115 results about "Laboratory safety" patented technology

The invention relates to the technical field of laboratory safety management. The experimenter monitoring method based on behavior analysis comprises the steps of performing human body detection and tracking on video information through an RCNN algorithm to obtain experimenter position information in a laboratory, performing face recognition verification on the experimenter information through a DLIB library to obtain experimenter identity information, and performing face recognition verification on the experimenter identity information through a DLIB library. If the identity information of the experimenter is successfully matched, carrying out behavior analysis on the experimenter in the laboratory through a behavior analysis model to obtain behavior state information, and judging whether the operation behavior of the experimenter accords with a preset laboratory safety management rule or not based on the behavior state information of the experimenter; and if the operation behavior of the experimenter does not conform to the preset laboratory safety management rule, safety early warning information is generated, and early warning levels are divided according to the safety early warning information. The method has the effect of improving the safety management of the laboratory.

The invention discloses a laboratory safety state evaluation method and system based on multi-source data fusion, and relates to the field of laboratory safety management.The method comprises the steps that multi-source sensing data of a laboratory are collected and aligned to a unified time axis, and a laboratory sensing data matrix is constructed; grey correlation analysis is introduced, the risk correlation degree between data of each sensor and a preset risk mode is calculated, and identification of a potential risk mode is achieved; the reliability weight is dynamically determined according to the historical stability, baseline deviation and calibration period of the sensor so as to suppress data distortion caused by aging and drifting; and comprehensively calculating the risk correlation degree, the reliability weight and the risk severity coefficient to form weighted risk energy, and generating laboratory risk field energy through space-time coupling superposition so as to calculate a corresponding laboratory risk state level. Therefore, the dynamic quantification and grading judgment of the overall safety state of the laboratory are realized, and the risk identification capability of the complex laboratory environment is improved.

The invention relates to the technical field of safety management and risk assessment, and discloses a laboratory safety intelligent monitoring and early warning method and system, and the method comprises the following steps: S1, building a three-dimensional digital model of a laboratory; s2, deploying a sensor network covering a laboratory; s3, monitoring an operation behavior in real time through a sensor network, and comparing the operation behavior with the operation logic chain; s4, when the sensor network detects that the physical environment is abnormal; s5, collaborating the logic abnormal state, the position and strength of the risk source and the risk type; and S6, performing evolution prediction based on the risk type and the risk source. According to the method, Bayesian fusion reasoning is performed on context information such as multi-dimensional sensor evidence and real-time operation regulations, so that high-precision and high-confidence identification of risk types is realized, and the problem that the risk types cannot be identified due to lack of cognition on field operation activities is solved. And the risk qualitative is fuzzy, the false alarm rate is high, and the real dangerous case and compliance operation interference cannot be distinguished.

The invention relates to the technical field of data processing, in particular to a laboratory safety monitoring method and system based on multi-sensor data. The method comprises the following steps: acquiring standardized data of dimension data of multi-source sensors deployed at different positions in a laboratory at a plurality of sampling moments; obtaining a fused data stream at each sampling moment; constructing a dynamic heterogeneous graph in a laboratory; updating the node state of the dynamic heterogeneous graph in real time by using the fusion data stream, and processing the dynamic heterogeneous graph by using a graph neural network model to extract a graph feature vector sequence representing the overall state of the laboratory scene; and inputting the graph feature vector sequence into a time sequence prediction model, and outputting a risk vector so as to monitor the safety risk of the laboratory environment. According to the scheme of the invention, the safety monitoring of the laboratory environment can be safely and accurately carried out.

The invention provides a laboratory safety monitoring method and system based on multi-data fusion. The method comprises the steps that S1, a data acquisition module monitors and acquires environmental data in a laboratory in real time; environment data in a laboratory are preprocessed; performing weight distribution on the laboratory internal environment data and the manual alarm function triggering state, and introducing a comprehensive threat index; s2, calculating a comprehensive threat index according to the collected laboratory internal environment data, the manual alarm function trigger state and the weight; s3, judging a security threat level based on the comprehensive threat index; judging a security threat type based on the security threat level, the laboratory internal environment data and the manual alarm function triggering state; and S4, taking security countermeasures according to the security threat type. The comprehensive threat index can comprehensively reflect the safety condition in the laboratory; and safety countermeasures are taken for the safety threat type, so that the accuracy of safety condition identification and the pertinence and effectiveness of the countermeasures are improved, and personnel and property loss is avoided.

The invention discloses an AIoT-based intelligent laboratory safety monitoring method and system. The method comprises the steps of S1, collecting laboratory multi-source heterogeneous data and performing preprocessing; s2, respectively extracting gas diffusion characteristics and thermal infrared characteristics according to the preprocessed gas concentration sequence and thermal infrared image sequence, and then calculating fusion characteristics; s3, physical constraint characteristics are calculated according to gas diffusion characteristics and thermal infrared characteristics, and a risk thermodynamic diagram is generated; s4, extracting a personnel bounding box and personnel behavior characteristics according to the preprocessed personnel video sequence, calculating global risk coordinates, and generating a personnel risk embedding vector; s5, generating an updated risk thermodynamic diagram, calculating a risk score, and generating a risk early warning signal; and S6, triggering a physical device response according to the risk early warning signal, and collecting a device state feedback log. The problem that a traditional laboratory safety monitoring method is difficult to carry out early warning in combination with multi-source data can be solved.

The invention relates to the technical field of laboratory safety management, and discloses an AI model fused laboratory safety management risk intelligent pre-judgment method and system. The method comprises the steps of collecting original monitoring data of a laboratory monitoring area, and extracting risk signals and abnormal signals corresponding to abnormal events from the original monitoring data; obtaining relevance characteristics between the risk signals and adjustment characteristics of the risk signals by abnormal events; risk features representing risk differences are generated according to the features, and target risk probability distribution is obtained based on the risk features; and performing interference suppression processing on the original monitoring data according to the target risk probability distribution to separate a prediction risk waveform of the target risk source. According to the method, through deep mining of the relevance of risk signals and the adjustment effect of abnormal events, the accuracy of risk pre-judgment is improved, potential risks can be effectively captured, and a more intelligent and more reliable risk pre-judgment means is provided for laboratory safety management.

The invention provides a college laboratory safety management and risk identification intelligent agent platform, which relates to the technical field of safety management, and comprises the following steps: obtaining environmental parameters through edge computing nodes to carry out real-time risk analysis, and setting multi-level safety threshold grading early warning; a mixed decision framework combining a graph neural network and reinforcement learning is adopted, a dynamic reasoning mechanism is constructed based on a security management knowledge graph, and intelligent research and judgment and co-processing of multi-dimensional security risks are realized; and finally, feeding back a disposal result to a safety management personnel terminal. According to the invention, the laboratory safety risk identification precision and the emergency disposal efficiency are improved, and intelligent safety management is realized.

The invention relates to a laboratory safety detection method and device, equipment and a medium. The method comprises the steps that a networking retrieval module is adopted to select a tool for large-scale data retrieval; guiding an intelligent agent RAG module to screen and verify information by adopting a thinking chain technology; in the generation stage, a contrast decoding method is used, the confidence difference between the reference lexical elements and the illusion lexical elements is calculated, and confidence reweighting is conducted on the reference lexical elements and the illusion lexical elements so as to strengthen real safety information and inhibit model illusion content. And inputting the laboratory scene image, the user input text instruction, the structured comprehensive query instruction and the effective information of all rounds into a multi-mode large language model reinforced by a thinking chain technology to generate a laboratory safety detection report, and proactively providing an optimization suggestion of the laboratory safety layout based on the laboratory safety detection report. According to the invention, the reasoning capability of the model in a complex security scene is enhanced, and the accuracy and reliability of a detection result are improved.

The invention relates to the technical field of laboratory safety risk assessment, and discloses a laboratory safety risk dynamic assessment method based on machine learning, and the method comprises the steps: S1, collecting the multi-source real-time data of a laboratory environment and equipment; s2, carrying out preprocessing and time sequence synchronization on the multi-source real-time data; s3, extracting time sequence features from the time sequence data based on a sliding time window; s4, inputting the feature vector into a machine learning model with an online learning capability; s5, distributing according to the risk prediction result and the current data; and S6, when the risk level reaches a preset condition, triggering laboratory safety early warning and linkage control. Incremental updating is carried out on the machine learning model by inputting feature vectors in real time, adaptive iteration adjustment is carried out on a to-be-updated parameter set based on prediction error changes of a continuous time window, risk judgment is corrected in time along with environment changes, and the real-time performance, sensitivity and stability of model risk prediction are improved.

The invention discloses a laboratory safety intelligent monitoring management system and method based on the Internet of Things and the data driving technology. The monitoring management system comprises a laboratory environment monitoring module, an experimenter behavior monitoring module, an experimental equipment state monitoring module, a hazardous chemical substance management monitoring module, an intelligent potential safety hazard early warning and evaluation module and an emergency response remote cooperative processing module, and the six modules carry out cooperative processing. The monitoring management method comprises five modes of laboratory environment monitoring, experimenter behavior monitoring, experimental equipment state monitoring, hazardous chemical substance management monitoring and emergency response remote cooperative processing. According to the invention, a newly proposed time sequence prediction attention mechanism module prediction unit is adopted, the prediction accuracy is improved, various factors which are easy to cause experimental accidents in a laboratory are comprehensively considered, early warning can be carried out for different abnormal conditions, and effective supervision of laboratory safety risks is ensured.

The invention relates to the technical field of laboratory intelligent management, and discloses a hazardous chemical substance laboratory supervision emergency system, which takes a central processing unit as a core, and integrates seven modules of multi-dimensional perception, ledger registration, laboratory digital twinborn model library, access cross validation, behavior identification intervention, emergency response strategy and mobile terminal interaction assistant. A complete closed-loop management system from hazardous chemical substance taking compliance verification, personnel operation safety monitoring to intelligent emergency response is constructed, and the hazardous chemical substance laboratory safety management level is comprehensively improved. The system can realize real-time linkage of data of each module, break information islands, avoid access violation from the source, block operation risks in real time and efficiently deal with emergencies, meanwhile, improves emergency efficiency by means of mobile terminal interaction assistant navigation, comprehensively strengthens the full life cycle supervision ability of hazardous chemicals, remarkably reduces the occurrence rate of laboratory safety accidents, and has a good application prospect. And the event emergency disposal efficiency is improved, and the intelligence and refinement level of overall safety management is improved.

The invention relates to the technical field of risk management and control, in particular to a laboratory dangerous chemical whole-process risk management and control method and system based on an AI large model. Under the condition that the gas concentration does not exceed the standard, the potential chemical reaction risk is predicted by depending on the gas component proportion, the reaction triggering condition and the environmental data, the potential safety hazard problem caused by the potential reaction is solved, the gas diffusion speed and the toxicity grade of the reaction product are combined through real-time monitoring and analysis of each control sub-region, and the safety of the reaction product is improved. According to the method, the reaction risk probability and the delay risk probability can be accurately calculated, an effective early warning signal and a management and control instruction are generated before the risk occurs, and the real-time performance and accuracy of laboratory safety management are remarkably improved, so that the pre-judgment and response capability of a laboratory to dangerous chemical leakage and reaction risk is effectively improved, and the safety of the laboratory is improved. Preventive measures can be taken when potential dangers do not appear, so that safety accidents are avoided.

The invention relates to the technical field of laboratory safety monitoring, and discloses a laboratory hazardous gas leakage monitoring method and system, and the method comprises the steps: configuring an electronic identity tag for a hazardous gas related article, deploying a read-write device in an operation region, and automatically generating a temporary operation voucher with timeliness when the article enters the operation region; the environment concentration is monitored in real time through a gas sensor, and when abnormity is detected, whether a matching voucher exists or not is checked firstly so as to distinguish normal operation and abnormal leakage; according to the method, through a dynamic coupling mechanism of the operation certificate and the area sensing, controlled release and accidental leakage are distinguished, the balance problem of traditional threshold value alarm between sensitivity and false alarm rate is improved, and the reliability of the system is improved. And meanwhile, the accuracy of leakage detection and the robustness of the system are improved by combining near-field gradient verification and an air flow abrupt change self-adaptive strategy.

The embodiment of the invention provides a multi-level early warning method and system for faults of intelligent equipment and a related device. The method comprises the following steps: receiving edge node data from edge nodes of a laboratory; according to the historical operation data of the plurality of intelligent devices, the environment baseline of the laboratory and the fault records of the plurality of intelligent devices, generating healthy operation thresholds corresponding to the plurality of intelligent devices; performing weighted scoring on the edge node data, and dividing risk levels of the plurality of intelligent devices according to weighted scores and a health operation threshold value; executing an early warning strategy according to the risk level grading; and establishing an association relationship among the fault events of the plurality of intelligent devices, the experiment batch information and the experiment environment change, and dynamically adjusting a healthy operation threshold according to the association relationship. Therefore, through multi-dimensional sensing and dynamic execution of the early warning strategy, active prevention and grading disposal of equipment faults are realized, the real-time performance of safety management of the drug laboratory is effectively improved, and accurate monitoring of early warning of the laboratory is realized.

The utility model provides a laboratory gas leakage linkage alarm control device, and relates to the technical field of laboratory safety monitoring. The laboratory gas leakage linkage alarm control device comprises a control device body, a mounting plate is mounted on the rear surface of the control device body, a fixing plate is arranged on the rear side of the mounting plate, splitting mechanisms which are symmetrically distributed are arranged at the joint of the mounting plate and the fixing plate, and fixing mechanisms are arranged at the joints of the splitting mechanisms and the mounting plate. A working cavity is formed in the mounting plate, a linkage mechanism is contained in the working cavity, an adjusting mechanism is arranged at the intersection of the linkage mechanism and the fixing mechanism, and a rotating mechanism is arranged at the driving end of the linkage mechanism. The laboratory gas leakage linkage alarm control device provided by the utility model has the advantages that the control device body can be conveniently and quickly disassembled and assembled, and further the maintenance work of workers on the control device body is guaranteed.

The invention discloses a laboratory safety assessment method based on machine vision, and relates to the technical field of laboratory safety monitoring, and the method comprises the steps: carrying out the standard processing of collected laboratory comprehensive data, obtaining a standard monitoring image, carrying out the feature element setting of the standard monitoring image, and obtaining a feature recognition matrix; constructing a virtual visual space, performing supplementary positioning on the virtual visual space to obtain a virtual laboratory model and an image acquisition node, and performing feature acquisition on the standard monitoring image through a feature recognition matrix based on the virtual visual space to obtain a monitoring feature picture; performing periodic comparison on the monitoring feature pictures to obtain a difference comparison result, and performing safety judgment on the laboratory according to the difference comparison result to obtain an anomaly evaluation result; laboratory safety is greatly improved, accident loss is reduced, and the safety management level of a laboratory is improved.

The invention relates to the technical field of laboratory safety management and control, and particularly discloses a laboratory safety comprehensive management and control method based on a multi-modal model, and the method comprises the following steps: S1, obtaining a material list and an operation time sequence table of an experiment, querying hazard parameters of a material in different physical states based on a preset safety database, calculating the hazard intensity value of each experimental operation; s2, collecting laboratory environment data in real time, and generating current spatial state distribution; according to the hazard intensity value, positioning in spatial distribution and calculating a risk value when each operation is executed; s3, pre-defining a strategy function, and determining hazard clearing efficiency required by different risk levels; and according to the risk value, matching a clearing efficiency requirement, solving and outputting an equipment control parameter sequence meeting the requirement, and finally, accurately adjusting the clearing equipment according to the equipment control parameter sequence.

This invention belongs to the field of laboratory safety monitoring technology, and particularly relates to a method and system for real-time intervention of experimental operation violations based on multimodal behavior recognition. It includes collecting multimodal operation data during the experiment; constructing a database of standard operating procedures (SOPs); identifying the currently executed action; comparing the currently executed action with data in the SOP database in multiple dimensions; calculating a deviation score based on the comparison results; and, combined with preset hazard coefficients, environmental coefficients, and personnel coefficients, using a fuzzy logic algorithm to determine the risk level of the experimental violation, thus achieving real-time intervention for experimental operation violations. This invention is based on the deployment and data acquisition of a multimodal sensor network, performing multidimensional modeling of standard operating procedures, and then using a real-time behavior recognition algorithm for multidimensional comparison and violation determination, thereby initiating corresponding intervention measures to promptly eliminate safety hazards, resulting in significant social and economic benefits.

The invention discloses an intelligent safety control system for an organic chemistry laboratory, and relates to the field of intelligent control. Wherein a laboratory data acquisition module, an experimental data acquisition module, a laboratory data management module, an experimental data analysis module, a data analysis early warning module and an intelligent safety control module are arranged; the laboratory data acquisition module acquires laboratory data information; the experimental data acquisition module acquires experimental data information; the laboratory data management module manages the laboratory data information and constructs a laboratory data graph; the experimental data analysis module obtains a corresponding experimental mapping map according to the experimental data information and the laboratory data map; the data analysis early warning module obtains experiment early warning information according to the experiment mapping map; the intelligent safety control module performs coordination processing according to the experiment early warning information to obtain corresponding laboratory coordination control information; the management efficiency of intelligent control is improved.

The application discloses a high-altitude environment laboratory safety protection system, which comprises a control room, a transition room and a high-altitude environment laboratory. The control room is communicated with the transition room through a first transition door and a third pipeline, and the transition room is communicated with the atmosphere environment through a first pipeline. The transition room is communicated with the high-altitude environment laboratory through a second transition door, a second pipeline and a fourth pipeline. A first control component and a second control component are respectively formed on the first pipeline and the second pipeline in the transition room. A three-way adjusting piece is used for connecting the first pipeline, the second pipeline and the transition room. A third control component is formed on the first pipeline in the control room. A fourth control component is formed on the fourth pipeline in the high-altitude environment laboratory. A first differential pressure sensor is formed in the control room or the transition room. A second differential pressure sensor is formed in the transition room or the high-altitude environment laboratory. The first transition door and the second transition door are in a mutually exclusive relationship. The application can avoid the health risks of the operating personnel when entering and leaving the high-altitude environment laboratory, and ensure the health and safety of the operating personnel.

The utility model discloses a travelling security camera, which belongs to the technical field of laboratory safety, and comprises a security camera and a support structure arranged on the security camera and used for supporting the security camera, the support structure comprises two U-shaped frames and two winding rollers rotationally mounted in the two U-shaped frames respectively, and the two guide sliding ropes are respectively arranged on the two winding rollers. During use, the L-shaped connecting plates on the two sides can be fixed to a wall surface or a support through bolts, the guiding slip rope is straightened, the sliding frame and the security camera can be supported through the guiding slip rope, and the sliding frame and the security camera can be controlled to horizontally move in the direction of the guiding slip rope by starting the motor. The security and protection camera has the advantages that a cyclic monitoring effect of the security and protection camera is achieved, the guide slip rope wound on the winding roller can be wound and unwound by rotating the linkage shaft so as to change the moving distance and range of the security and protection camera, and adjustment can be performed according to the space of an installation environment.

The application discloses a laboratory safety authentication method and device based on a Lims system, relates to the technical field of safety authentication, and solves the technical problem that the safety authentication system in the prior art is difficult to adapt to the safety authentication of specific conditions of relevant personnel, thereby reducing the efficiency of safety authentication. The method comprises the following steps: obtaining reservation information of a laboratory, generating a reference threshold value based on reservation item information in the reservation information; obtaining verification information corresponding to a pilot verification item and a plurality of verification items of the laboratory; generating a pilot verification result based on the verification information corresponding to the pilot verification item and an influence coefficient corresponding to each verification item; generating an item matching degree based on the verification information corresponding to each verification item; and generating a final authentication result based on the item matching degree, the influence coefficient and an item reference threshold value of each verification item. The accuracy of safety authentication is improved, and the efficiency of safety authentication is improved.

A method and system for AR-based graded management education of laboratory safety risk are provided, which includes following steps: collecting laboratory image data and sensor data and obtaining a risk grade matching rule of a laboratory; identifying image feature data of the image data and sensor feature data of the sensor data, converting matched image feature data into a laboratory equipment name and converting matched sensor feature data into an equipment model; inputting the equipment name and a corresponding equipment model and quantity into the risk grade matching rule of the laboratory, and outputting a risk grade of a current laboratory according to the risk grade matching rule of the laboratory; and fusing and matching a AR template image corresponding to the identified and output risk grade and real image information according to preset AR template images for various risk grades, so as to output alarm information.

The invention relates to the technical field of environment monitoring and safety management, in particular to a laboratory monitoring system which comprises an environment sensing module, a data processing and analysis module, a signal distribution module and an execution module. The invention provides a laboratory monitoring system, which is used for judging whether a laboratory is in a normal or abnormal environment by collecting environmental data in real time, filtering noise by using a wavelet denoising algorithm and combining abstract features extracted by an LSTM network and using a support vector machine model. The system can intelligently evaluate the environment state, triggers corresponding safety early warning signals according to the judgment result, such as adjusting temperature, humidity, gas concentration and pressure, and automatically executes protection operation. The system improves the automation level of laboratory safety management, can timely respond and prevent potential dangers, and ensures the stability of a laboratory environment and personnel safety.

The utility model relates to the field of chemical reaction devices, in particular to a chemical laboratory safety reaction device which comprises an operation table, an operation frame, a reaction device, a connecting device, a chemical test tube, a heating frame, a sealing cap, a threaded column and an injection agent pipe. A reaction device and a chemical test tube are installed in the operating table and the operating frame, a connecting device is installed on the upper side of the reaction device, three agent injection pipes are installed on the side wall of the reaction device, sealing caps are installed at the top ends of the agent injection pipes, and a heating frame is installed in the middle of the operating table; the reaction device can be stably fixed through the fixing table and the operation frame, it is guaranteed that the reaction device cannot shake in the chemical reaction process, and the experiment safety is improved.

The present application relates to the technical field of laboratory safety, and more particularly to a laboratory safety early warning system, comprising a registered module, a portrait tracking module, a digital twin module, a general monitoring module, a monitoring analysis module for determining the monitoring mode of the laboratory, and a monitoring control module, wherein the monitoring control module determines a safety warning library according to the experimental content of each experimenter to identify abnormal behavior of the experimenter, determines the running experimental equipment according to the experimental content and the experimental video to monitor and update the corresponding part of the digital twin model in real time, and controls the general monitoring module to perform general monitoring on the experimental area to determine the influence representation trend of the non-experimental area on the experimental area to determine whether to perform safety early warning. The present application solves the problems of incomplete monitoring, untimely early warning, difficult accident cause tracing, and unreasonable resource utilization in the laboratory safety management of the prior art.

The application relates to the technical field of laboratory intelligent management, and discloses a hazardous chemical laboratory supervision emergency system, which takes a central processing unit as a core, integrates seven modules of multidimensional perception, account registration, a laboratory digital twin model library, cross verification of taking and using, behavior recognition intervention, emergency response strategies and a mobile terminal interaction assistant, constructs a complete closed-loop management system from hazardous chemical taking compliance verification, personnel operation safety monitoring to intelligent emergency response, and comprehensively improves the safety management level of a hazardous chemical laboratory. The system can realize real-time linkage of data of each module, break information islands, avoid taking violations from the source, block operation risks in real time, efficiently dispose of emergency conditions, rely on the mobile terminal interaction assistant to improve emergency efficiency, comprehensively strengthen the whole life cycle supervision capability of hazardous chemicals, significantly reduce the incidence of laboratory safety accidents, improve the efficiency of event emergency disposal, and improve the intelligentization and refinement level of overall safety management.

The invention relates to the field of laboratory safety control, in particular to a laboratory environment safety control system, which comprises an information input module used for dividing a laboratory into N sub-regions and supporting manual setting of the sub-regions as experimental sub-regions and setting of a standard temperature and humidity interval; the temperature and humidity calculation module is used for calculating second temperature and humidity information of each sub-region according to the first temperature and humidity information, and marking the second temperature and humidity information of the experimental sub-region as third temperature and humidity information; the temperature and humidity control module is used for judging whether the third temperature and humidity information is in a standard temperature and humidity interval or not; according to the method, when the temperature and humidity information in the laboratory is calculated, the influence of door opening and closing and a temperature and humidity adjusting system on the temperature and humidity in the laboratory is considered, and compared with a common calculation method, the precision of calculating the temperature and humidity of each subarea of the laboratory can be effectively improved.

The present application relates to the technical field of biological sample bank equipment management and laboratory safety, in particular to a low-temperature storage equipment shifting system for a biological sample bank and an application method thereof, which comprises a shifting bearing platform, an environment maintaining module, a safety monitoring module and a cooperative control module.The shifting bearing platform is used for bearing and moving the equipment; the environment maintaining module is used for adjusting the internal environment information of the equipment; the safety monitoring module is used for monitoring and obtaining monitoring information, including the posture information, position information and speed information of the shifting bearing platform, the environment information within the preset range of the equipment, the internal environment information of the equipment and the path obstacle information; the cooperative control module is used for moving path planning, controlling the moving range and coordinating the work of the environment maintaining module according to the monitoring information, and performing risk analysis, triggering risk warning and emergency disposal.The present application realizes smooth movement in the shifting process, whole-process low-temperature maintenance, multi-dimensional state monitoring and active risk warning through the integrated and intelligent shifting system, and guarantees the activity of samples and the safety of equipment.