway device applied to workshop and laboratory management and belongs to the field of Internet of Things and industrial Internet gateway. The technical scheme of the application is divided into three modules: a measurement and control integrated power supply module inputs alternating current commercial power, provides stable power supply for the inside of the system after filtering, rectifying and isolation voltage stabilization, simultaneously provides controllable alternating current output for external equipment through a relay driven by a main control chip, and integrates a high-precision measurement chip to monitor input electric energy in real time. A core processing and debugging module is based on an ARM Cortex-M4 main control chip, coordinates data processing, logic control and communication, and reserves a debugging and expansion interface. A multi-interface communication and data acquisition module integrates various industrial interfaces including RS-485, RS-232, CAN, Ethernet and wireless communication, and isolated analog and digital quantity acquisition channels, and reliable data exchange is realized. The whole system is optimized in layout and isolated in design through four layers of PCB boards, and the stability and anti-interference performance of each functional unit are effectively improved.

This invention discloses a comprehensive management platform and method for university laboratories based on big data, belonging to the field of intelligent laboratory management technology. The specific method includes: real-time sensing and collection of multi-source heterogeneous data covering all elements of the laboratory; data fusion, governance, and standardized modeling to construct a unified "laboratory digital twin" data model; multi-level intelligent analysis and judgment based on machine learning to achieve dynamic assessment of safety risks, predictive health management of equipment, and optimized scheduling of resource efficiency; and cross-domain collaborative decision-making and precise service execution based on the analysis results to achieve closed-loop management optimization. This invention solves the problems of data silos, single analytical dimensions, and insufficient cross-domain collaboration in existing university laboratory management technologies, realizing comprehensive sensing, intelligent judgment, and automatic collaboration in university laboratory management, significantly improving the safety, resource utilization efficiency, and management refinement level of university laboratories.

1. Name of this design: Graphical User Interface for Trusted Application Innovation Labs in Electronic Devices. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are its graphical user interface content. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: The graphical user interface is the graphical user interface displayed by the user during the operation of the application. It is used for human-computer interaction, running programs and displaying information. The text displayed in the view is sample content used to show the appearance effect. This appearance design is not limited to the displayed text, and can also be other text or content determined by the user. 6. Human-computer interaction method of graphical user interface: The main view is the homepage of the Trusted Application Innovation Laboratory Management Platform. Clicking the "Laboratory Introduction" button on the navigation bar in the main view will take you to the Laboratory Introduction page, as shown in Figure 1. Clicking the "Database Profile" button on the navigation bar in Figure 1 will take you to the Database Profile page, as shown in Figure 2. Clicking the "Laboratory Tools" button on the navigation bar in Figure 2 will take you to the Laboratory Tools page, as shown in Figure 3. Clicking the "Success Cases" button on the navigation bar in Figure 3 will take you to the Success Cases page, as shown in Figure 4. Clicking the "Ecosystem and Cooperation" button on the navigation bar in Figure 4 will take you to the Ecosystem and Cooperation page, as shown in Figure 5.

This invention relates to the field of automotive crash safety test management technology, and more particularly to a digital and intelligent full-process management system for crash safety laboratories. The system comprises a perception layer, a transmission layer, a core service layer, and an application layer. The perception layer collects sample, asset, and test information and presets constraints and filling rules. The transmission layer pushes data in real time. The core service layer achieves full-element management of tests, samples, assets, calibration, and data through five modules, integrating three types of intelligent models to realize intelligent asset scheduling, inventory early warning, and equipment maintenance. The application layer mines data value based on a joint probability density AI model, providing support for R&D decisions and design. This invention solves the problems of information silos, process disconnects, low data flow and application rates, and lack of full-process data quality control in traditional laboratory management, resulting in low laboratory management efficiency.

The invention discloses a laboratory management system which comprises an external information module and an internal information module. The external information module comprises a client information module, a delegation order management module and a financial management module. The internal information module comprises a basic setting module, a process management module, a report management module, a personnel management module, a calibration management module, an equipment management module and a database module. The personnel management module comprises a personnel information module, a qualification management module and a qualification validity module. The personnel information module is configured to receive personnel information. The qualification management module is configured to access the standard inspection information and the personnel qualification authentication state, and obtains a personnel qualification determination result after determining whether the personnel qualification authentication state accords with the standard inspection information. The qualification validity module is configured to receive the personnel qualification determination result and generate a training list according to the result. According to the invention, laboratory managers can master the personnel qualification authentication state and the equipment maintenance state.